IDEAS home Printed from
   My bibliography  Save this article

Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources


  • Adefarati, T.
  • Bansal, R.C.


The application of renewable energy resources in a power system has received significant attention owing to the environmental impacts and fluctuations of fossil fuel prices. Consequently, renewable energy resources have become important sources to generate power at the commercial level due to their various benefits, coupled with the government incentives and public supports. This research work is focused on the evaluation of the reliability, economic and environmental benefits of renewable energy resources in a microgrid system. The lifecycle analysis of a microgrid system that consists of the photovoltaic, wind turbine generator, electric storage system and diesel generator is implemented in this study to test their commercial prospects in rural communities that have no access to electricity due to economic and technical constraints. The objective of this research work is to minimize the cost of energy, lifecycle cost, the annual cost of load loss and lifecycle greenhouse gas emission cost as well as to improve the overall benefit of green technologies in the proposed microgrid system. This objective is achieved by utilizing the basic probability concept to obtain the reliability performance indicators such as expected energy not served, loss of load expectation and loss of load probability, in addition to utilizing an fmincon optimization tool in the MATLAB environment to investigate the environmental and economic effects of renewable energy resources in a power system. The suitability of the model is tested on six case studies by using the same load profile, wind speed and irradiation of the site and diesel generator power capacity. The market factors such as interest rate and price of diesel fuel as well as forced outage rate, annual peak load variation and distributed generation penetration level are utilized to study their impacts on the operation of a microgrid system. The results obtained in this study demonstrate the optimal feasibility of renewable energy resources in a microgrid system. This indicates that it offers a significant reduction in the values of lifecycle cost, cost of energy, greenhouse gas emission cost and the annual cost of load loss when compared with case study 1. This research work shows that the utilization of green technologies in a microgrid system optimizes the reliability, cost savings, lifecycle cost and environmental impact. The technique adopted in the study can serve as a reference for rural electrification projects and solve socioeconomic problems that are associated with power outages.

Suggested Citation

  • Adefarati, T. & Bansal, R.C., 2019. "Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources," Applied Energy, Elsevier, vol. 236(C), pages 1089-1114.
  • Handle: RePEc:eee:appene:v:236:y:2019:i:c:p:1089-1114
    DOI: 10.1016/j.apenergy.2018.12.050

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Parra, David & Norman, Stuart A. & Walker, Gavin S. & Gillott, Mark, 2017. "Optimum community energy storage for renewable energy and demand load management," Applied Energy, Elsevier, vol. 200(C), pages 358-369.
    2. Adefarati, T. & Bansal, R.C., 2017. "Reliability assessment of distribution system with the integration of renewable distributed generation," Applied Energy, Elsevier, vol. 185(P1), pages 158-171.
    3. Ghorbani, Narges & Kasaeian, Alibakhsh & Toopshekan, Ashkan & Bahrami, Leyli & Maghami, Amin, 2018. "Optimizing a hybrid wind-PV-battery system using GA-PSO and MOPSO for reducing cost and increasing reliability," Energy, Elsevier, vol. 154(C), pages 581-591.
    4. van der Stelt, Sander & AlSkaif, Tarek & van Sark, Wilfried, 2018. "Techno-economic analysis of household and community energy storage for residential prosumers with smart appliances," Applied Energy, Elsevier, vol. 209(C), pages 266-276.
    5. Li, Yang & Feng, Bo & Li, Guoqing & Qi, Junjian & Zhao, Dongbo & Mu, Yunfei, 2018. "Optimal distributed generation planning in active distribution networks considering integration of energy storage," Applied Energy, Elsevier, vol. 210(C), pages 1073-1081.
    6. Sardi, Junainah & Mithulananthan, N. & Gallagher, M. & Hung, Duong Quoc, 2017. "Multiple community energy storage planning in distribution networks using a cost-benefit analysis," Applied Energy, Elsevier, vol. 190(C), pages 453-463.
    7. Parra, David & Gillott, Mark & Norman, Stuart A. & Walker, Gavin S., 2015. "Optimum community energy storage system for PV energy time-shift," Applied Energy, Elsevier, vol. 137(C), pages 576-587.
    8. Amrollahi, Mohammad Hossein & Bathaee, Seyyed Mohammad Taghi, 2017. "Techno-economic optimization of hybrid photovoltaic/wind generation together with energy storage system in a stand-alone micro-grid subjected to demand response," Applied Energy, Elsevier, vol. 202(C), pages 66-77.
    9. Morano, Pierluigi & Tajani, Francesco & Locurcio, Marco, 2017. "GIS application and econometric analysis for the verification of the financial feasibility of roof-top wind turbines in the city of Bari (Italy)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 999-1010.
    10. Zhang, Shenxi & Cheng, Haozhong & Wang, Dan & Zhang, Libo & Li, Furong & Yao, Liangzhong, 2018. "Distributed generation planning in active distribution network considering demand side management and network reconfiguration," Applied Energy, Elsevier, vol. 228(C), pages 1921-1936.
    11. Sanajaoba, Sarangthem & Fernandez, Eugene, 2016. "Maiden application of Cuckoo Search algorithm for optimal sizing of a remote hybrid renewable energy System," Renewable Energy, Elsevier, vol. 96(PA), pages 1-10.
    12. Marini, Abbas & Latify, Mohammad Amin & Ghazizadeh, Mohammad Sadegh & Salemnia, Ahmad, 2015. "Long-term chronological load modeling in power system studies with energy storage systems," Applied Energy, Elsevier, vol. 156(C), pages 436-448.
    13. Chade, Daniel & Miklis, Tomasz & Dvorak, David, 2015. "Feasibility study of wind-to-hydrogen system for Arctic remote locations – Grimsey island case study," Renewable Energy, Elsevier, vol. 76(C), pages 204-211.
    14. Aghajani, G.R. & Shayanfar, H.A. & Shayeghi, H., 2017. "Demand side management in a smart micro-grid in the presence of renewable generation and demand response," Energy, Elsevier, vol. 126(C), pages 622-637.
    15. Li, M.S. & Lin, Z.J. & Ji, T.Y. & Wu, Q.H., 2018. "Risk constrained stochastic economic dispatch considering dependence of multiple wind farms using pair-copula," Applied Energy, Elsevier, vol. 226(C), pages 967-978.
    16. Zhao, Bo & Zhang, Xuesong & Li, Peng & Wang, Ke & Xue, Meidong & Wang, Caisheng, 2014. "Optimal sizing, operating strategy and operational experience of a stand-alone microgrid on Dongfushan Island," Applied Energy, Elsevier, vol. 113(C), pages 1656-1666.
    17. Ogunjuyigbe, A.S.O. & Ayodele, T.R. & Akinola, O.A., 2016. "Optimal allocation and sizing of PV/Wind/Split-diesel/Battery hybrid energy system for minimizing life cycle cost, carbon emission and dump energy of remote residential building," Applied Energy, Elsevier, vol. 171(C), pages 153-171.
    18. Nan, Sibo & Zhou, Ming & Li, Gengyin, 2018. "Optimal residential community demand response scheduling in smart grid," Applied Energy, Elsevier, vol. 210(C), pages 1280-1289.
    19. González, Arnau & Riba, Jordi-Roger & Rius, Antoni & Puig, Rita, 2015. "Optimal sizing of a hybrid grid-connected photovoltaic and wind power system," Applied Energy, Elsevier, vol. 154(C), pages 752-762.
    20. Das, Barun K. & Al-Abdeli, Yasir M. & Kothapalli, Ganesh, 2017. "Optimisation of stand-alone hybrid energy systems supplemented by combustion-based prime movers," Applied Energy, Elsevier, vol. 196(C), pages 18-33.
    21. Das, Choton K. & Bass, Octavian & Kothapalli, Ganesh & Mahmoud, Thair S. & Habibi, Daryoush, 2018. "Optimal placement of distributed energy storage systems in distribution networks using artificial bee colony algorithm," Applied Energy, Elsevier, vol. 232(C), pages 212-228.
    22. Crespo Del Granado, Pedro & Pang, Zhan & Wallace, Stein W., 2016. "Synergy of smart grids and hybrid distributed generation on the value of energy storage," Applied Energy, Elsevier, vol. 170(C), pages 476-488.
    23. Malheiro, André & Castro, Pedro M. & Lima, Ricardo M. & Estanqueiro, Ana, 2015. "Integrated sizing and scheduling of wind/PV/diesel/battery isolated systems," Renewable Energy, Elsevier, vol. 83(C), pages 646-657.
    24. Roy, Apratim & Kabir, Md. Ashfanoor, 2012. "Relative life cycle economic analysis of stand-alone solar PV and fossil fuel powered systems in Bangladesh with regard to load demand and market controlling factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4629-4637.
    25. Santos, Sérgio F. & Fitiwi, Desta Z. & Cruz, Marco R.M. & Cabrita, Carlos M.P. & Catalão, João P.S., 2017. "Impacts of optimal energy storage deployment and network reconfiguration on renewable integration level in distribution systems," Applied Energy, Elsevier, vol. 185(P1), pages 44-55.
    26. Julia M. Puaschunder, 2018. "Intergenerational Responsibility in the 21st Century," Vernon Press Titles in Economics, Vernon Art and Science Inc, edition 1, number 135, February.
    27. Chauhan, Anurag & Saini, R.P., 2014. "A review on Integrated Renewable Energy System based power generation for stand-alone applications: Configurations, storage options, sizing methodologies and control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 99-120.
    28. Dufo-López, Rodolfo & Bernal-Agustín, José L. & Yusta-Loyo, José M. & Domínguez-Navarro, José A. & Ramírez-Rosado, Ignacio J. & Lujano, Juan & Aso, Ismael, 2011. "Multi-objective optimization minimizing cost and life cycle emissions of stand-alone PV–wind–diesel systems with batteries storage," Applied Energy, Elsevier, vol. 88(11), pages 4033-4041.
    29. Abbes, Dhaker & Martinez, André & Champenois, Gérard, 2014. "Life cycle cost, embodied energy and loss of power supply probability for the optimal design of hybrid power systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 98(C), pages 46-62.
    30. Azimoh, Chukwuma Leonard & Klintenberg, Patrik & Mbohwa, Charles & Wallin, Fredrik, 2017. "Replicability and scalability of mini-grid solution to rural electrification programs in sub-Saharan Africa," Renewable Energy, Elsevier, vol. 106(C), pages 222-231.
    31. Amutha, W. Margaret & Rajini, V., 2016. "Cost benefit and technical analysis of rural electrification alternatives in southern India using HOMER," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 236-246.
    32. Nadjemi, O. & Nacer, T. & Hamidat, A. & Salhi, H., 2017. "Optimal hybrid PV/wind energy system sizing: Application of cuckoo search algorithm for Algerian dairy farms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1352-1365.
    33. Dufo-López, Rodolfo & Cristóbal-Monreal, Iván R. & Yusta, José M., 2016. "Optimisation of PV-wind-diesel-battery stand-alone systems to minimise cost and maximise human development index and job creation," Renewable Energy, Elsevier, vol. 94(C), pages 280-293.
    34. Shahzad, M. Kashif & Zahid, Adeem & ur Rashid, Tanzeel & Rehan, Mirza Abdullah & Ali, Muzaffar & Ahmad, Mueen, 2017. "Techno-economic feasibility analysis of a solar-biomass off grid system for the electrification of remote rural areas in Pakistan using HOMER software," Renewable Energy, Elsevier, vol. 106(C), pages 264-273.
    35. Ma, Tao & Yang, Hongxing & Lu, Lin, 2014. "A feasibility study of a stand-alone hybrid solar–wind–battery system for a remote island," Applied Energy, Elsevier, vol. 121(C), pages 149-158.
    36. Arnau González & Jordi-Roger Riba & Antoni Rius, 2015. "Optimal Sizing of a Hybrid Grid-Connected Photovoltaic–Wind–Biomass Power System," Sustainability, MDPI, Open Access Journal, vol. 7(9), pages 1-20, September.
    37. Brodrick, Philip G. & Brandt, Adam R. & Durlofsky, Louis J., 2018. "Optimal design and operation of integrated solar combined cycles under emissions intensity constraints," Applied Energy, Elsevier, vol. 226(C), pages 979-990.
    38. Adefarati, T. & Bansal, R.C., 2017. "Reliability and economic assessment of a microgrid power system with the integration of renewable energy resources," Applied Energy, Elsevier, vol. 206(C), pages 911-933.
    39. repec:wly:emjrnl:v:21:y:2018:i:3:p:264-276 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Dhunny, A.Z. & Allam, Z. & Lobine, D. & Lollchund, M.R., 2019. "Sustainable renewable energy planning and wind farming optimization from a biodiversity perspective," Energy, Elsevier, vol. 185(C), pages 1282-1297.
    2. Wang, Richard & Lam, Chor-Man & Hsu, Shu-Chien & Chen, Jieh-Haur, 2019. "Life cycle assessment and energy payback time of a standalone hybrid renewable energy commercial microgrid: A case study of Town Island in Hong Kong," Applied Energy, Elsevier, vol. 250(C), pages 760-775.
    3. Khawaja, Yara & Allahham, Adib & Giaouris, Damian & Patsios, Charalampos & Walker, Sara & Qiqieh, Issa, 2019. "An integrated framework for sizing and energy management of hybrid energy systems using finite automata," Applied Energy, Elsevier, vol. 250(C), pages 257-272.
    4. Mike Brian Ndawula & Sasa Z. Djokic & Ignacio Hernando-Gil, 2019. "Reliability Enhancement in Power Networks under Uncertainty from Distributed Energy Resources," Energies, MDPI, Open Access Journal, vol. 12(3), pages 1-24, February.
    5. Bartolucci, Lorenzo & Cordiner, Stefano & Mulone, Vincenzo & Pasquale, Stefano, 2019. "Fuel cell based hybrid renewable energy systems for off-grid telecom stations: Data analysis and system optimization," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    6. Dincer, Hasan & Yuksel, Serhat, 2019. "Balanced scorecard-based analysis of investment decisions for the renewable energy alternatives: A comparative analysis based on the hybrid fuzzy decision-making approach," Energy, Elsevier, vol. 175(C), pages 1259-1270.
    7. Mi, Yang & Chen, Xin & Ji, Hongpeng & Ji, Liang & Fu, Yang & Wang, Chengshan & Wang, Jianhui, 2019. "The coordinated control strategy for isolated DC microgrid based on adaptive storage adjustment without communication," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    8. Wenhui Zhao & Ruican Zou & Guanghui Yuan & Hui Wang & Zhongfu Tan, 2019. "Long-Term Cointegration Relationship between China’s Wind Power Development and Carbon Emissions," Sustainability, MDPI, Open Access Journal, vol. 11(17), pages 1-12, August.

    More about this item


    Economic; Emission; Environment; Microgrid; Reliability;


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:236:y:2019:i:c:p:1089-1114. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.