IDEAS home Printed from
   My bibliography  Save this article

Optimization of a stand-alone photovoltaic–wind–diesel–battery system with multi-layered demand scheduling


  • Tu, Tu
  • Rajarathnam, Gobinath P.
  • Vassallo, Anthony M.


Operational and financial optimization of a renewable energy-based stand-alone electricity micro-grid is described. Due to the large problem size in time-series models, we construct the model using mixed integer linear programming (MILP). As the constraints required in this model generally have modest complexity, we were able to perform piece-wise linearization on any non-linear variable relationship. Additionally, controls have also be applied on the demand side. Here, a two stage MILP model has been developed to minimize the overall levelized electricity cost for a micro-grid containing a photovoltaic power source, wind turbine, diesel generator, and an energy storage system. The model aimed to converge on a balance of decision accuracy and computational efficiency. Model outputs were capable of defining both the optimal system sizing and scheduling for each system component, with additional demand management control levers on the loss of power supply probability and load deferring allowance. We believe that this model is one of the first to explore the possibilities of the influences of potential demand management strategies in overall system cost reduction, while presenting a relatively efficient first-pass component sizing for stand-alone micro-grids.

Suggested Citation

  • Tu, Tu & Rajarathnam, Gobinath P. & Vassallo, Anthony M., 2019. "Optimization of a stand-alone photovoltaic–wind–diesel–battery system with multi-layered demand scheduling," Renewable Energy, Elsevier, vol. 131(C), pages 333-347.
  • Handle: RePEc:eee:renene:v:131:y:2019:i:c:p:333-347
    DOI: 10.1016/j.renene.2018.07.029

    Download full text from publisher

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

    File URL:
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item

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

    References listed on IDEAS

    1. Rajanna, S. & Saini, R.P., 2016. "Modeling of integrated renewable energy system for electrification of a remote area in India," Renewable Energy, Elsevier, vol. 90(C), pages 175-187.
    2. Ould Bilal, B. & Sambou, V. & Ndiaye, P.A. & Kébé, C.M.F. & Ndongo, M., 2010. "Optimal design of a hybrid solar–wind-battery system using the minimization of the annualized cost system and the minimization of the loss of power supply probability (LPSP)," Renewable Energy, Elsevier, vol. 35(10), pages 2388-2390.
    3. Dufo-López, Rodolfo & Cristóbal-Monreal, Iván R. & Yusta, José M., 2016. "Stochastic-heuristic methodology for the optimisation of components and control variables of PV-wind-diesel-battery stand-alone systems," Renewable Energy, Elsevier, vol. 99(C), pages 919-935.
    4. Yang, Hongxing & Wei, Zhou & Chengzhi, Lou, 2009. "Optimal design and techno-economic analysis of a hybrid solar-wind power generation system," Applied Energy, Elsevier, vol. 86(2), pages 163-169, February.
    5. Bekele, Getachew & Palm, Björn, 2010. "Feasibility study for a standalone solar-wind-based hybrid energy system for application in Ethiopia," Applied Energy, Elsevier, vol. 87(2), pages 487-495, February.
    6. Morais, Hugo & Kádár, Péter & Faria, Pedro & Vale, Zita A. & Khodr, H.M., 2010. "Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming," Renewable Energy, Elsevier, vol. 35(1), pages 151-156.
    7. Mazzola, Simone & Astolfi, Marco & Macchi, Ennio, 2015. "A detailed model for the optimal management of a multigood microgrid," Applied Energy, Elsevier, vol. 154(C), pages 862-873.
    8. Silva, Sergio B. & de Oliveira, Marco A.G. & Severino, Mauro M., 2010. "Economic evaluation and optimization of a photovoltaic-fuel cell-batteries hybrid system for use in the Brazilian Amazon," Energy Policy, Elsevier, vol. 38(11), pages 6713-6723, November.
    9. Zhou, Wei & Yang, Hongxing & Fang, Zhaohong, 2007. "A novel model for photovoltaic array performance prediction," Applied Energy, Elsevier, vol. 84(12), pages 1187-1198, December.
    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. Rodríguez-Gallegos, Carlos D. & Vinayagam, Lokesh & Gandhi, Oktoviano & Yagli, Gokhan Mert & Alvarez-Alvarado, Manuel S. & Srinivasan, Dipti & Reindl, Thomas & Panda, S.K., 2021. "Novel forecast-based dispatch strategy optimization for PV hybrid systems in real time," Energy, Elsevier, vol. 222(C).
    2. Carlo Roselli & Maurizio Sasso & Francesco Tariello, 2020. "A Wind Electric-Driven Combined Heating, Cooling, and Electricity System for an Office Building in Two Italian Cities," Energies, MDPI, Open Access Journal, vol. 13(4), pages 1-25, February.
    3. Ghenai, Chaouki & Bettayeb, Maamar, 2019. "Modelling and performance analysis of a stand-alone hybrid solar PV/Fuel Cell/Diesel Generator power system for university building," Energy, Elsevier, vol. 171(C), pages 180-189.
    4. Qingpeng Cao & Moses Olabhele Esangbedo & Sijun Bai & Caroline Olufunke Esangbedo, 2019. "Grey SWARA-FUCOM Weighting Method for Contractor Selection MCDM Problem: A Case Study of Floating Solar Panel Energy System Installation," Energies, MDPI, Open Access Journal, vol. 12(13), pages 1-30, June.
    5. Cai, Wei & Li, Xing & Maleki, Akbar & Pourfayaz, Fathollah & Rosen, Marc A. & Alhuyi Nazari, Mohammad & Bui, Dieu Tien, 2020. "Optimal sizing and location based on economic parameters for an off-grid application of a hybrid system with photovoltaic, battery and diesel technology," Energy, Elsevier, vol. 201(C).
    6. Roselli, C. & Diglio, G. & Sasso, M. & Tariello, F., 2019. "A novel energy index to assess the impact of a solar PV-based ground source heat pump on the power grid," Renewable Energy, Elsevier, vol. 143(C), pages 488-500.
    7. Aghamolaei, Reihaneh & Shamsi, Mohammad Haris & O’Donnell, James, 2020. "Feasibility analysis of community-based PV systems for residential districts: A comparison of on-site centralized and distributed PV installations," Renewable Energy, Elsevier, vol. 157(C), pages 793-808.
    8. Bahramara, Salah & Sheikhahmadi, Pouria & Golpîra, Hêmin, 2019. "Co-optimization of energy and reserve in standalone micro-grid considering uncertainties," Energy, Elsevier, vol. 176(C), pages 792-804.
    9. Mukhopadhyay, Bineeta & Das, Debapriya, 2021. "Optimal multi-objective expansion planning of a droop-regulated islanded microgrid," Energy, Elsevier, vol. 218(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Mahesh, Aeidapu & Sandhu, Kanwarjit Singh, 2015. "Hybrid wind/photovoltaic energy system developments: Critical review and findings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1135-1147.
    3. Erdinc, O. & Uzunoglu, M., 2012. "Optimum design of hybrid renewable energy systems: Overview of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1412-1425.
    4. Bahramara, S. & Moghaddam, M. Parsa & Haghifam, M.R., 2016. "Optimal planning of hybrid renewable energy systems using HOMER: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 609-620.
    5. Prasad, Abhnil A. & Taylor, Robert A. & Kay, Merlinde, 2017. "Assessment of solar and wind resource synergy in Australia," Applied Energy, Elsevier, vol. 190(C), pages 354-367.
    6. Chen, Jun & Garcia, Humberto E., 2016. "Economic optimization of operations for hybrid energy systems under variable markets," Applied Energy, Elsevier, vol. 177(C), pages 11-24.
    7. Yu, Nan & Kang, Jin-Su & Chang, Chung-Chuan & Lee, Tai-Yong & Lee, Dong-Yup, 2016. "Robust economic optimization and environmental policy analysis for microgrid planning: An application to Taichung Industrial Park, Taiwan," Energy, Elsevier, vol. 113(C), pages 671-682.
    8. Sinha, Sunanda & Chandel, S.S., 2015. "Review of recent trends in optimization techniques for solar photovoltaic–wind based hybrid energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 755-769.
    9. Mazzola, Simone & Astolfi, Marco & Macchi, Ennio, 2015. "A detailed model for the optimal management of a multigood microgrid," Applied Energy, Elsevier, vol. 154(C), pages 862-873.
    10. Chen, Jun & Rabiti, Cristian, 2017. "Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems," Energy, Elsevier, vol. 120(C), pages 507-517.
    11. Scioletti, Michael S. & Goodman, Johanna K. & Kohl, Paul A. & Newman, Alexandra M., 2016. "A physics-based integer-linear battery modeling paradigm," Applied Energy, Elsevier, vol. 176(C), pages 245-257.
    12. Chen, Hung-Cheng, 2013. "Optimum capacity determination of stand-alone hybrid generation system considering cost and reliability," Applied Energy, Elsevier, vol. 103(C), pages 155-164.
    13. Elma, Onur & Selamogullari, Ugur Savas, 2012. "A comparative sizing analysis of a renewable energy supplied stand-alone house considering both demand side and source side dynamics," Applied Energy, Elsevier, vol. 96(C), pages 400-408.
    14. Tezer, Tuba & Yaman, Ramazan & Yaman, Gülşen, 2017. "Evaluation of approaches used for optimization of stand-alone hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 840-853.
    15. Zahraee, S.M. & Khalaji Assadi, M. & Saidur, R., 2016. "Application of Artificial Intelligence Methods for Hybrid Energy System Optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 617-630.
    16. Xiaohang Wang & Wentong Chong & Kokhoe Wong & Saihin Lai & Liphuat Saw & Xianbo Xiang & Chin-Tsan Wang, 2019. "Preliminary Techno–Environment–Economic Evaluation of an Innovative Hybrid Renewable Energy Harvester System for Residential Application," Energies, MDPI, Open Access Journal, vol. 12(8), pages 1-28, April.
    17. Mbodji, Abdoul K. & Ndiaye, Mamadou L. & Ndiaye, Papa A., 2016. "Decentralized control of the hybrid electrical system consumption: A multi-agent approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 972-978.
    18. Bismark Singh & Bernard Knueven, 2021. "Lagrangian relaxation based heuristics for a chance-constrained optimization model of a hybrid solar-battery storage system," Journal of Global Optimization, Springer, vol. 80(4), pages 965-989, August.
    19. Mohammed, Y.S. & Mustafa, M.W. & Bashir, N., 2014. "Hybrid renewable energy systems for off-grid electric power: Review of substantial issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 527-539.
    20. Kwon, Sunghoon & Won, Wangyun & Kim, Jiyong, 2016. "A superstructure model of an isolated power supply system using renewable energy: Development and application to Jeju Island, Korea," Renewable Energy, Elsevier, vol. 97(C), pages 177-188.


    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:renene:v:131:y:2019:i:c:p:333-347. 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: . 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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: .

    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.