GHG Emissions and Monetary Analysis of Electric Power Sector of Pakistan: Alternative Scenarios and it's Implications Academic research paper on "Economics and business"

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Energy Procedía 61 (2014) 2443 - 2449

The 6th International Conference on Applied Energy - ICAE2014

GHG emissions and monetary analysis of electric power sector of Pakistan: Alternative scenarios and it's implications

Usama Perweza*, Ahmed Sohaila

aDepartment of Mechanical Engineering, College of E&ME, National University of Sciences & Technology (NUST), Islamabad and _PO Box 46000, Pakistan_

Abstract

This paper is concerned with analyzing financial and environmental perspective of alternative scenarios for electric power sector of Pakistan. In this paper, LEAP model is used to perform extensive scenario analysis by examining overnight capital cost, fuel cost, operation & maintenance cost (O&M), and greenhouse gases (GHG) emissions from different source of power plants. However, the outcome of simulations show that New Coal scenario (NC) is more attractive economically requiring less running and capital cost than Business as usual scenario (BAU) and Green future scenario (GF). Meanwhile in GHG emissions analysis, GF scenario is more viable in environmental aspect with BAU and NC scenarios having comparatively higher emissions. These scenario simulations provide recommendations in economic and environmental aspect for Pakistan's future electric power sector infrastructure.

©2014The Authors.PublishedbyElsevierLtd. This is anopen access article under the CC BY-NC-ND license

(http://creativecommons.Org/licenses/by-nc-nd/3.0/).

Peer-review under responsibility of the Organizing Committee of ICAE2014

Keywords: GHG emissions; Energy economics; LEAP; Pakistan

1. Introduction

Energy economics is a scientific analysis of allocating resource for supply of energy in a society. It is heavily reliant on policies, demand and supply response of the energy market which is the main reason for uncertainties for energy planners whose main focus is to develop environment for capital investment in energy sector [1]. In context of energy economics dynamics, Pakistan's electric power sector has failed miserably due to substandard maintenance of power plants resulting in de-rated capacity, misuse of subsidies in power tariffs and faulty forecasting of energy mix which resulted in electricity shortfall of

* Corresponding author. Tel.: +92-3455070871 E-mail address: usama13perwez@hotmail.com

1876-6102 © 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license

(http://creativecommons.org/licenses/by-nc-nd/3.0/).

Peer-review under responsibility of the Organizing Committee of ICAE2014

doi: 10.1016/j.egypro.2014.12.020

7000 MW and build up of circular debt worth Rs.300 billion [2] [3]. However, it is expected that electricity demand in Pakistan is expected to increase from existing 136 TWh to 322 TWh in 2030, as shown in Fig. 1, which will require huge capital investment to meet the requirement and this study is based on above forecast which will analyze the overnight capital cost, fuel cost and O&M cost for different source of power plant to estimate the financial investment and running cost incurred annually from 2012 to 2030 in different alternative scenarios [4].

According to EIA (2012), thermal power plants are the highest source of CO2 emissions which is expected to increase manifold up to 2050 due to increase in energy consumption worldwide [5]. In this paper, effect of GHG emissions with comparative cost of emissions reduction is also taken into account due to energy consumption which is expected to increase 240 % as stated above would be the major contributor source of these emissions [6]. Overall this paper will try to figure out the GHG emissions mitigation and total cost incurred per annum to effectively run power electric sector for different policy scenarios to provide recommendation for Pakistan's long term electric power planning.

2. Economic analysis of energy pathways

The energy dynamics used for this analysis is based on fuel cost for each source of power plants and other monetary assumptions to simulates these scenarios as shown in Table 1. Moreover, the sunk capital cost is not considered before 2011 because of difficulty in obtaining data for retroactive cost of power plants and their years of construction. However, comparison of alternative scenarios will be quantified on the basis of future cost by considering overnight capital cost and running cost (fuel and O&M cost).

■ Demand

■ Supply

Fig. 1. Forecasted Demand and Supply of Electricity generation during the study period

Table 1. Energy economic assumptions [7] [8]

Technology Overnight Capital Cost (2011$/KW) O&M Cost (2011$/MWh) Fuel Cost (2011$/MWh)

Nuclear 2000 70 9.15

Gas 550 1.807 35.8

Oil 1000 3.2 154.5

Hydro 1970, 2120 (2020), 2250 (2025) 4.51 -

Biomass 2180, 2110 (2020), 2020 (2025) 8.79, 8.56 (2020), 8.21 (2025) 19.13

Solar PV 2590, 1760 (2020), 1360(2025) 39, 26 (2020), 20 (2025) -

Wind 1480, 1530 (2020), 1440 (2025) 22, 23 (2020), 23 (2025) -

Coal 1100 8.95 25.02

The comparison between BAU and NC scenario shows that O&M cost which is a portion of running cost is similar but in terms of capital cost and fuel cost, there is a significant difference (Fig. 2). In BAU scenario, overnight capital cost is least than others because of reliance on existing energy infrastructure as per government policies. Meanwhile, NC scenario has lower fuel cost in comparison to BAU pathway due to focus on coal power generation. As shown in Fig. 2, the capital cost pattern shows a stable trend during the analysis period with GF pathway slightly increasing from 2020 onwards as country move towards greener technology and focusing on its infrastructure. On the other hand, GF pathway shows different trend than BAU and NC scenarios. The analysis shows that capital investment is higher than other pathways due to higher capital cost linked with renewable technologies and in terms of running cost, GF scenario has low running cost than other scenarios due to increase of power generation from renewables up to 70% in 2030 from 33% in 2011.

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030

Fig. 2. Capital investment and Running cost of additional power generation

The above consideration can be further validated by discounting all the costs over the defined study period. As shown in Fig. 3, total cost incurred includes capital investment, fuel cost and O&M cost is discounted at rates of 4%, 7% and 10%. Comparison of alternative scenarios show that NC scenario have low value at every discount rate because of low fuel cost associated with expansion of coal power generation. Similarly, GF pathway is more expensive than NC scenario because of higher capital investment required for renewable technologies. Meanwhile, BAU scenario shows higher figure than other alternative scenarios due to government policies which focus on existing diversified energy infrastructure resulting in higher running costs than other scenarios.

■ 4Î4 H 7% m 10% 200 -

Fig.. 3. Aggregate NPC at discount rate of 4%, 7% and 10%

The net present generation cost relative to NC pathway is shown in Fig. 4, which provides useful insight into dispersal between running cost and overnight capital cost. It is illustrated in Fig. 4 that GF scenario relative to NC pathway will require higher capital costs ($3 billion) and saving in running cost ($1 billion) due to minimal fuel cost associated with renewable during the 20 year study period. In GF scenario, the discounted capital cost (at 7%) for bringing new power generation in system is $30 billion out of which 70% goes to renewable energy. Meanwhile, NC scenario's discounted capital cost during this study period is $27 billion out of which 46% is spent on coal power generation. This indicates that benefit of renewable technology can be assessed on long term plans when initial investment recovery is done by large savings in running cost of power generation. However, if environmental and social aspect is taken into account relative to thermal power generation than GF pathway can be considered competitive.

u -«A ^ to

Capital Cost Fuel Codt O&M Cost at 7% discount rate

Total Net Cost

Fig. 4. NPC relative to NC scenario at 7% discount rate

3. Greenhouse gas emissions of alternative scenarios

The GHG emissions analysis is based on amount of CO2, NO2 and SO2 emissions per KWh on different source of power generation analyzed according to energy pathway scenario with results as shown in Table 2. As illustrated, NC scenario shows rapid increase of GHG emissions due to shift of power generation to coal. Over the study period (2012-2030) in NC scenario, CO2 emissions increases by 346% from 43.16 to 149.73 million tCO2 which shows increase of 5.61% per annum and similarly, NO2 and SO2 emissions increase by 395% and 327% respectively which shows growth of 13.93% and 24.19% per annum. Moreover, the NC scenario has higher GHG emissions than BAU and GF pathways because of reliance on expansion of coal power generation.

Table 2. Aggregate GHG emissions comparison summary

Scenario Overall CO2 Emissions (million tonne) Overall SO2 Emissions (000 tonne) Overall NO2 Emissions (000 tonne)

BAU 1580 7238.18 3581.86

NC 1796.9 8114.2 4184.59

GF 1140.03 3646.4 2233.31

NC Vs BAU reduction -216.9 -876.02 -602.73

% reduction -12.07 -10.7 -14.40

NPCbau - NPCnc $4 billion $4 billion $4 billion

Abatement Cost in BAU 18.44 $/tCO2 4566.1 $/tSO2 6636.4 $/tNO2

NC Vs GF reduction -656.87 -4461.8 -1951.28

% reduction -36.5 -55.06 -46.63

NPCgf - NPCnc $2 billion $2 billion $2 billion

Abatement Cost in GF 3.04 $/tCO2 448.24 $/tSO2 1024.9 $/tNO2

In BAU scenario, GHG emissions also show the upward trend in the study period because of government policy to import LNG of 800 mmcfd with 400 mmcfd dedicated to power generation and also to run Gaddani energy park on imported coal. This shows that the government will focus on cheapest source of thermal power generation which will have repercussions on environment. However, BAU scenario results in 12%, 10.7% and 14.4% reductions of CO2, SO2 and NO2 emissions respectively relative to NC scenario as shown in Table 2. In contrast to other scenarios, GF scenario follow a stagnant and decreasing trend from 2019 onwards as shown in Fig. 5 because of addition of renewable energy in power generation system. Moreover, Biomass power generation is considered as renewable source because it is termed as 'carbon neutral'. Comparison of three energy pathways show the better environmental performance of GF scenario than NC and BAU scenarios in relation to GHG emissions.

Estimating the cost of GHG emissions is arguable since different source of power generation results in different impacts which vary on multiple dimensions. The simulation can be analyze either by using marginal damage cost method or abatement cost method. In this paper, abatement cost method is used to compare BAU and GF scenarios in relation to NC scenario. In BAU and GF scenarios, CO2 emissions reduction cost is forecasted to be 18.44 $/tCO2 and 3.44 $/tCO2 respectively. According to abatement strategy, it is effective when the investment required is low to avoid 1 tonne of CO2 emissions. In this paper, GF pathway show better results than the other scenarios. However, if we consider factor of net present generation cost (NPC) than GF pathway does not present the chance of reducing

carbon emissions with cost savings which does not qualify it for 'no-regrets' option in future planning recommendation.

C 0 ■H

(fl (fl

Fig. 5. SO2 emissions in period of 2012 to 2030 for all pathways

The abatement cost analysis for NO2 and SO2 emissions is based on same principle of CO2 emissions. There is a considerable similarity in NO2 and SO2 emissions reduction of both scenarios relative to NC pathway. Abatement cost in GF scenario for SO2 and NO2 emissions are 448.24 $/tSO2 and 1024.96 $/tNO2 which is favourably more competitive than BAU scenario as shown in Table 2. It can also be observed that GF scenario shows CO2 emissions reduction accompanied with massive drop in NO2 and SO2 emissions. Since, neither of both scenarios (BAU and GF) presents no regret option which would have resulted in cost saving or zero cost in reducing emissions, so the main purpose is shifted towards improving general welfare issues, public health and air quality problems. This will result in lower health bills and GDP loss related to air and water pollution.

4. Conclusion

In most of the developing countries, the increase in energy demand is met by imported energy and further capital investment in import infrastructure to achieve higher economic growth. In situation of Pakistan, identical energy security dynamics exists which has caused the policy makers to rely on Middle East, Iran and Central Asia resulting in deeper state of energy dependency. Pakistan's energy consumption growth has over leaped the discovered fossil fuel reserves but in this paper, energy pathway analysis shows that Pakistan has still some options which can be adopted by making mature political decisions, use of secure investment in cost efficient power generation and technological interventions. The analysis also show that NC scenario is more economically efficient way forward on long term plan than BAU and GF pathways because it focuses on coal power generation which is untapped resource so far in Pakistan power sector resulting in low running cost as compared to higher capital invested GF scenario and fuel cost enriched BAU scenario. In NPC analysis, NC scenario at 7% discount rate will result in $4 billion and $2 billion saving as compared to BAU and GF pathway respectively. These results

700 600 500 400 300 200 100

t SO2 Emissions (BAU)..

S02 Emissions (NC)

SO2 Emissions (GF)

■mil ii in ii i

MIM I III I ll

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030

show two separate characteristics. Firstly, Pakistan who posses huge coal reserves need to be tapped by bringing foreign investment to gain local expertise in goal gasification as a long term plan and as a short term plan, imported coal transportation network should be build to reduce rising power tariff's which results in circular debt. Secondly, the heavy reliance on coal exhibits that power sector will be a main source of GHG emissions in near future. In contrast to above observations, GHG analysis shows that GF scenario has low air pollutant emissions than other scenarios. The most striking feature of this analysis is that lower emission is achieved by diversifying the energy mix on the basis of utilizing local resources (hydro, wind, solar and bio-mass). However, cleaner scenario pathway in context of Pakistan will bring positive local impact rather than on worldwide issues until focus on promoting CDM projects gains some pace in the policy of government and secondly, the renewable scenario will become more realistic when alternative technologies will start to penetrate or emerge into mainstream energy market. This paper overall analyze three scenarios (BAU, NC and GF) to illustrate the economical efficient and environmentally cleaner way forward for electric power sector with its consequence on dynamics of Pakistan energy market.

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