Market-based participation of energy storage scheme to support renewable energy sources for the procurement of energy and spinning reserve

Market-based participation of energy storage scheme to support renewable energy sources for the procurement of energy and spinning reserve

Accepted Manuscript Market-based Participation of Energy Storage Scheme to Support Renewable Energy Sources for the Procurement of Energy and Spinning...

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Accepted Manuscript Market-based Participation of Energy Storage Scheme to Support Renewable Energy Sources for the Procurement of Energy and Spinning Reserve

Anuj Banshwar, Naveen Kumar Sharma, Yog Raj Sood, Rajnish Shrivastava PII:

S0960-1481(18)31441-1

DOI:

10.1016/j.renene.2018.12.009

Reference:

RENE 10884

To appear in:

Renewable Energy

Received Date:

22 August 2017

Accepted Date:

04 December 2018

Please cite this article as: Anuj Banshwar, Naveen Kumar Sharma, Yog Raj Sood, Rajnish Shrivastava, Market-based Participation of Energy Storage Scheme to Support Renewable Energy Sources for the Procurement of Energy and Spinning Reserve, Renewable Energy (2018), doi: 10.1016/j.renene.2018.12.009

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Energy Demand Reserve Demand

800

Disaggregated Market (For EM & SRM)

Bidding Mechanism

700

Power (MW)

600 500

Payment Mechanism (As per

400 300

CPPs bid into the market

200 100 0 0

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Hour

SO Determines Energy & SR requirements

Market based Procurement of Energy & Spinning Reserve

SO clears the EM by optimizing the bidding & obtain schedule and PCE

SO opens the market for bidding from market participants

SO clears the SRM on the basis of results obtained in EM

Payment to the market participants as per their capacities scheduled in EM & SRM

VPPs bid into the market

RPPs bid into the market WPP Availability PVP Availability

100

80 PSU(WPP) Available Capacity

70

80

Capacity (MW)

Power Available (MW)

60 50 40 30

Capacity available at 𝐕𝐏𝐏𝐖𝐏𝐏 to bid into the market

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SRM

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WPP - Surplus Capacity (MW) PSU(WPP) - Available Capacity (MW)

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WPP - Surplus Capacity (MW)

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Capacity Scheduled (MW)

Capacity Scheduled (MW)

Proposed VPP (Hybrid RPP-PSU) Operation

Power Available (MW)

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(b)

Hour

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VPP(WPP)_EM

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Hours

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Hour

VPP(WPP)_RM

PSU(WPP) Available Capacity 80 30

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0 2 4 6 8 10 12 14 16 18 20 22 24

Hour

Hour

(e)

(c)

WPP bid into the market

Schedule of WPP in EM & SRM

Surplus capacity available at WPP after EM & SRM

Capacity available at PSU at WPP to bid into the market

Final schedule of 𝐕𝐏𝐏𝐖𝐏𝐏 in EM & SRM

ACCEPTED MANUSCRIPT

1 2 3 4 5

Market-based Participation of Energy Storage Scheme to Support Renewable Energy Sources for the Procurement of Energy and Spinning Reserve

7

Anuj Banshwar*a, Naveen Kumar Sharmab, Yog Raj Soodc, Rajnish Shrivastavad aNoida Institute of Engineering & Technology, G. Noida, U.P., India bIKG Punjab Technical University, Punjab, India cNational Institute of Technology, Hamirpur, India dAdvisor, Mahindra Educational Institutions, Telangana, India

8

Abstract: Energy Storage Scheme (ESS) is of great importance to realize energy management

9

and to optimally utilize Renewable Energy (RE) integration in the electricity system. An

10

increasing exploitation of RE in electricity system raises the concern about the need for Ancillary

11

Services (AS) in a power system. These services are required for maintaining the reliability and

12

security of the supply. This paper proposes a market-based participation of ESS to support large-

13

scale RE penetration for the procurement of energy and AS using Virtual Power Plant (VPP) in a

14

deregulated environment. The proposed VPP consists of a pumped-storage system as one of the

15

recognized ESS and Renewable Power Producers (RPPs). This optimization problem is

16

formulated and solved using an optimal power flow technique which considers network

17

constraints and power flow limits. Spinning Reserve (SR) as one of the main AS is considered in

18

this paper, which is procured under Spinning Reserve Market (SRM). The ability of the proposed

19

approach to provide both energy and SR is tested on 3 case studies and demonstrated by

20

considering a modified IEEE-30 bus test system. Results show that the VPPs can play a

21

significant role in increasing the penetration of RE for the procurement of energy and AS.

22

Keywords: Ancillary Services; energy procurement cost; energy storage schemes, reserve

23

procurement cost; spinning reserve markets; virtual power plant.

24

Nomenclature:

6

25 26

*Corresponding

Author: Anuj Banshwar (Email: [email protected])

1

Abbreviations

ACCEPTED MANUSCRIPT

27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56

AS ASM AC ARC BES CES CPP DAM EM ESS FRP GHG LFAC OR OPF PAB PC PCE PCR PSP RE RES RPP STM SB SR SRM SO VPP

57

Symbols

58 59 60

Ξ·PSU

Efficiency of the Pumped-Storage Unit

Ξ¦ E1,E2,E3,E4,E5

Phase angle at different buses Energy loads on a test system

61

ARCsi

Available reserve capacity of 𝑖 supplier

62

ACsi

Available capacity of 𝑖 supplier

63 64

Esi

Capacity of 𝑖 selected supplier in EM

EL

Total energy demand in the system

65

max EPVP(h) Maximum max EiRPP(h) Maximum max E si Maximum max EWPP(h) Maximum capacity sch EPVP(h) Combined

66 67 68 69

Ancillary Services Ancillary Service Markets Available Capacity Available Reserve Capacity Battery Energy Storage Conventional Energy Sources Conventional Power Plants Day Ahead Markets Energy Market Energy Storage Scheme Flexible Ramping Product Green House Gas Low-Frequency AC Operating Reserve Optimal Power Flow Pay-As-Bid Procurement Cost Procurement Cost of Energy Procurement Cost of Reserve Pumped Storage Plant Renewable Energy Renewable Energy Source Renewable Power Producers Short-Term Market Social Benefit Spinning Reserve Spinning Reserve Market System Operator Virtual Power Plant

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

capacity offered by the PVP in the electricity market in β„Ž hour π‘‘β„Ž

π‘‘β„Ž

capacity offered by the 𝑖 RPP in the electricity market in β„Ž hour π‘‘β„Ž

capacity offered by the 𝑖 supplier in the electricity market π‘‘β„Ž

offered by the WPP in the electricity market in β„Ž hour π‘‘β„Ž

schedule of PVP in EM and SRM in β„Ž hour

2

ACCEPTED MANUSCRIPT

sch

π‘‘β„Ž

π‘‘β„Ž

70

EiRPP(h)

71

EWPP(h) Combined schedule of WPP in EM and SRM in β„Ž hour

72

EPVP (h)

73

ERPP (h)

74

EWPP (h)

75

EPVP

76

EiRPP

77

EWPP

78

EPVP

79

EiRPP

80

EWPP

81

E PVP (h)

82

EiRPP(h)

83

EWPP(h) Surplus capacity available at WPP after β„Ž hour

84

EPSU (h + 1)

85

EPSU (h + 1)

86

EPSU

87 88 89 90

g(V,Ο•) h H MVAfij

91 92 93

MVAf

Combined schedule of 𝑖 RPP in EM and SRM in β„Ž hour

sch

π‘‘β„Ž

sch

EM

sch

EM

sch

EM

Avl SRM

π‘‘β„Ž

Capacity scheduled from WPP in EM in β„Ž hour π‘‘β„Ž

Available capacity at PVP for participation in SRM in β„Ž hour

(h)

Available capacity at 𝑖 RPP for participation in SRM in β„Ž hour

(h)

Available capacity at WPP for participation in SRM in β„Ž hour

(h)

Capacity scheduled from PVP in SRM in β„Ž hour

(h)

Capacity scheduled from 𝑖 RPP in SRM in β„Ž hour

(h)

Capacity scheduled from WPP in SRM in β„Ž hour

SRM

Avl SRM

SRM

π‘‘β„Ž

Capacity scheduled from RPP in EM in β„Ž hour

(h)

Avl

sch

π‘‘β„Ž

Capacity scheduled from PVP in EM in β„Ž hour

sch SRM

sch SRM

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

surp

Surplus capacity available at PVP after β„Ž hour

π‘‘β„Ž

surp

Surplus capacity available at 𝑖 RPP after β„Ž hour

π‘‘β„Ž

surp

π‘‘β„Ž

π‘‘β„Ž

avl

PVP

avl

RPP

avl

π‘‘β„Ž

Available capacity offered by PSUPVP in the next (β„Ž + 1) interval π‘‘β„Ž

Available capacity offered by PSURPP in the next (β„Ž + 1) interval π‘‘β„Ž

WPP

(h + 1) Available capacity offered by PSUWPP in the next (β„Ž + 1) interval

max ij

Power flow equation Hour Next interval (β„Ž + 1) MVA flow between bus 𝑖 and bus 𝑗 Maximum MVA flow between bus 𝑖 and bus 𝑗

Ns_EM

Total number of suppliers in EM market

Ns_SRM

Total number of suppliers available in SRM

94

Pi

Calculated real power at 𝑖 PQ bus

95

P

Specified real power at 𝑖 PQ bus

96

Pm

Calculated real power at 𝑖 PV bus

97

Pm

Specified real power at 𝑖 PV bus

98

Pgi

Real power generation at 𝑖 PV bus

99

P

Maximum real power generation allowed at 𝑖 PV bus

100

max gi min P gi

101

PCEsi(Esi)

Procurement cost of energy to the accepted capacity 𝐸𝑠𝑖in EM from the 𝑖 selected supplier

102

PCRsi(Rsi)

Procurement cost of SR to the accepted capacity 𝐸𝑠𝑖in SRM from the 𝑖 selected supplier

103

PEsi

Price of capacity offered by the 𝑖 supplier in EM

104

PRsi

Price of capacity offered by the 𝑖 supplier in SRM

net i

net

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

Minimum real power generation allowed at 𝑖 PV bus π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž π‘‘β„Ž

3

ACCEPTED MANUSCRIPT

105

PSUPVP

Pumped-storage unit concerned to PVP

106 107

PSUiRPP

Pumped-storage unit concerned to 𝑖 RPP

PSUWPP

Pumped-storage unit concerned to WPP

108

Qi

Calculated reactive power at 𝑖 PQ bus

109

Q

110

Qgi

Reactive power generation at 𝑖 PV bus

111

Q

max gi min Q gi

Maximum reactive power generation allowed at 𝑖 PV bus

RL

Total SR demand in the system

114

Rsi

Capacity 𝑖 selected supplier in SRM

115 116 117

RRi

Ramp Rate of the 𝑖 supplier

V

Voltage magnitudes at different buses

Vi

Phase voltage at 𝑖 bus

118

V

Minimum phase voltage at 𝑖 bus

119

max i min V i

120

VPPiRPP

Virtual Power Plant concerned to 𝑖 RPP

121

VPPPVP(H)

max

Maximum capacity offered by the VPPPVP in EM and SRM in 𝐻 hour

122

VPPRPP(H)

max

Maximum capacity offered by the VPPRPP in EM and SRM in 𝐻 hour

123

VPPWPP(H)

max

Maximum capacity offered by the VPPWPP in EM and SRM in 𝐻 hour

124

VPPPVP (H)

Capacity scheduled from VPPPVP in EM in 𝐻 hour

125

VPPRPP (H)

sch

Capacity scheduled from VPPRPP in EM in 𝐻 hour

126

VPPWPP (H)

sch

Capacity scheduled from VPPWPP in EM in 𝐻 hour

127

VPPPVP

128

VPPRPP

129

VPPWPP

112 113

π‘‘β„Ž

π‘‘β„Ž

net i

π‘‘β„Ž

Specified reactive power at 𝑖 PQ bus π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

Minimum reactive power generation allowed at 𝑖 PV bus π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž π‘‘β„Ž

Minimum phase voltage at 𝑖 bus π‘‘β„Ž

sch

EM

EM

EM

Avl SRM

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

π‘‘β„Ž

(H)

Available capacity at VPPRPP for participation in SRM in 𝐻 hour

(H)

Available capacity at VPPRPP for participation in SRM in 𝐻 hour

(H)

Available capacity at VPPPVP for participation in SRM in 𝐻 hour

Avl SRM

Avl SRM

π‘‘β„Ž

π‘‘β„Ž

130 131

1. INTRODUCTION

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Recent years have witnessed various countries across the globe deploying a mix of several

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systems for electricity generation purposes. The reliance on fossil fuels results in most significant

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threats to environmental pollutions, including Green House Gas (GHG) emissions that result in

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worst and irreversible harm to the climate. Non-diminishing RE represents a possible alternative

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to reduce GHG emissions, improve energy security and decrease dependency on diminishing

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supplies of fossil fuels for energy generation [1]. The penetration of Renewable Energy Source

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(RES) in the electrical system is gradually increasing, and the share of Conventional Energy 4

ACCEPTED MANUSCRIPT

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Sources (CESs) like coal, gas, and oil is undergoing a declining stake in the primary inputs to the

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generation mix [2]. At present, RE represents the only clean and constantly growing source of

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electricity generation worldwide. The year 2015 was an extraordinary year for RE with the

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largest global capacity additions of around 213 TWh [3]. The long-lasting RESs produce more

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eco-friendly power but put greater pressure on power system operations and the electricity

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markets due to their variable and intermittent nature [4].

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Due to enormous growth in energy demand in recent years, power system equipment needs

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to run at their full capacities. This possibly will lead to unplanned outages and failure of the

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equipment. To match generation and demand on a real-time basis, some sort of services are

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required that can maintain reliability and security of the supply. These so-called services are

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commonly known as ancillary services [5]. These are simply classified into frequency control

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services (like regulation, load following, operating reserves), voltage control services (through

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reactive power support) and emergency services (by black-start services) and are considered as

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main AS in almost every electricity market [6].

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Special consideration in this paper is given to the procurement of capacity based Operating

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Reserve (OR) that include Spinning Reserve (SR). SR is a service that can be supplied by the

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resources that are synchronized with the grid and able to deploy its capacity within ten minutes

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of receiving dispatch signals from the System Operator (SO) [7, 8]. These services in the

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deregulated environment are mainly procured through the market clearing mechanism. These are

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the optimization techniques that involve the determination of quantities produced and consumed.

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1.1 Literature Survey

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Traditionally, AS are provided widely from traditionally gas Conventional Power Plants (CPPs)

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which has relied heavily on fossil fuels like coal, oil, and natural gas. The progressive evolution

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of competitive electricity sector is resulting in a greater interest in the sufficient and efficient

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utilization of RES in the generation mix [9]. Nowadays, similar to CPPs, RPPs are also proficient

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of participating in energy as well as in Ancillary Service Markets (ASM) to provide a full range

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of AS like frequency support, operating reserves and reactive power services [10, 11]. These

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variable and intermittent sources are participating in AS markets in order to maximize their

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profits competitively due to their fast responding ability and declining cost of electricity

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production. In general, RPPs agrees with certain production level in competitive markets, which

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must be delivered in the contracted periods. 5

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170

Several kinds of literature are available on the participation of RPPs in electricity markets to

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provide both energy and OR. A critical review of several control functionalities like inertial

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control to the secondary control in wind energy systems for supporting frequency based AS has

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been presented by Aziz et al. [12]. The authors also discussed various research challenges faced

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by the wind integrated systems for providing better frequency control AS. Attya et al. [13]

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presented a comprehensive review of WPP capabilities to provide frequency support AS and

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covered different perspectives in terms of technical challenges and future research to be carried

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out while procuring AS from RES. On the basis of the review, the authors suggested several

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supporting methods that can be a feasible solution to reduce the risk of intermittent and poor

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wind speed conditions.

180

Dong et al. [14] proposed and investigated different methods to integrate hybrid generation

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system of the wind farm and hydropower plant to provide AS when connected through a Low-

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Frequency AC (LFAC) system. These methods utilize hydropower plants at LFAC power

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systems to offer AS including power smoothing and the frequency drops mitigation on with the

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help of WPPs. Sensitivity analysis regarding the provision of primary control reserve from

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distributed solar battery systems has presented by Hollinger et al. [15]. Xavier et al. [16]

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demonstrated that power electronic based PV inverter can be used to provide AS to the main

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grid. The focus of the work was on the analysis of how these converters can perform AS to

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support the grid. These inverters with reactive power support and harmonic current

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compensation capability can improve the power system quality.

190

A novel optimization technique has been described by Al-Awami et al. in [17] for EV to

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participate in reserve markets by minimizing their contracted and real-time participation.

192

Knezevic et al. [18] evaluated the technical feasibility of a series-produced EV to provide AS

193

like congestion management, voltage support, and primary frequency regulation in real Danish

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distribution grid. Reddy et al. [19] proposed a disaggregated market clearing approach for

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procurement of energy and SR considering the uncertainties in WP generation to minimize both

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day-ahead and real-time adjustment costs.

197

Renewables like the wind in a combined energy and regulation reserve market model

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encourage the trading of RPPs and further favour grid security [20]. Banshwar et al. [21]

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proposed a market-based participation of RPPs like wind and PV to procure both energy and AS.

200

The objective of the proposed method was to obtain a feasible solution for reserve market and 6

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201

reduction in AS procurement cost while integrating RPPs in these markets. They further

202

developed a penalty based Short-Term Market (STM) for the procurement of energy and AS

203

while considering the stochastic behaviour of wind power on Social Benefit (SB) and

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Procurement Cost (PC) for obtaining the required services, viz. energy and reserve [22].

205

Integrating a high penetration of non-dispatchable RES in an electrical system is a

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challenging task because of their uncertain and intermittent nature. These schemes are being

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mainly used for the purpose of load following, surplus power absorption, peaking power and as a

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standby reserve. ESS appears to play the best solution in order to overcome the problems

209

associated with RE like wind and PV in context to their storage and high penetration to the grid

210

[23].

211

An optimal siting and sizing of energy storage as a profit-seeking entity in a joint energy and

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reserve market as a bi-level problem has been formulated by Xu et al. [24]. The formulation also

213

ensures the profitability of the investment in ES by implementing a rate of return constraint. On

214

the similar background of the Bi-level problem, Pandžić et al. [25] presented a model to optimize

215

merchant investments in ES units that can participate in the joint energy and reserve market. Bi-

216

level programming framework has been employed by the authors to maximize the profit and to

217

ensure a desired rate-of-return in the market.

218

Models for determining the optimal bidding strategy of joint operation of RES and energy

219

storage devices for the procurement of energy and AS has been proposed in [26]. Mashhour et al.

220

[27, 28] formulated and numerically examined a bidding strategy of VPP in a day-ahead joint

221

market of energy and AS by addressing a non-equilibrium model under different scenarios of

222

markets prices. A multi-stage stochastic programming model has been used to find the optimal

223

operation of a wind power plant associated battery storage system in the spot and adjustment

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markets in order to provide secondary reserve while considering uncertainties in clearing prices

225

and wind power generation [29]. Hu et al. [30] proposed an optimization model for battery

226

energy storage (BES) aggregator to optimally provide Flexible Ramping Product (FRP) in the

227

multiproduct market with the aim to maximize its monetary benefits. In addition to the revenues

228

obtained for providing energy, regulation, and FRP, this model also considers the over-offering

229

risk and the reimbursements in degradation of BESs.

230

Berrada et al. [31] focused on the economy based participation of energy storage within real-

231

time and day-ahead timelines to provide energy and regulation services. The optimization model 7

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232

determines the optimal schedule of energy quantities that should be offered by the ESS into the

233

energy and regulation market. A day-ahead scheduling strategy for the combined community

234

energy system in a joint energy and AS markets has been presented by Zhou et al. [32]. The

235

uncertainty in market prices as well as in wind and PV power has been taken into account.

236

Rodrigues et al. [33] proposed a novel two-stage stochastic model that considers different

237

degrees of risk aversion while optimizing the DA energy and spinning reserve bidding strategy

238

of a wind farm with on-site ESS. The authors have considered price uncertainties, wind

239

generation forecasts, and day-ahead profit risk while developing the two-stage model.

240 241

1.2 Contribution of the Work

242 243

The contributions of the proposed work with respect to the discussed literature survey can be summarized as follows:

244

ο‚·

As energy storage device, Pumped Storage Plants (PSPs) have the ability to make profits

245

in a competitive energy market because of its outstanding response time, ramp rate, and

246

start-up and shutdown times as compared to other generating resources [34].

247

ο‚·

These units are best suited to provide spinning reserve at relatively cheaper rate whereas

248

diesel generators are used to provide non-spinning/replacement reserve at high capacity

249

cost and have significant local pollution.

250

ο‚·

The analyzed pumped-storage system is assumed to be equipped at the same location

251

where RES is connected as well so that the surplus power available at each RES after

252

each interval will be easily absorbed by the concerned PSU.

253

ο‚·

This work evaluates the market based economic viability of Virtual Power Plant, that is,

254

hybrid ESS-RES system participating in day-ahead energy and spinning reserve market

255

as a price-maker in the SRM to increase penetration and participation of RES in such

256

markets.

257

1.3 Structure of the paper

258

Specifically, the remainder of this paper is organized as follows. Section II introduces the

259

proposed methodology and problem formulation for the procurement of energy and AS. A

260

sequential optimization approach for energy and ASM clearing is briefly introduced in this

261

section. Technical characteristics and assumptions made in the proposed approach are discussed 8

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262

in Section III. Section IV discusses the operation of VPPs to support RPPs in EM and SRM.

263

Different cases are tested to validate the proposed market-based participation of ESSs to support

264

large-scale RPPs and to increase their profitability in Section V. Finally, the conclusions are

265

presented in the final section.

266

2. PROPOSED APPROACH AND PROBLEM FORMULATION

267

In electricity markets, the retailers are liable for procuring energy on behalf of customer base

268

and can obtain it from the suppliers either through bilateral transactions or auction-based

269

mechanism. Generally, in most of the electricity markets worldwide including the US, European

270

and Indian markets [35], energy is traded through Day Ahead Markets (DAM). It operates on a

271

day-ahead timeline, where the retailers on the basis of their own load forecast submit bids into

272

the market to secure energy 24-hour ahead of the actual delivery [36]. In a similar way, SO

273

forecasts and procures some services for grid reliability on a day-ahead basis.

274

The market clearing approach has been formulated as an optimization problem where the SO

275

minimizes the procurement cost of energy and SR from the available resources.

276

2.1 Market Structure for EM & ASM

277

The market model in proposed work is considered to be sequential based optimization model.

278

The model identifies the fact that both energy and AS consume the same generating capacity. It

279

involves sequential dispatch of EM and ASM in which EM is cleared first and the results would

280

represent the starting point for the ASM [37, 38]. Simplicity and transparency in clearing

281

mechanism is an attractive feature of the sequential framework. Also, in this approach,

282

justification and explanation of schedules and prices are quite simpler. Moreover, this

283

mechanism has been similar to the mechanism that is used in many electrical markets worldwide

284

like Spain, Italy, and the Nordic pool etc. for clearing of their EM and ASM. The structure

285

related to the clearing of energy and ASM under this model is given in Appendix A.

286

2.2 Proposed approach for the participation of ESS to support RPPs in EM and SRM

287

In the vertically regulated systems, to reduce the fuel cost and emission, hydrothermal

288

coordination is used. This is carried out by letting the pumped-storage system to serve the peak

289

load by generating action and then pumping the water back into the upper reservoir during light

290

load periods [39]. 9

ACCEPTED MANUSCRIPT

291

In the proposed work, a pumped storage scheme is applied with RPPs and CPPs for the

292

procurement of energy and SR. The proposed Virtual Power Plant (VPP) is a hybrid system

293

consists of a PSU connected to a bus where RPP is connected as well. In each interval, PSU

294

absorbs the surplus capacity from WPP and/or PVP after EM and SRM clearing as shown by the

295

descriptive diagram of VPPs given in Fig. 1.

.

EPVP(max) EWPP(max)

Esurp(PVP)

Esurp(WPP) PSUWPP

.

WPP

Eavl(WPP)

PVP

297

. (b)

(a)

296

PSUPVP Eavl(PVP)

Fig. 1 Working principle of (a) VPP1 and (b) VPP2 max

max

298

If EWPP(h) and EPVP(h) respectively be the maximum capacity that the WPP and PVP offer

299

into the electricity market. If EWPP (β„Ž) and EPVP (β„Ž) be the capacities scheduled from WPP

300

and PVP respectively in EM, then after clearing of EM, the capacity available at the 𝑖 RPP for

301

participation in SRM will be -

302

EiRPP

303

For WPP: EWPP

304

For PVP: EPVP

305

If the combined schedule of 𝑖 RPP after clearing of EM and SRM in the h hour be EiRPP(h),

306

then

307

EiRPP(h) = EiRPP (h) + EiRPP

308

For WPP: EWPP(h) = EWPP (h) + EWPP

309

For PVP: EPVP(h) = EPVP (h) + EPVP

sch

sch

EM

EM

π‘‘β„Ž

Avl SRM

max

sch

(h) = EiRPP(h) β€’ EiRPP (h)

(1a)

EM

Avl

max

SRM

Avl

sch

(h) = EWPP(h) β€’ EWPP (h) max

SRM

(1b)

EM

sch

(h) = EPVP(h) β€’ EPVP (h)

(1c)

EM

π‘‘β„Ž

sch

sch

sch

EM

sch

SRM

th

(h)

(2π‘Ž)

sch

sch

EM

sch

sch

EM

sch

SRM

sch SRM

(h)

(h)

(2b) (2c)

10

ACCEPTED MANUSCRIPT

π‘‘β„Ž

310

Therefore, after clearing of EM and SRM, the surplus capacity available at the 𝑖 RPP at the end

311

of the current interval will be obtained based on Eqn. (2) and is given as -

312

EiRPP(h) = EiRPP(h) β€’ EiRPP(h)

313

For WPP: EWPP(h) = EWPP(h) β€’ EWPP(h)

314

For PVP: E PVP (h) = EPVP(h) β€’ EPVP(h)

315

The available capacity at PSUWPP and PSUPVPthat they will bid into the next interval (that is,

316

H = h + 1) in EM and SRM will be obtained from the following relation [40]:

317

EPSU

318

For PSUWPP: EPSU

319

For PSUPVP: EPSU (h + 1) = Ξ·PSU Γ— E PVP (h) = VPPPVP(H)

surp

max

sch

surp

max

surp

avl

(3a)

max

sch

(3b)

sch

(3c)

surp

max

(h + 1) = Ξ·PSU Γ— EiRPP(h) = VPPiRPP(H)

(4a)

iRPP

avl

surp

WPP

max

(h + 1) = Ξ·PSU Γ— EWPP(h) = VPPWPP(H)

(4b)

surp

(4c)

avl

max

PVP

320

where πœ‚π‘ƒπ‘†π‘ˆ is the efficiency of the pumped storage unit (typical value is about 67%).

321

Similar to other market participants like CPPs and RPPs, the VPPs with their maximum

322

capacities at concerned π‘ƒπ‘†π‘ˆπ‘…π‘ƒπ‘ƒ, that is, VPPRPP(H) will bid in the next interval H into the EM

323

and SRM. These PSUs are best suited to provide spinning reserve at relatively faster and cheaper

324

rate.

325

If the scheduled of 𝑉𝑃𝑃𝑖𝑅𝑃𝑃 in EM be VPPRPP (H) then available capacity at the VPP for

326

participation in SRM will be

327

VPPRPP

328

For WPP: VPPWPP

329

For PVP: VPPPVP

330

2.3 Problem Formulation

max

sch

EM

Avl SRM

max

sch

(H) = 𝑉𝑃𝑃iRPP(H) β€’ VPPRPP (H)

(5a)

EM

Avl

max

SRM

Avl SRM

sch

(H) = 𝑉𝑃𝑃WPP(H) β€’ VPPWPP (H) EM

max

sch

(H) = 𝑉𝑃𝑃PVP(H) β€’ VPPPVP (H) EM

11

(5b) (5c)

ACCEPTED MANUSCRIPT

331

In the proposed work, SO is considered as a single authority behind the market clearance.

332

Under the competitive market scenario, suppliers or market participants submit their bids in each

333

time interval that to be cleared in the market. Only supplier side bidding is considered, that is,

334

there is no bidding from the consumer side. Herein, for energy and SR requirement in the

335

system, SO behaves as a single buyer, which buys for all.

336

2.3.1 Bidding mechanism

337

In the deregulated model, the proposed approach considers bidding function which may differ from

338

the cost function as per the strategy of the bidder. Linear bidding function has been considered for the

339

CPPs, RPPs and the hybrid system (that is VPPs) participating in EM and ASM. These bidding

340

functions are in terms of the amount of capacity that they are willing to sell in EM and/or ASM

341

(in MW) and their prices (in $/MW).

342

If the total number of suppliers participating in the market be 𝑁𝑠, each supplier (CPP, RPP,

343

and VPPs) submits individual bid each in EM and SRM as:

344

In EM: 𝐸𝑠𝑖, 𝑃𝐸𝑠𝑖,

345

In SRM: 𝑅𝑠𝑖, 𝑃𝑅𝑠𝑖,

346

where 𝐸𝑠𝑖 and 𝑅𝑠𝑖 is the amount of energy and reserve, 𝑃𝐸𝑠𝑖 and 𝑃𝑅𝑠𝑖 the price of energy and

347

reserve offered by the 𝑖 supplier respectively in EM and SRM.

348

2.3.2 Payment mechanism

349

The payment mechanism in EM and SRM is considered to be Pay-As-Bid (PAB), then the

350

Procurement Cost of Energy (PCE) to the accepted capacity (𝐸𝑠𝑖) in EM from the selected 𝑖

351

supplier will be –

352

𝑖 = 1, 2, 3, …..,𝑁𝑠

(6)

𝑖 = 1, 2, 3, …..,𝑁𝑠

(7)

th

th

𝑃𝐢𝐸𝑠𝑖(𝐸𝑠𝑖) = 𝐸𝑠𝑖 Γ— 𝑃𝐸𝑠𝑖

(8)

353

Similarly, the Procurement Cost of Reserve (PCR) to the accepted reserve capacity 𝑅𝑠𝑖 in the

354

SRM from the selected 𝑖 supplier will be –

355 356

π‘‘β„Ž

𝑃𝐢𝑅𝑠𝑖(𝑅𝑠𝑖) = 𝑅𝑠𝑖 Γ— 𝑃𝑅𝑠𝑖

(9)

2.4 Step-by-Step Algorithm for Market Clearing 12

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357

In the proposed approach, the role of ESS to support large-scale RPP penetration in

358

sequential energy and SR market in the deregulated environment has been addressed. According

359

to the submitted bids from the suppliers (CPPs, RPPs, and VPPs), SO clears the EM with an

360

objective of PCE minimization. After clearing of EM, SRM is cleared such that the PCR is

361

minimized. These three cases are considered in order to evaluate the role of ESS to support RPPs

362

participation in EM and SRM. In the first case, the participation of CPPs alone in both EM and

363

SRM is considered; the second case considers the integration of RPPs with already existing CPPs

364

in the system whereas the participation of VPPs along with RPPs and CPPs has been considered

365

in the third case.

366 367

Market clearing mechanism is implemented through the following step-by-step algorithm. Step 1: Clear EM from available suppliers such that Ns_EM

368

Min

βˆ‘ PCE (E ) si

(10)

si

i=1

369

such that Ns_EM

370

βˆ‘E

si =

EL

(11)

i=1

371

Step 2: Calculate Available Capacity (AC) and Available Reserve Capacity (ARC)

372

corresponding to each CPP after clearing of EM, from the following relations:

373

𝐴𝐢𝑠𝑖 = 𝐸

374

𝐴𝑅𝐢𝑠𝑖 = 𝑀𝑖𝑛(𝐴𝐢𝑠𝑖, 10 Γ— 𝑅𝑅𝑖)

375

where 𝑁𝑠_𝑆𝑅𝑀 denotes the number of suppliers available in SRM and RR𝑖 ramp rate of the 𝑖

376

supplier.

377

Step 3: SO clear the SRM such that PCR from 𝐴𝑅𝐢𝑠𝑖 of all available suppliers is minimized or

378

mathematically

π‘šπ‘Žπ‘₯ 𝑠𝑖 β€’ 𝐸𝑠𝑖

𝑖 = 1,2, …. 𝑁𝑠_𝑆𝑅𝑀 𝑖 = 1,2, …. 𝑁𝑠_𝑆𝑅𝑀

(12) (13) π‘‘β„Ž

𝑁𝑠_𝑆𝑅𝑀

379

𝑀𝑖𝑛

βˆ‘ 𝑃𝐢𝑅 (𝑅 ) 𝑠𝑖

(14)

𝑠𝑖

𝑖=1

13

ACCEPTED MANUSCRIPT

380

such that 𝑁𝑠_𝑆𝑅𝑀

381

βˆ‘π‘…

𝑠𝑖 =

𝑅𝐿

(15)

𝑖=1

382

The work analyzes the characteristics of Optimal Power Flow (OPF) based formulation for

383

the procurement and pricing of energy and SR under sequential clearing environment. An OPF

384

technique has an ability to deal with power flow limits, transmission constraints, and physical

385

constraints like generation limits and ramp rate restrictions which have a significant effect on

386

CPPs responses in both EM and SRM clearing process.

387 388

The flowchart of the proposed clearing mechanism in EM and SRM (for energy and spinning reserve) is shown in Fig. 2.

14

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Start

SO determines Energy and Reserve requirements for a reliable system and opens the market for market participants

Market participants bid into the market for energy and Spinning reserve

Set hour h = 1

CPPs submit the bid into the market

RPPs submit the bid into the market

VPPs submit the bid into the market as per Eqn. (4)

Increment to next interval as H = h +1

Disaggregated market for Energy

On the basis of bids submitted by the participants in the market, SO performs optimization & determine schedule of each participant and PCE

Yes

Is RL = 0 ? No

Calculate AC of ith CPP using Eqn. (12)

Calculate AC of ith RPP using Eqn. (1)

Calculate AC of ith VPP using Eqn. (5)

Calculate ARC of ith CPP using Eqn. (13)

Calculate surplus capacity at ith RPP as per Eqn. (3)

Disaggregated market for Spinning Reserve On the basis of bids submitted in SRM SO performs optimization & determine schedule of each participant and PCR

Is Reliability met th for h hour ?

No

Calculate combined schedule th of i RPP after EM & SRM clearing as per Eqn. (2)

SO sends signal to participants to adjust their Bids

Yes Increment the interval as h+1

No

Is H > 24 ? Yes

Final Schedule for EM & SRM for 24 hours

Payment to the participants

389 390

Fig. 2 Flowchart of the proposed approach for incorporating VPPs in EM & SRM clearing

391

Optimization of objective functions with constraints along with generation and demand

392

bidding constraints as considered in the work has been done by modifying the Matpower

393

program. Matpower includes a primal-dual interior point solver called MIPS, for Matlab Interior

15

ACCEPTED MANUSCRIPT

394

Point Solver [41]. Interior point method has a unique characteristic of solving linear as well as

395

nonlinear OPF problem with both nonlinear objective function and nonlinear constraints.

396

The objective function in Eq. (10) and (14) has to be minimized subject to the following

397

system constraints:

398

A. The power flow equation of the power network

399 400

401

402 403

𝑔(𝑉,πœ™) = 0 where

𝑔(𝑉,πœ™) =

ο‚·

408 409 410 411

For each PQ bus For each PV bus π‘š, not including the reference bus

The inequality constraint on real power generation (𝑃𝑔𝑖) at PV buses min max gi ≀ Pgi ≀ P gi

P ο‚·

(17)

The inequality constraint on reactive power generation (𝑄𝑔𝑖) at PV buses

406 407

{

𝑛𝑒𝑑 𝑖 𝑛𝑒𝑑 𝑄𝑖(𝑉,πœ™) β€’ 𝑄 𝑖 𝑛𝑒𝑑 π‘ƒπ‘š(𝑉,πœ™) β€’ 𝑃 π‘š

𝑃𝑖(𝑉,πœ™) β€’ 𝑃

B. Inequality constraints on real and reactive power generation:

404 405

(16)

Q

min max gi ≀ Qgi ≀ Q gi

(18)

C. The inequality constraint on phase voltage (𝑉) at each PQ bus: min max i ≀ Vi ≀ V i

V

(19)

D. The branch flows are limited by MVA flow limit constraints: MVAfij ≀ MVAf

max ij

(20)

3. TECHNICAL CHARACTERISTICS AND ASSUMPTIONS

412

To verify the effectiveness of the proposed approach, an IEEE-30 bus test system is modified

413

where various types of generation technologies are used to evaluate the contribution of ESS to

414

support RE penetration in energy and SR market.

415

3.1 Test System characteristics

416

The single line diagram of a modified IEEE-30 bus test system is shown in Fig. 3. The test

417

system consists of 6 CPPs which are located at the buses 1, 2, 13, 22, 23 and 27; among the

418

RPPs, WPP and PVP are considered as one of the most recognized sources of electricity

419

generation worldwide and are considered to be located respectively at buses 4 and 29. The 16

ACCEPTED MANUSCRIPT

420

modified system has 2 PSUs, one each for WPP and PVP and is located on the same buses 4 and

421

29 respectively. The line data and associated capacities considered for the simulation studies are

422

given in Appendix B. PVP 29

28

27 PSUPVP

VPP2 CPP6 26

30

25

23

24 E5 CPP5

18

15

19

20

17 14

21 RL

16

22

13

10

12 11 CPP3

E4

9

CPP4

VPP1 WPP

1

3

E1

4 E3

8

6 PSUWPP 7

CPP1 5

2 E2

CPP2

423 424

Fig. 3 Single Line Diagram of Modified IEEE-30 Bus Test System with VPPs (hRPP – PSU System)

425

For the procurement of energy from EM, the modified system has five loads 𝐸1, 𝐸2, 𝐸3, 𝐸4,

426

and 𝐸5 that are connected respectively at buses 1, 2, 3, 10, and 23. These energy loads 𝐸1, 𝐸2, 𝐸3

427

, 𝐸4, and 𝐸5 shares respectively 10%, 25%, 25%, 20%, and 20% of the complete energy demand

428

such that

429

𝐸𝐿 = 𝐸1 + 𝐸2 + 𝐸3 + 𝐸4 + 𝐸5

(21)

17

ACCEPTED MANUSCRIPT

430

To heighten the technical feasibility of the electricity market, suppliers must declare their

431

technical characteristics in terms of unit’s maximum capacity and associated Ramp Rates (RR).

432

Technical characteristics of CPPs, RPPs, and PSUs as listed in Table 1 includes energy and

433

reserve bidding blocks, unit’s maximum capacities and associated RRs.

434

Table 1: Technical Characteristics of Generation System S. No. 1 2 3 4 5 6 7 8 9 10

Bus

GENCO

1 2 4 4 13 22 23 27 29 29

CPP1 CPP2 WPP PSUWPP

Energy Offer ($/MWh) 40 35 50 50 45 70 56 86 66 66

CPP3 CPP4 CPP5 CPP6 PV PSUPVP

Reserve Offer ($/MW) 40 42 42.5 42.5 54 84 67 103 56 56

Ramp Rate (RR) 5 6 --3 3 4 8 ---

Maximum Capacity 260 300 Varying Hourly Varying Hourly 20 100 170 150 Varying Hourly Varying Hourly

435 436

Practical prices for RPPs are considered in order to enhance the practicability of the electrical

437

system and represent the actual cost of energy production from different suppliers in Asian

438

countries [21].

439

3.2 Energy and SR demand profile

440

In case of an electrical system, the total energy demand on the electrical system will

441

generally be higher during the day and in the early evening and lower during the late evening and

442

in the early morning when most of the population is asleep as shown in Fig. 4 whereas Fig. 5

443

shows a typical RPP status for the complete day and are adapted from [21].

1000

Energy Demand Spinning Reserve Demand

900 800

Capacity (MW)

700 600 500 400 300 200 100 0

444

0

2

4

6

8

10

12

Hour

18

14

16

18

20

22

24

ACCEPTED MANUSCRIPT

445 446

Fig. 4 Hourly Energy and Spinning Reserve Demand

The modified system has a single load for SR requirement, that is, 𝑅𝐿 located at bus 10. WPP Availability PVP Availability 80 70

Power Available (MW)

60 50 40 30 20 10 0 0

2

4

6

8

10

12

14

16

18

20

22

24

Hour

447 448

Fig. 5 Hourly RPPs availability status for the complete timeframe

449

3.3 Assumptions

450

These are the following assumptions which are considered in the proposed approach:

451

1. The reserve requirement is to be either equal to the size of the largest generating unit or

452

5-10% of peak load in the system [42]. In the present work, the variable reserve

453

requirement is considered, that is, about 10% of the hourly energy requirement as shown

454

in Fig. 4.

455 456

2. Market participants (suppliers or GENCOs) do not provide transmission losses payment. Hence, these payments in the pool are assumed to be supplied by the SO itself.

457

3. In SRM, except CPP1, all other CPPs increase their bid price as compared to EM in order

458

to earn higher profit whereas the RPPs reduce their bid price to remain in the market.

459

4. Each VPP comprises of RPP and PSU which are located on the same location so that the

460

excess of RE available after clearing EM and SRM can be easily absorbed by the

461

concerned PSU.

462 463

4. OPERATION

OF

VIRTUAL

POWER

PLANTS

TO

SUPPORT

RPP

464

PARTICIPATION IN EM AND SRM

465

Devising a good bidding strategy in EM and SRM is very important for market participants

466

to maximize their participation and in turn profit. The functioning of the hybrid system of ESS 19

ACCEPTED MANUSCRIPT

467

and RPPs for the procurement of required services in energy and SR market is discussed in this

468

section. Case 1 and Case 2, respectively, describe the market-based participation of VPP1

469

(hybrid WPP-PSU system) and VPP2 (hybrid PVP-PSU system) in EM and SRM.

470

4.1 Case 1: Market-based participation of VPP1 (hybrid WPP-PSU system) in EM and SRM

471

The location of VPP2 is shown in single line diagram as given in Fig. 3 in which a PSU is

472

connected at the bus 4 where PVP already exists. After clearing of EM and SRM, this PSU will

473

absorb the surplus power from this WPP only. VPP1 will participate in both the markets and it is

474

assumed that in VPP1 (or hybrid WPP-PSU), both WPP and π‘ƒπ‘†π‘ˆπ‘Šπ‘ƒπ‘ƒ bid with the same price

475

stack separately in the EM and SRM as given in Table 1. The participation of VPP1, that is, the

476

combined operation of WPP and PSU in energy and SR market is shown by pictorial

477

representation in Fig. 6.

Wind Availability

Reserve

Energy 80

80

60

60

75

70

65

60

2

4

6

8

10

12

14

16

18

20

22

20

40

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

Hour

Hour

30

20

20

10

10

0

0

-10

-10 6

8

10

12

14

Hour

16

18

20

22

24

20

10

0

80 Power Available (MW)

30

30 Power Scheduled (MW)

40

30 Power Scheduled (MW)

50

40

4

100

PSU(WPP) Offer PSU(WPP) - Available Power (MW)

WPP - Surplus Power (MW)

60

50

2

PSU(WPP)_Reserve

70

WPP - Surplus Power (MW) PSU(WPP) - Available Power (MW)

0

(b)

40

PSU(WPP)_Energy

60

20

0

(a)

70

40

24

Hours

478

480

40

0 0

479

Power Scheduled (MW)

Power Scheduled (MW)

Power Available (MW)

80

20

10

60

40

20

0

0

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

Hour

Hour

0

2

4

6

8

10

(e)

(c)

Fig. 6. Hybrid WPP – PSU operation in EM and SRM clearing

20

12

Hour

(d)

14

16

18

20

22

24

ACCEPTED MANUSCRIPT

481

Along with other participants, the WPP bids into the EM and SRM with their hourly

482

availability as shown in Fig. 6(a). Fig. 6(b) shows the schedule of WPP both in EM and SRM. It

483

is seen that during hour 1, WPP has an available capacity of 73.08 MW, out of which capacity of

484

0 MW and 6.38 MW is scheduled in EM and SRM respectively. After clearing of EM and SRM,

485

WPP has 66.7 MW as the surplus capacity during the concerned period as shown in Fig. 6(c). In

486

order to exploit this surplus capacity in EM and SRM, PSU stores this surplus capacity by its

487

pumping mode of operation. According to Eqn. (4), π‘ƒπ‘†π‘ˆWPP offers 44.46 MW of capacity that is

488

two-third of the surplus power, in the EM along with other available resources for the next hour

489

2 as shown in Fig. 6(d).

490

In EM, it is seen from Fig. 6(e) that in none of the period, offer from π‘ƒπ‘†π‘ˆWPP is selected.

491

This is because of the other cheaper resources are participating in the market to fulfill energy

492

requirement. After clearing of EM, SRM is cleared from the complete π‘ƒπ‘†π‘ˆWPP offer and other

493

available resources according to step number 3 of a step-by-step algorithm such that PCR is

494

minimized. During hours 6 – 10, the offer from π‘ƒπ‘†π‘ˆWP is selected to schedule their capacity for

495

providing SR in SRM. It is seen that at the end of the day VPP1 has 35.48 MW of capacity

496

available in its PSU that it will offer in the market for the first hour of the next day.

497

4.2 Case 2: Market-based participation of VPP2 (hybrid PVP-PSU system) in EM and SRM

498

The location of VPP2 is shown in single line diagram given in Fig. 3 in which a PSU is

499

connected at the bus 24 where PVP already exists. After clearing of EM and SRM, this PSU will

500

absorb the surplus capacity from this PVP only. Similar to VPP1, the participation of VPP2 (or

501

hybrid PVP-PSU) is allowed in both the markets. As per the Table 1, the PSU offer at the same

502

price as that of PVP in EM and SRM. Likewise VPP1, the participation of VPP2, that is, an

503

operation of hybrid PV-PSU in energy and SRM is shown in Fig. 7.

504

Along with other participants, the PVP bids into the EM and SRM with their hourly

505

availability shown in Fig. 7(a). It is seen that there is no availability of power from PVP up to the

506

hour 7. Fig. 7(b) shows the schedule of PVP in both EM and SRM. In hour 8, PVP has offered a

507

capacity of 3.8 MW to the market, out of which no power has been scheduled from PVP in EM

508

and SRM. Hence, after clearing of EM and SRM from all available resources, PVP has a surplus

509

capacity of 3.8 MW in the hour 8 as shown in Fig. 7(c). 21

ACCEPTED MANUSCRIPT

40

30

20

10

30

20

10

0

0 0

2

4

6

8

10

12

14

16

18

20

22

24

30

20

10

0 0 2 4 6 8 10 12 14 16 18 20 22 24

Hours

Hour

(b)

15 10 5

20 15 10

511

5 0 2

4

6

8

10

12

14

16

18

20

22

24

Hour

PSU(PVP) Offer

80

60 50 40 30 20

0 -10

-5

Hour

10

5

10

5

0 2 4 6 8 10 12 14 16 18 20 22 24

10

70

0

-5

15

(c)

25

0

15

Hour

Power Available (MW)

30

Scheduled Power (MW)

Scheduled Power (MW)

30

20

20

0

PSU(PVP)_Reserve 35

25

25

20

0

40

PSU(PVP)_Energy 35

30

PVP Surplus Power (MW) PSU(PVP) Available Power (MW)

25

0 2 4 6 8 10 12 14 16 18 20 22 24

(a)

40

512

PVP Surplus Power (MW)

30

Scheduled Power (MW)

Scheduled Power (MW)

40 Power Available (MW)

40

PV Availability

50

510

Reserve 50

PSU(PVP) Available Power (MW)

Energy 50

0 2 4 6 8 10 12 14 16 18 20 22 24

0

2

4

6

8

Hour

(e)

10

12

Hour

14

16

18

20

22

24

(d)

Fig. 7. Hybrid PVP – PSU operation in EM and SRM clearing

513

In order to utilize the surplus capacity in EM and SRM, PSU stores this capacity by pumping

514

mode of operation. According to Eqn. (4) and Fig. 7(d), π‘ƒπ‘†π‘ˆPVP now offers in EM with the

515

capacity of 2.53 MW along with other available resources in the next hour 9. In EM, it is seen

516

from the Fig. 7(e) that in none of the period, offer from π‘ƒπ‘†π‘ˆPVP is selected. After clearing of EM,

517

SRM is cleared with the complete capacity of π‘ƒπ‘†π‘ˆPVP and other available resources. During

518

hours 11 – 12 and 19 – 21, the offer from π‘ƒπ‘†π‘ˆPVP is selected in SRM to schedule their capacity

519

to provide the spinning reserve.

520

5. EVALUATING THE CONTRIBUTION OF VPPS IN EM AND SRM

521

As discussed in section 2, three cases are considered in order to evaluate the role of ESS in

522

EM and SRM clearing to increase the penetration of RPPs in such markets.

523

5.1 Energy Market (EM)

22

ACCEPTED MANUSCRIPT

524

In this case, as per the proposed approach, energy requirement from the available resources

525

are dispatched first in EM such that total PCE is minimized. The schedule of each CPP in all

526

three cases considered is shown in Fig. 8. CPP1

CPP2

300

300

wo RPP

w hRPP-PSU

w RPP

w RPP

wo RPP

100

200

100

320

Scheduled Power (MW)

100

200

Scheduled Power (MW)

200

Scheduled Power (MW)

Scheduled Power (MW)

Scheduled Power (MW)

320

300

280

0

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

Hour

527

320

300

280

300

280

0

0 0 2 4 6 8 10 12 14 16 18 20 22 24

w hRPP-PSU

Scheduled Power (MW)

300

Hour

Hour

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

Hour

Hour

Hour

CPP3 22

wo RPP

22

w RPP

CPP4

w hRPP-PSU

20

20

18

18

18

20

20

20

16

16

16

18

18

18

14

16

16

8 6

10 8 6

12 10 8 6

4

4

4

2

2

2

0

0

-2

-2

528

14 12 10 8 6

w RPP

22

14 12 10 8 6

14 12 10 8 6 4

2

2

2

0

0

0

0

-2

-2

-2

-2

0 2 4 6 8 10 1214 16 18 2022 24

0 2 4 6 8 10 1214 16 18 2022 24

Hour

Hour

Hour

w hRPP-PSU

16

4

0 2 4 6 8 10 1214 16 18 2022 24

4

22

Scheduled Power (MW)

10

12

wo RPP

Scheduled Power (MW)

12

14

22

Scheduled Power (MW)

14

Scheduled Power (MW)

20

Scheduled Power (MW)

Scheduled Power (MW)

22

0 2 4 6 8 10 1214 16 18 2022 24

0 2 4 6 8 10 1214 16 18 2022 24

0 2 4 6 8 10 1214 16 18 2022 24

Hours

Hours

Hours

CPP5

50

0

529 530

CPP6 200

w hRPP-PSU

150

100

50

0

wo RPP

50

0

200

w RPP

150

150

100

200

100

50

100

50

0

0

w hRPP-PSU

150

Scheduled Power (MW)

100

200

Scheduled Power (MW)

150

Scheduled Power (MW)

Scheduled Power (MW)

150

w RPP

Scheduled Power (MW)

wo RPP

200

Scheduled Power (MW)

200

100

50

0

0 2 4 6 8 1012141618202224

0 2 4 6 8 1012141618202224

0 2 4 6 8 1012141618202224

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

Hours

Hours

Hours

Hour

Hour

Hour

Fig. 8 Schedule of various CPPs in EM in 3 cases considered 23

ACCEPTED MANUSCRIPT

531

5.1.1 Case 1: Considering only CPPs participation in EM clearing

532

In this case, it is assumed that only CPPs exchange their capacities in EM whereas the

533

participation of RPPs and VPPs are neglected. The schedule of each supplier, in this case, is

534

represented by square bullet line indicating without RPPs (wo RPP) in Fig. 8. The selection of

535

each supplier in EM is according to the supplier’s bidding, energy requirement in the market and

536

the network constraints. The cheaper and the feasible is the energy bid, the chances of their

537

selection in the EM becomes more.

538

The supplier CPP2 with the most economical bid in the EM is cleared first and is scheduled

539

to provide its complete capacity throughout the complete duration. Since all its capacity is

540

scheduled in the EM hence it doesn’t have any capacity to be dispatched under SRM. In a similar

541

manner, in any period of time, the supplier CPP6 is not selected during the dispatching process

542

because of its expensive bid in the EM. Hence it will participate in the RM with its complete

543

capacity. After CPP6, CPP4 is the most costly supplier, from the figure it is observed that this

544

supplier will provide its capacity only in one period, that is, in hour 12. In a similar manner, the

545

other suppliers participating in EM are dispatched. The total procurement cost of energy for

546

dispatching the total energy requirement of 13.55 GW from EM, in this case, comes to about

547

$553148 for the complete timeframe.

548

5.1.2 Case 2: Considering both CPPs and RPPs participation in EM clearing

549

In this case, it is assumed that both CPPs and RPPs are participating in EM whereas the

550

participation of VPPs is neglected. Similar to case 1, the feasible suppliers are selected as per

551

energy requirement and the system constraints. During the selection process, the RPPs (WPP

552

and/or PV) replace their capacity with some of the CPPs in the EM. This is because of the

553

cheaper bids of RPPs in the EM compared to some of the CPPs.

554

Herein, the schedule of CPP1 and CPP2 being the same as that in Case 1 because of their

555

economical bids in the EM than that of RPPs. After dispatching energy from these suppliers,

556

WPP is selected to schedule their capacity to fulfil the rest of the energy requirement in EM.

557

Since this RPP is cheaper than CPP4 and CPP5 hence the capacity of WPP is selected before the

558

selection of these CPPs. Therefore, the combined effect of integrating RPPs (WPP and/or PVP)

559

in the EM where CPPs have already existed is that none of the energy from the CPP4 in any

560

period and lesser energy from CPP5 (in hours 9-14 and 20-21) is selected to be scheduled in EM 24

ACCEPTED MANUSCRIPT

561

as RPPs replaces most of the costlier suppliers as shown by black circled bullet line indicating

562

with RPPs (w-RPP) in Fig. 8. Similar to Case 1, the supplier CPP6 will participate in the RM

563

with its complete capacity because it is not selected in EM throughout the complete duration.

564

Fig. 9 shows the schedule of WPP and PVP in EM clearing over the time period of complete one

565

day.

60

80

Scheduled Power (MW)

Scheduled Power (MW)

PVP

WPP

80

40

20

0

566 567 568

60

40

20

0

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

Hour

Hour

Fig. 9 RPPs schedule in EM clearing in Case 2 The integration of RPPs in EM results in the reduction in PCE, it comes to about $2749

569

lesser than the case when only CPPs are allowed to participate in EM.

570

5.1.3 Case 3: Considering hybrid RPPs-PSU, RPPs and CPPs participation in EM clearing

571

In this case, it is assumed that all the resources, that is, CPPs, RPPs, and VPPs are allowed to

572

participate in EM to provide their capacity. It is proposed that the PSUs are connected at the

573

same bus where the RPPs are connected as well. So the surplus capacity available at the RPPs

574

will be easily absorbed by the involved PSU after EM and SRM clearing. There are two PSUs (

575

π‘ƒπ‘†π‘ˆπ‘Šπ‘ƒπ‘ƒ and π‘ƒπ‘†π‘ˆπ‘ƒπ‘‰π‘ƒ), one each for absorbing surplus power from WPP and PVP. However,

576

because of the comparatively faster ramp rate, PSUs can reduce the number of start-ups and shut-

577

downs for other CPPs in the system. Since the efficiency of PSU is considered to be 67%, hence

578

it can generate two-thirds of the surplus power available at different RPPs. In addition to this, the

579

PSU will bid into the market with the same price as that by the concern RPP, so that it can be

25

ACCEPTED MANUSCRIPT

580

easily selected in the market. The schedule of each CPP is represented by circled bullet line

581

indicating with hybrid RPP-PSU system (w hRPP-PSU) in Fig. 8.

582

The schedule of CPPs remains the same as that was in case 2 when the proposed approach of

583

integrating PSUs in EM is applied. Hence neither of the bids from the (π‘ƒπ‘†π‘ˆWPP or π‘ƒπ‘†π‘ˆPVP) is

584

selected in any timeframe to provide energy in EM. This is because no capacity is scheduled to

585

be dispatched from the PSUs after procuring energy from CPPs and RPPs in EM. Therefore, the

586

total PCE, in this case, is the same as that was in the previous case. Hence the integration of PSU

587

in EM provides no extra benefit to the SO.

588

5.2 Spinning Reserve Market (SRM)

589

After clearing of EM, AC and ARC at each supplier are calculated after scheduling their

590

capacity in the EM for the concerned period. SO clears SRM from ARC in each hour according

591

to Eqn. (2) and (3) such that PCR is minimized. The selection process of suppliers in SRM is

592

same as that in EM with the exception that here the SR is cleared from ARC in place of the

593

maximum capacity of the supplier as that was in EM. The schedule of each CPP in all three cases

594

considered is shown in Fig. 10.

60

w RPP

wo RPP

CPP2

CPP1

60

200

w hRPP-PSU

200

wo RPP

0

0

20

Scheduled Power (MW)

20

40

Scheduled Power (MW)

Scheduled Power (MW)

Scheduled Power (MW)

Scheduled Power (MW)

20

40

100

50

0

150

100

50

0

0

595

w hRPP-PSU

w RPP

150

150 40

200

Scheduled Power (MW)

60

100

50

0

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

Hour

Hour

Hour

Hour

Hour

Hour

26

ACCEPTED MANUSCRIPT

CPP4

CPP3 18

18

16

16

16

14

14

12 10 8 6 4

Scheduled Power (MW)

18

12 10 8 6

12 10 8 6 4

2

2

2

0

0

0

-2

596

-2

w hRPP-PSU

14

4

32

-2

wo RPP

32

32

w RPP

30

30

30

28

28

28

26

26

26

24

24

24

22

22

22

20 18 16 14 12 10 8 6

Scheduled Power (MW)

20

Scheduled Power (MW)

w RPP

20

Scheduled Power (MW)

wo RPP

Scheduled Power (MW)

Scheduled Power (MW)

20

20 18 16 14 12 10 8 6

4

4

2

2

w hRPP-PSU

20 18 16 14 12 10 8 6 4 2

0

0

0

-2

-2

-2

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 12 14 16 18 20 22 24

0 2 4 6 8 10 1214 16 18 2022 24

0 2 4 6 8 10 1214 16 18 2022 24

0 2 4 6 8 10 1214 16 18 2022 24

Hour

Hour

Hour

Hour

Hour

Hour

CPP6

CPP5 w RPP

wo RPP

w hRPP-PSU

w RPP

60

Scheduled Power (MW)

20

0

0

Scheduled Power (MW)

Scheduled Power (MW)

Scheduled Power (MW)

20

20

40

20

598 599

40

20

40

20

0

0

597

60

40

Scheduled Power (MW)

40

40

w hRPP-PSU

60

Scheduled Power (MW)

wo RPP

0

0

0 2 4 6 8 10 1214 16 18 2022 24

0 2 4 6 8 10 1214 16 18 2022 24

0 2 4 6 8 10 1214 16 18 2022 24

0 2 4 6 8 10 1214 16 18 2022 24

0 2 4 6 8 10 1214 16 18 2022 24

0 2 4 6 8 10 1214 16 18 2022 24

Hours

Hours

Hours

Hour

Hour

Hour

Fig. 10 Schedule of various CPPs in SRM in 3 cases considered 5.2.1 Case 1: Considering only CPPs participation in SRM clearing

600

In this case, it is assumed that only CPPs participate in SRM to provide SR whereas the

601

participation of RPPs and VPPs are restricted. To meet the reserve requirement, the generating

602

schedule for each CPP over the time horizon of the complete timeframe of one day is shown in

603

Fig. 10 and represented by square bullet line indicating without RPPs (wo RPP).

604

Being the most economical supplier in the EM, CPP2 isn’t able to provide any capacity under

605

SRM throughout the complete duration since its complete capacity is already scheduled in EM.

606

Hence, the optimization process will search for the next feasible supplier. After CPP2, CPP1 is

607

the next economic and feasible supplier in the SRM, hence CPP1 will fulfil the reserve

608

requirement in those periods when CPP1 has ARC. CPP1 has no ARC in SRM for periods 7-15,

609

and 19-21. During these periods, the process will search for the next feasible options. This 27

ACCEPTED MANUSCRIPT

610

process of selecting feasible options continues between different available suppliers until

611

complete SR requirement is dispatched.

612

The supplier CPP6 is selected in SRM in most of the period in spite of their expensive

613

reserve bid because it has more ARC as compared to other suppliers throughout the complete

614

time frame. All other suppliers participating in the SRM are selected based on their bids and

615

feasibility of the system while considering various network constraints. The total PCR for

616

dispatching total SR requirement of 1355 MW in SRM comes to about $121351.

617

5.2.2 Case 2: Considering both RPPs and CPPs participation in SRM clearing

618

In this case, it is assumed that RPPs are also participating in SRM along with CPPs to

619

provide a reserve in SRM whereas the participation of VPPs is restricted. After EM clearing, the

620

AC and ARC at different CPPs in SRM are calculated according to step 2 of the step-by-step

621

algorithm. This ARC of CPPs depends upon the ramp rate of the unit. Therefore, higher the RR

622

more the ARC will be available at the CPPs participating in the SRM. Hence, RR limits the

623

participation of CPPs in SRM.

624

In such a scenario, the RPPs plays a vital role in providing ARC in SRM as they are

625

independent of the ramping constraint. After EM clearing, the surplus capacities available at

626

different RPPs will now act as ARC in SRM. The CPPs schedule, in this case, is shown by black

627

circle bullet line in Fig. 10. It is seen from the figure that after integrating RPPs in the SRM,

628

more capacity is scheduled from the RPPs than from CPPs. This leads to the reduction of PCR

629

for obtaining the required SR. It is also observed that after integrating RPPs into the EM and

630

SRM, there is a reduction in the capacities scheduled by all the CPPs mainly CPP2, CPP3, CPP4

631

and CPP6 in SRM as RPPs replaces their capacities with the CPPs in the SRM during the

632

dispatching process when compared with Case 1. This phenomenon is two-fold – firstly, RPPs

633

participation in the SRM is not limited by the ramping constraints, hence the complete capacity

634

of the RPPs after dispatching in the EM will be available in the SRM. Secondly, the bids offered

635

by RPPs in SRM are less costly than some of the CPPs participating in the market to provide SR.

636

Fig. 11 shows the schedule of RPPs (WPP and PVP) in SRM clearing over the time period of

637

complete one day.

28

ACCEPTED MANUSCRIPT

PVP

WPP 80

Scheduled Power (MW)

Scheduled Power (MW)

80

60

40

20

0

40

20

0

0 2 4

6 8 10 12 14 16 18 20 22 24

638

Hour

0 2 4

6 8 10 12 14 16 18 20 22 24

Hour

Fig. 11 RPPs schedule in SRM clearing in Case 2

639 640

60

When RPPs are allowed to participate in the SRM, the PCR is reduced to $88600, which is

641

about 73% of the PCR in Case 1.

642

5.2.3 Case 3: Considering hybrid RPPs-PSU, RPPs and CPPs participation in SRM clearing

643

In this case, the participation of all the suppliers, that is, CPPs, RPPs, and VPPs are allowed

644

in SRM to exchange their capacity. It is seen in most of the periods that after dispatching the

645

capacities of the RPPs in EM and SRM, still surplus capacity is available at the RPPs. After

646

clearing of EM and SRM, this surplus capacity available at each RPP will be stored by the PSU

647

in the particular hour. PSU with this stored capacity will bid in the next hour in both EM and

648

SRM similar to RPPs and CPPs. Hence the surplus capacity available at each RPPs can be

649

utilized in order to increase the RPPs participation and profit maximization with the support of

650

PSUs.

651

The schedule of each CPP, in this case, is represented by circle bullet line indicating market

652

clearing with hybrid RPP-PSU system (w hRPP-PSU) in Fig. 10. It has been observed that after

653

integrating the hybrid system of RPPs and PSU in the EM and SRM, lesser capacities are

654

scheduled from CPP4 and CPP5. This is due to the fact that hybrid VPP scheme being economic

655

and its fast response properties are more competitive in SRM. Hence, the capacities of CPPs can

656

be replaced to further lower generation levels both in EM and SRM. Since, the capacity of the

657

hybrid scheme replaces the capacities of costlier CPPs in the EM, making these suppliers

658

available in the SRM. Because of their lower bids of PSUs (π‘ƒπ‘†π‘ˆWPP or π‘ƒπ‘†π‘ˆPVP) compared to 29

ACCEPTED MANUSCRIPT

659

other participants in the SRM, the surplus capacity of RPP stored in PSUs will replace their

660

capacities various CPPs that was scheduled in the previous cases. Hence, results in the reduction

661

of PCR.

662

The schedule of each PSU (π‘ƒπ‘†π‘ˆWPP and π‘ƒπ‘†π‘ˆPVP ) is given in Fig. 12. From this figure it is

663

observed that there are some periods where the offers from π‘ƒπ‘†π‘ˆWPP (in hours 6-10) and π‘ƒπ‘†π‘ˆPVP

664

(in hours 11-12 and 19-21) are selected to provide their capacity in SRM.

35

PSU (WPP)

PSU (PVP)

35

30 30

Power Scheduled (MW)

Power Scheduled (MW)

25 20 15 10 5 0

25 20 15 10 5 0

-5

-5 0

2

4

6

8 10 12 14 16 18 20 22 24

Hour

665

0

2

4

6

8 10 12 14 16 18 20 22 24

Hour

Fig. 12 PSUs schedule in SRM clearing in Case 3

666 667

The integration of the hybrid system into the SRM further reduces the total PCR when

668

compared to Case 2. Additional 2395$/day has been saved by employing the proposed approach

669

of using energy storage scheme with RPPs.

670

5.3 Comparison of proposed model with previous work available in literature

671

On the basis of refereed literature, the comparison can be made in respect to the

672

methodologies used, and objective function considered in their simulation work and is listed in

673

Table 2.

674

Table 2: Methodology comparison of other work available in literature with the proposed work Reference

Methodology used

Objective Function

[24]

Bi-level formulation

Minimization of system cost by siting & Sizing of Energy storage for joint energy and RM

30

Whether the market based approach considered or not No (expected system operating cost and ES

Remark/Gap Combined Procurement cost minimization is not considered

ACCEPTED MANUSCRIPT

investment cost is considered) No

[26]

General Algebraic Modeling System (GAMS)/CPLEX.

To determine the optimal bidding strategy of WP, PV, PSP and ES devices in energy and RM

[29]

Multi-stage stochastic programming model

No (Recovery of capital cost investment in BESS is considered)

[27, 28]

A non-equilibrium model based on the deterministic Price-Based Unit Commitment Robust MILP model

To find the optimal operation of a wind power plant associated battery storage system through VPP participation in the spot and adjustment markets To check and validate the effectiveness of bidding strategy for the participation of VPPs in Energy and SRM

Yes

Integration of RES in energy and AS market is absent

Day-ahead scheduling strategy for the Integrated Community Energy Systems (ICES) and combined cooling, heating, and power (CCHP) systems in the joint EM and ASM Procurement of energy and AS using Virtual Power Plant (VPP) in a deregulated environment

Yes, (but only for scheduling of ICES in energy and ASM)

ESS system is not considered so that the surplus capacity of each area can be stored and utilized through ES mechanism ο‚· Total procurement cost minimization. ο‚· Profit maximization of RES and procurement cost minimization through ESS based VPPs.

[32]

Proposed Method

Primal-dual interiorpoint solver for optimal power flow technique

Market-based participation of ESS to support large-scale RE penetration in electricity markets

The market-based approach is not considered by individual participants Minimization of procurement cost of obtaining energy is not considered

675 676

From Table 2, it is observed that a market-based approach for the participation of ESS in energy and AS

677

markets is absent in the literature. The proposed approach can provide a better market based platform to

678

the ESS so that they can participate in such markets in order to maximize their own profit and also to

679

increase participation and penetration of RES in these markets.

680

6

Conclusion & Discussion

681

The combined operation of renewables and energy storage schemes is one of the important

682

ways to achieve supply-demand balance in real time and to improve energy sustainability. In this

683

paper, a market-based strategy for the participation of hybrid operation of renewable power

684

producers and energy storage scheme for the procurement of energy and spinning reserve in a

685

deregulated environment is presented. The proposed strategy takes into account the participation

686

of various resources like conventional power plants and renewable power plants in both the 31

ACCEPTED MANUSCRIPT

687

energy and reserve markets. An optimal power flow method is used to formulate an optimization

688

problem which has an ability to deal with physical constraints like generating limits and ramping

689

restrictions that have a significant effect on conventional power producers’ schedules in both the

690

markets.

691

The proposed strategy is tested on the modified IEEE-30 bus test system under different

692

market conditions. For the procurement of energy (13.53GW/day) and SR (1.355GW/day)

693

respectively from EM and SRM, SO pays $553148 and $ 121351 to the market participants when

694

CPPs alone are participating in the markets. It is seen that when RPPs are allowed to participate

695

in the markets along with CPPs, the PCE and PCR reduces to $550399 and $88600 for obtaining

696

the same quantity of energy and SR. With the participation of VPPs, that is, hybrid operation of

697

RPPs and PSUs, along with CPPs and RPPs, the PCE appears to remain the same as in the

698

previous case but additionally $2395/day can be saved in SRM for the procurement of SR.

699

Obtained results show that by using hybrid operation of renewable power producer and energy

700

storage scheme, not only the penetration of renewable power producer in SRM is increased, but

701

also procurement of SR is reduced. The results of the proposed model demonstrate that higher

702

potential revenues could be generated when VPPs are participating in the SR market.

703

However, because of the faster ramp rate, the hybrid scheme is more competitive in SRM

704

that can reduce the burden on conventional power producers to generate the lesser capacity to

705

provide the reserve. It has been observed that a number of solutions have resulted based on the

706

combined operation of renewables and ESS, providing decision-makers, the flexibility to select

707

the appropriate solution based on the different situations.

708

Acknowledgement

709

The authors wish to thanks anonymous referees who reviewed this paper and gave their valuable

710

comments and helpful suggestions. Moreover, the first author would also like to thank his family

711

for their continuous support and belief during difficult times.

712

Appendix A

713

The sequential framework for energy and ancillary services market clearing is given in Fig. 13.

32

ACCEPTED MANUSCRIPT

Stage 01

Stage 02

Energy Market

Ancillary Services Market

MW

System Operator

MW

$

Power Flow

$

MW

Money Flow

S1

. .

Sx

. .

Virtual Power Plant (VPP)

Sn

VPPs : (MW, $/MW)

Suppliers : (MW, $/MW)

714

Fig. 13. Sequential framework for energy and ancillary services market

715 716

Appendix B

717

The line data and associated capacities considered for the simulation studies are given in Table 3.

718

Table 3: Line Data and Corresponding Capacities From bus

To bus

r

x

b

1 1 2 3 2 2 4 5 6 6 6 6 9 9 4 12 12 12 12 14

2 3 4 4 5 6 6 7 7 8 9 10 11 10 12 13 14 15 16 15

0.02 0.05 0.06 0.01 0.05 0.06 0.01 0.05 0.03 0.01 0 0 0 0 0 0 0.12 0.07 0.09 0.22

0.06 0.19 0.17 0.04 0.2 0.18 0.04 0.12 0.08 0.04 0.21 0.56 0.21 0.11 0.26 0.14 0.26 0.13 0.2 0.2

0.03 0.02 0.02 0 0.02 0.02 0 0.01 0.01 0 0 0 0 0 0 0 0 0 0 0

33

Line flow (MVA) 520 520 260 520 520 260 360 280 520 128 260 260 260 260 260 260 128 128 128 64

ACCEPTED MANUSCRIPT

16 15 18 19 10 10 10 10 21 15 22 23 24 25 25 28 27 27 29 8 6

17 18 19 20 20 17 21 22 22 23 24 24 25 26 27 27 29 30 30 28 28

0.08 0.11 0.06 0.03 0.09 0.03 0.03 0.07 0.01 0.1 0.12 0.13 0.19 0.25 0.11 0 0.22 0.32 0.24 0.06 0.02

0.19 0.22 0.13 0.07 0.21 0.08 0.07 0.15 0.02 0.2 0.18 0.27 0.33 0.38 0.21 0.4 0.42 0.6 0.45 0.2 0.06

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.02 0.01

64 64 64 128 128 128 128 128 128 64 64 64 64 64 64 260 64 64 64 128 128

719 720

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ACCEPTED MANUSCRIPT

Highlights The following strong observations have been made towards proposed technique: ο‚·

The paper examines the role of ESS to support RPP penetration in energy and ASM.

ο‚·

The proposed approach considers ESS to tap unexploited RE for energy and SR market.

ο‚·

Three cases are considered in support of the proposed approach of considering ESS.

ο‚·

The paper deals with optimization problem considering various system constraints.