Quantifying the Potential Impact of Pakistan’s GHG Mitigation Policies for Coal-Fired Power Plants

Quantifying the Potential Impact of Pakistan’s GHG Mitigation Policies for Coal-Fired Power Plants

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ScienceDirect Availableonline onlineatatwww.sciencedirect.com www.sciencedirect.com Available Energy Procedia 00 (2017) 000–000

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Energy Procedia 142 Energy Procedia 00(2017) (2017)2809–2815 000–000 www.elsevier.com/locate/procedia

9th International Conference on Applied Energy, ICAE2017, 21-24 August 2017, Cardiff, UK

Quantifying the Potential Impact of Pakistan’s GHG Mitigation The 15th International Symposium on District Heating and Cooling Policies for Coal-Fired Power Plants * Assessing the feasibility of using heat demand-outdoor Hanan Ishaquethe temperature function for a long-term district heat demand forecast Alpen Adria University, Universitätsstraße Klagenfurt 9020, Austria Abstract a

I. Andrića,b,c*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc

IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal

b Veolia impact Recherche & Innovation, 291 Avenuegas Dreyfous Daniel, 78520 policies Limay, France This study quantifies the potential of Pakistan’s greenhouse (GHG) mitigation pertaining to coal-fired power c Département Systèmes Énergétiques Environnementin- coal-fired IMT Atlantique, 4 rue Alfred Kastler,and 44300 Nantes, France plants on power sector emissions. Policies foretimprovement generation efficiency carbon capture and storage (CSS) retrofitting for sizable increase in planned coal-based capacity are evaluated. Emission reduction potential, fuel input requirements and emission mitigation costs are estimated by scenario analysis using Pakistan’s bottom-up power sector model. The results show that the impact of coal plant efficiency scenario in emission reduction is limited despite significant fuel cost Abstract savings that result in negative abatement costs. Alternatively, CSS retrofitting scenario requires more input fuel due to efficiency penalty but has a substantially higher potential in reducing GHG emissions by capturing the CO2 emissions. However, high cost heatingmakes networks are commonly addressed the literature as one ofprovides the most effective solutions forfor decreasing ofDistrict CO2 capture it economically unviable. Whileinefficiency improvement a cost-effective measure mitigatingthe greenhouse gas emissions from the building sector. These systems require high investments which are returned through heat GHG emissions in the short run, large-scale deployment of CSS in the long run can potentially mitigate 36 times as muchthe CO2 sales. DueItstocommercial the changed climatehowever, conditions and building policies, heat demand the future emissions. viability, depends on capitalrenovation cost reduction and favorable carboninpricing regimecould in thedecrease, future. prolonging the investment return period. The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand © 2017 The Authors. Published by Elsevier Ltd. forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 Peer-review under responsibility of the scientific committee of the 9th International Conference on Applied Energy. buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were Keywords: GHG emissions; coal-fired power plants; power sector; CCS reftrofitting, Pakistan compared with results from a dynamic heat demand model, previously developed and validated by the authors. The results showed that when only weather change is considered, the margin of error could be acceptable for some applications (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation 1. Introduction scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the Against backdrop Pakistan’s recent energy crisis, the focus of policy has shifted to prioritizing coal-fired decrease in the the number of of heating hours of 22-139h during the heating season (depending on the combination of weather and power generation to considered). meet excessOn demand in hand, the country exceeds available generationper capacity around 5000 renovation scenarios the other functionthat intercept increased for 7.8-12.7% decade by (depending on the Megawatt (MW). ToThe meet the current supply power infrastructure (Gigawatt) coupled scenarios). values suggested coulddeficit, be usedintoaddition modify to theother function parameters for theprojects, scenarios8.4 considered, and improve the accuracy of heat demand estimations.

© 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. Tel.: +43 660 713 4533 Cooling. E-mail address: [email protected]

Keywords: Heat demand; Forecast; Climate change 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the scientific committee of the 9th International Conference on Applied Energy.

1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.

1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the scientific committee of the 9th International Conference on Applied Energy. 10.1016/j.egypro.2017.12.426

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GW of pulverized coal combustion power plants (PCC) under China Pakistan Economic Corridor (CPEC) project will be added to the national grid by the year 2021 [1]. The long-term generation expansion plans foresee an addition of 15 GW of PCC power plants capacity by the 2030 to meet the future demand for electricity consequent upon rapid economic growth as envisioned in Pakistan Vision 2025. The PCC plants require relatively lower capital costs and construction periods as compared to the hydro and other renewable energy plants. For the same reason, the short run generation expansion plans, amid power crisis, rely mainly on PCC based power. However, these power plants could have adverse environmental implications, mainly due to the resulting greenhouse gas (GHG) emissions. Carbon dioxide (CO2) emissions from PCC plants alone are estimated to be around 63.6 MtCO2/year by the year 2030, which are even higher than Pakistan’s total power sector emissions in 2015 [2]. Although Pakistan has a miniscule share in the global GHG emissions, it has been highly vulnerable to adverse impacts of climate change [3]. National climate change policy 2012 puts forward measures for GHG mitigation in the energy sector, but considering the country’s depleting indigenous natural gas reserves and dependence on oil imports, does not preclude the use of coal for electricity generation [4]. Nevertheless, it recommends efficiency improvement and retrofitting of the planned PCC plants with carbon capture and storage (CCS) technology for emission abatement. Pakistan ratified the Paris agreement in 2016 and the Nationally Determined Contribution (NDC) communicated to United Nations Framework Convention on Climate Change includes measures to reduce GHG emissions from various sectors. In energy supply sector, the proposed measures include increase in grid efficiency, improvement in coalbased plant efficiency, renewable energy deployment and the use of CCS when it becomes commercially viable. This paper tries to quantify the impact of energy and emission reduction policies related to the PCC power plants i.e. coal plant efficiency improvement and CCS retrofitting. The policy analysis of climate change mitigation measures and NDC regarding power sector has not been conducted so far, especially in the context of Pakistan’s huge expansion in coal-fired power capacity. Pakistan’s bottom-up power sector model is used to integrate long-term economic and demographic projections with discrete energy and emission mitigation policies to forecast emissions profile in the long run and estimate emission abatement costs. 2. Reference Electricity Demand-Supply Scenario To analyze the impact of polices for GHG mitigation from PCC power plants in the long run and estimate emission abatement costs, the reference scenario in Pakistan’s bottom-up power sector model is built using Long Range Energy Alternatives Planning (LEAP) modelling tool. The bottom-up power sector model forecasts the electricity demand and supply from the years 2014 to 2050 in reference scenario. The long run electricity demand driven by economic, demographic and development trajectory is forecast at disaggregate level [5]. To meet the forecast demand, the longterm electricity supply scenario is developed that depicts supply-side outlook grounded on the power policy 2013 [6], the current generation expansion plans, CPEC energy sector projects [1], long term fuel price forecasts and energy investment trends. Total demand in the country will grow from 82.4 TWh in 2014 to 522 TWh in 2050. Electricity generation in reference scenario will increase from 104 TWh to 580 TWh in 2050. With a total installed capacity of 15 GW, coal will be the second biggest source of electricity as its share will increase from 0.1% in 2014 to 16.5% in 2050. Annual GHG emissions from the power sector will increase from 45 MtCO2 to 118.2 MtCO2 in the year 2050 with 67% emissions released by the coal-fired power plants. GHG emissions from the power sector virtually comprise CO2 since methane and nitrous oxide have negligible shares in the total emissions. Fig. 1 presents power sector emissions by fuel in the reference scenario. 3. GHG Mitigation Policies and Scenario Development Mitigation measures regarding PCC plants recommended in climate change policy 2012 and the NDC are analyzed as policy scenarios to quantify their potential impact on the coal input and long run GHG emission profile of Pakistan’s power sector. 3.1 Coal- Fired Plant Efficiency Scenario Ministry of climate change emphasizes coal-fired plant efficiency improvement policy as one of the high priority measures for GHG mitigation. In this scenario, the policy is assumed to be implemented following the IEA’s

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roadmap [7] and China’s action plan on climate change [8] to install ultra-supercritical (USC) technology in the coalfired plants post 2020. Enhancing the steam parameters of these plants from supercritical (SC) to USC improves net thermal efficiency by 1.8% [9]. Since 7 GW of PCC plants with SC parameters are already under construction and expected to be completed by 2020, this policy scenario assumes mandatory use of USC steam parameters for efficiency improvement of all plants planned between 2020-2030 having generation capacity of 7.9 GW. The capital and operations and management (O&M) costs for USC power plants increases by 3.2% and 1.7% over SC power plants respectively [10]. 3.2 Carbon Capture and Storage Scenario The CCS technology with 90% of CO2 capture potential offers encouraging prospects for mitigating power sector CO2 emissions, however, its large-scale deployment hinges upon significant cost reductions and carbon pricing policies [11]. Full scale CCS deployment in the power sector is unlikely before 2030 [12,13]. National climate change policy recommends installation of the plant designs in PCC power plants that are suitable for CCS retrofitting when the technology becomes commercially viable. Initial screening shows that 14.2 GW of power plants are well placed for retrofitting as per size and efficiency parameters. This scenario assumes implementation of the CSS retrofit policy post 2030 for all the PCC power plants having SC steam parameters. However, many plant specific characteristics and availability of storage sites are important determinants which, in this scenario, are assumed to support CSS deployment. The techno-economic parameters used in the analysis are presented in table 1. Incremental capital and O&M costs for retrofits estimated by NETL [14] have been adjusted to 2014 using Power Capital Cost Index (PCCI), a cost index for power plants excluding nuclear.

Figure 1. Power sector GHG emissions by fuel in reference scenario


Table 1. Techno-economic parameters of coal-fired power plants SCPC USC-PC PC with CCS retrofit




Advanced Amine





Emission factor (Mt/MWh)




Capital cost (mln$/MW)




Fixed cost (000, $/MW)




Variable cost ($/MWh)




Sources: [14–16] * Efficiency penalty of 9% is incurred by carbon capture process

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4. Results Table 2 presents summary results of the cumulative impact of considered policy scenarios on the entire power sector. Total electricity generation in the reference and policy scenarios does not vary much. However, coal input requirement decreases with the installation of high efficiency USC equipped power plants post 2020 as compared with the reference scenario as shown in Fig. 2. Average annual fuel input savings of 0.43 million tonnes of coal equivalent (MtCE) and a total of 13.2 MtCE during the entire analysis period result in significant reduction in GHG emissions. Total GHG emissions saved during 2020-2050 amount to 36 million tonnes of CO2 equivalent (MtCO2). Some studies suggest 7-8 improvement in efficiency by switching from SC to USC steam parameters (e.g. [16,17]). However, this study uses more recent efficiency improvement parameters for USC power plants using lignite coal as input fuel resulting in relatively lower impact on fuel input and GHG reduction. Conversely, the input fuel requirement in CCS scenario increases after the year 2030 as 9 percentage points efficiency penalty is incurred due to energy requirement of the capture process. This implies that additional fuel input is needed to maintain baseline power output as depicted in Fig.2. Total fuel input in the CCS scenario increases by 165.3 MTCE. Nevertheless, CO2 emission rate (t/MWh) after capture using Amine based solvents decreases by 83% saving substantial amount of CO2 emissions during the 20-years’ post CCS retrofitting period. The cumulative GHG savings of 1308 MtCO2 by CSS retrofitting are 36 times higher than that of coal efficiency scenario. Fig. 3. presents the impact of the mitigation policies on power sector GHG emissions. It is worth mentioning that despite significant reduction in overall emissions in the CCS scenario, CH4 and N2O emissions are higher than in reference scenario. While CCS technology only captures CO2, fuel input for power generation and additional input capture process results in higher emissions of the other GHGs.

Figure 2. Coal input requirement in various scenarios

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Figure 3. Power sector total GHG emissions in various policy scenarios

4.1 Economic Analysis of Mitigation Policies All three scenarios are compared by quantifying the net present cost (NPC) using capital and running costs (O&M and fuel costs) discounted at 5% discount rate. GHG emission abatement cost of coal plant efficiency scenario is calculated after Rubin 2011[18] as follows.

NPC eff − NPC ref $ Cost of emission abatement ( )= t GHG ref − GHG eff


The NPC for coal efficiency scenario is slightly lower than that of reference scenario as the savings on fuel input offset the higher capital and O&M costs. The NPC advantage in coal efficiency scenario over the reference scenario drives the emission abatement cost in to negative. The abatement cost for 36 million tonnes of GHG emissions avoided during the life time of power plants is estimated to be -50 $/t. This implies each ton of emissions avoided by improving efficiency also saves $50 due to reduced fuel requirements. For the CCS scenario, the cost of carbon capture is estimated as follows;

Cost of CO2 captured (

COE ccs − COE ref $ )= t CO 2 (t CO 2 MWh)captured


where, COE refers to average cost of electricity per unit in respective scenarios. For 1308.5 MtCO2 of emissions captured by CCS over the 20-year time horizon at 68% average plant factor, the cost of CO2 captured amounts to 53 $/tCO2 which is consistent with EPRI (2012) and GCCSI (2011) [19,20]. Another measure of cost i.e. cost of CO2 avoided is not used in this case as it would be misleading without including transport of storage costs of the captured CO2 in the analysis. Analysis of transport and storage costs depends on the type of terrain, distance of the source of emission to the storage site, the type and capacity of storage reservoirs etc. However, reference CO2 transport costs per ton of CO2 transported over 250 Km as estimated by USDoE (2014) [21] is 4.9 $ while onshore storage costs range between 7-13 $/tCO2. The depleted oil and gas fields in Pakistan have storage capacity of 1.7 Gt of CO2. This capacity is sufficient to sequester 1.31 Gt of CO2 captured between the years 2030-2050 by retrofitting 14.2 GW of PCC power plants. A detailed analysis of the plant-wise mapping with potential storage sources, assessment of development and transportation costs which are highly site, region and market specific, is encouraged for future analysis when CO2 prices rise enough to lure CCS investments.

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Reference scenario

Coal plant efficiency scenario

CCS Retrofit scenario

Fuel Input requirement (MtCE)




CO2 emission (MtCO2)




N2O emissions (MtCO2)




CH4 emissions (000, tCO2)




Net present cost ($ billion)




Emission abatement cost ($/ton)




CO2 capture cost ($/ton)




Total GHG savings (MtCO2)




4. Conclusion Pakistan’s power sector, after a long period of supply deficit and subdued investments, is on the verge of recovery with sizeable capacity additions planned under CPEC project. To meet the growing demand from steady economic growth in the recent years and up to 7% economic growth envisaged in Vision 2025, generation expansion plans include addition of 15 GW of PCC power plants by the year 2030. Average annual GHG emissions from these plants alone amount to 63 MtCO2 totaling 2068 MtCO2 from the years 2014-2050. Although the planned PCC plants would provide reliable baseload besides reducing reliance on oil imports and diversifying power generation mix, the climate change and GHG mitigation policies recommend measures to reduce resulting GHG emissions. This paper analyzed policies for coal plant efficiency improvement and CCS retrofitting for their impact on emission profile, fuel input requirement and the cost of mitigation. Policy scenarios in the light of available technologies were developed, applied and compared with reference scenario using Pakistan’s bottom-up power sector model. The analysis shows that the policy of mandatory use of USC steam parameters in the future PCC plants results in cumulative reduction of 36 MtCO2 of GHG emissions by reducing fuel input requirement by 13.2 MtCE till 2050. Emission abatement cost of coal plant efficiency scenario is negative implying that improving efficiency of PCC plants is economically more viable due to lower NPC over the reference scenario calculated using 5% discount rate for the analysis period. The CCS retrofit scenario based on policy of retrofitting 14.2 GW PCC plants equipped with SC technology reduces CO2 emissions by 1308.5 MtCO2. The cost of carbon capture for CCS scenario is estimated to be 53 $/ton. Cost of avoiding CO2 that also includes transport and storage costs would be higher than carbon capture cost depending on site specific factors. The analysis suggests that improving efficiency of PCC plants has a limited potential in GHG emission mitigation despite negative abatement costs. The planned PCC plants already have high efficiency and enhancing the steam parameters improves the efficiency merely by 1.8%. Total GHG emissions avoided till 2050 are less than the CO2 captured annually by the CSS. The CCS retrofitting saves 36 times more emissions but it is commercially unviable due to high costs. The success of CCS policies hinges on cost reduction due to technological advancements, carbon pricing and regulatory regime. Acknowledgements The author is thankful to Professor Norbert Wohlgemuth, Alpen Adria University Klagenfurt, for his valuable comments and suggestions. References [1]

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