Development of renewable energy resources in Afghanistan for economically optimized cross-border electricity trading

Mohammad Masih Sediqi; Harun Or Rashid Howlader; Abdul Matin Ibrahimi; Mir Sayed Shah Danish; Najib Rahman Sabory; Tomonobu Senjyu; Mohammad Masih Sediqi; Harun Or Rashid Howlader; Abdul Matin Ibrahimi; Mir Sayed Shah Danish; Najib Rahman Sabory; Tomonobu Senjyu

doi:10.3934/energy.2017.4.691

AIMS Energy

2017, Volume 5, Issue 4: 691-717. doi: 10.3934/energy.2017.4.691

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Research article Topical Sections

Development of renewable energy resources in Afghanistan for economically optimized cross-border electricity trading

1.
Electrical and Electronics Engineering Department, University of the Ryukyus, Okinawa, Japan
2.
Energy Engineering Department, Kabul University, Kabul, Afghanistan

Received: 08 June 2017 Accepted: 17 July 2017 Published: 26 July 2017

Afghanistan is a key country between energy surplus areas (Central Asian Republics andIran) and energy deficit regions (Pakistan and India). It is in a position that can facilitate and launchregional electricity trade for the benefit of the region also derive significant gains for its own economyfrom energy imports and exports. On the other hand, Afghanistan is endowed with large renewableenergy resources (RERs), which it could exploit not only to satisfy its domestic power demand butalso to earn significant export revenue. This paper firstly explains the methodology and framework forthe power trade and then presents an optimization framework for profit maximization in the short-runtrading and cost minimization in the long-run trading. The proposed methodology is applied to a realcase between Afghanistan and Pakistan. The objective functions, parameters, variables and constraintsare described for both optimization models. System sizing, simulation and optimization are carriedout using genetic algorithm (GA) technique. The results in the short-run model represent optimalityof about 2654 MW electricity export from Afghanistan to Pakistan during summer. Moreover, resultsderived from running long-run model depict that by utilizing its RERs such as solar, wind and hydro,Afghanistan can not only meet its power demand but also can export to Pakistan during its deficitperiods and gain remarkable energy profits.
- regional electricity trade,
- short-run optimization,
- long-run optimization,
- renewable energy resources,
- system sizing
Citation: Mohammad Masih Sediqi, Harun Or Rashid Howlader, Abdul Matin Ibrahimi, Mir Sayed Shah Danish, Najib Rahman Sabory, Tomonobu Senjyu. Development of renewable energy resources in Afghanistan for economically optimized cross-border electricity trading[J]. AIMS Energy, 2017, 5(4): 691-717. doi: 10.3934/energy.2017.4.691

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Abstract

Afghanistan is a key country between energy surplus areas (Central Asian Republics andIran) and energy deficit regions (Pakistan and India). It is in a position that can facilitate and launchregional electricity trade for the benefit of the region also derive significant gains for its own economyfrom energy imports and exports. On the other hand, Afghanistan is endowed with large renewableenergy resources (RERs), which it could exploit not only to satisfy its domestic power demand butalso to earn significant export revenue. This paper firstly explains the methodology and framework forthe power trade and then presents an optimization framework for profit maximization in the short-runtrading and cost minimization in the long-run trading. The proposed methodology is applied to a realcase between Afghanistan and Pakistan. The objective functions, parameters, variables and constraintsare described for both optimization models. System sizing, simulation and optimization are carriedout using genetic algorithm (GA) technique. The results in the short-run model represent optimalityof about 2654 MW electricity export from Afghanistan to Pakistan during summer. Moreover, resultsderived from running long-run model depict that by utilizing its RERs such as solar, wind and hydro,Afghanistan can not only meet its power demand but also can export to Pakistan during its deficitperiods and gain remarkable energy profits.

References

[1]	Worldometers. Population of Southern Asia, 2017. Available from: http://www.worldometers.info/world-population/southern-asia-population/.
[2]	Central Statistics Office (CSO). Ministry of Statistics and Programme Implementation. Government of India. Available from: http://mospi.nic.in/.
[3]	Pakistan Bureau of Statistics (PBS). Ministry of Economic Affairs and Statistics of Pakistan. Available from: http://www.pbs.gov.pk/.
[4]	Bangladesh GDP Growth Rate. Available from: http://www.tradingeconomics.com/bangladesh/gdpgrowth.
[5]	Integrated Research and Action for Development (IRADe) (2013) Prospects for Regional Cooperation on Cross-Border Electricity Trade in South Asia.
[6]	Faheem JB (2016) Energy Crisis in Pakistan. IRA-Int J of Technol Eng 03: 1-16.
[7]	CASA-1000. Available from: http://www.casa-1000.org/.
[8]	The world Bank. Central Asia-South Asia Electricity Transmission and Trade Project (CASA-1000). Available from: http://www.worldbank.org/en/news/speech/2016/05/13/centralasia-south-asia-electricity-transmission-and-trade-project-casa-1000.
[9]	Sasaki D, Nakayama M (2015) A study on the risk management of the CASA-1000 project. Hydrol Res Lett 9: 90-96. doi: 10.3178/hrl.9.90
[10]	USAID Energy Policy Program (2014) Import of surplus power from Central Asian Republics and Afghanistan to Pakistan.
[11]	The World Bank Group. Development of Electricity Trade in Central Asia-South Asia Region. Available from: http://siteresources.worldbank.org/INTSOUTHASIA/556101-1100091707765/21358230/AfghanistanElectricityTradePaperforDelhiRECC(111006).pdf.
[12]	ADB Technical Assistance Report (2014) Islamic Republic of Afghanistan: Renewable Energy Development. Capacity Development Technical Assistance (CDTA). Project Number: 47266-001.
[13]	Sediqi MM, Furukakoi M, Lotfy ME, et al. (2017) Optimal Economical Sizing of Grid-Connected Hybrid Renewable Energy System. Energy Power Eng 11:244-253.
[14]	Aminjonov F. Afghanistan's energy security. Tracing Central Asian countries' contribution.
[15]	Irving J, Meier P (2012) Afghanistan Resource Corridor Development: Power Sector Analysis. Australian AID.
[16]	Sparrow FT, Brian HB, Shimon KM (2003) General training manual for the purdue long-term electricity trading model. Institute for Interdisciplinary Engineering Studies.
[17]	Shakouri GH, Eghlimi M, Manzoor D (2009) Economically optimized electricity trade modeling: Iran-Turkey case. Energ Policy 37: 472-483. doi: 10.1016/j.enpol.2008.09.074
[18]	Shakouri GH, Eghlimi M, Manzoor D (2006) Power trade between Iran and Turkey: A nonlinear optimization analysis. IEEE 1st Power and Energy Conference. 28-29 November. Malaysia.
[19]	Kousksou T, Bruel P, Jamil A, et al. (2014) Energy storage: applications and challenges. Sol Energ Mat Sol C 120: 59-80. doi: 10.1016/j.solmat.2013.08.015
[20]	Tao M, Hongxing Y, Lin L, et al. (2015) Pumped storage-based standalone photovoltaic power generation system: Modeling and techno-economic optimization. Appl Energ 137: 649-659. doi: 10.1016/j.apenergy.2014.06.005
[21]	Tao M, Hongxing Y, Lin L, et al. (2014) Technical feasibility study on a standalone hybrid solarwind system with pumped hydro storage for a remote island in Hong Kong. Renew Energ 69: 7-15. doi: 10.1016/j.renene.2014.03.028
[22]	Erdinc O, Uzunoglu M (2012) Optimum design of hybrid renewable energy systems: overview of different approaches. Renew Sust Energ Rev 16: 1412-1425. doi: 10.1016/j.rser.2011.11.011
[23]	Kaabeche A, Belhamel M, Lbtiouen R (2011) Sizing Optimization of Grid-Independent Hybrid Photovoltaic/Wind Power Generation System. Energy 36: 1214-1222. doi: 10.1016/j.energy.2010.11.024
[24]	Askarzadeh A, dos Santos Coelho L (2015) A Novel Framework for Optimization of a Grid Independent Hybrid Renewable Energy System: A Case Study of Iran. Sol Energ 112: 383-396. doi: 10.1016/j.solener.2014.12.013
[25]	Hong YY, Lian RC (2012) Optimal Sizing of Hybrid Wind/PV/Diesel Generation in a Stand-Alone Power System Using Markov-Based Genetic Algorithm. IEEE T Power Deliver 27: 640-647. doi: 10.1109/TPWRD.2011.2177102
[26]	Deshmukh MK, Deshmukh SS (2008) Modeling of Hybrid Renewable Energy Systems. Renew Energ Rev 12: 235-249. doi: 10.1016/j.rser.2006.07.011
[27]	Holland JH (1992) Adaptation in natural and artificial systems. MIT Press.
[28]	Malhotra R, Singh N, Singh Y (2011) Genetic algorithms: concepts, design for optimization of process controllers. Computer and Information Science 4: 39-54.
[29]	Feroldi D, Zumoffen D (2014) Sizing methodology for hybrid systems based on multiple renewable power sources integrated to the energy management strategy. Int J of Hydrogen Energ 39: 8609-8620. doi: 10.1016/j.ijhydene.2014.01.003
[30]	Koutroulis E, Kolokotsa D, Potirakis A, et al. (2006) Methodology for optimal sizing of standalone photovoltaic/wind-generator systems using genetic algorithms. Sol Energ 80: 1072-1088. doi: 10.1016/j.solener.2005.11.002

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