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Optimal Asset Planning for Prosumers Considering Energy Storage and Photovoltaic (PV) Units: A Stochastic Approach

Author

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  • Eleonora Achiluzzi

    (Department of Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada)

  • Kirushaanth Kobikrishna

    (Department of Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada)

  • Abenayan Sivabalan

    (Department of Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada)

  • Carlos Sabillon

    (Department of Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada)

  • Bala Venkatesh

    (Department of Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada)

Abstract

In the distribution system, customers have increasingly use renewable energy sources and battery energy storage systems (BESS), transforming traditional loads into active prosumers. Therefore, methodologies are needed to provide prosumers with tools to optimize their investments and increase business opportunities. In this paper, a stochastic mixed integer linear programming (MILP) formulation is proposed to solve for optimal sizes of prosumer assets, considering the use of a BESS and photovoltaic (PV) units. The objective is to minimize the total cost of the system, which is defined as the combination of a solar PV system investment, BESS investment, maintenance costs of assets, and the cost of electricity supplied by the grid. The developed method defines the optimal size of PV units, the power/energy capacities of the BESS, and the optimal value for initial energy stored in the BESS. Both deterministic and stochastic approaches were explored. For each approach, the proposed model was tested for three cases, providing a varying combination of the use of grid power, PV units, and BESS. The optimal values from each case were compared, showing that there is potential to achieve more economic plans for prosumers when PV and BESS technologies are taken into account.

Suggested Citation

  • Eleonora Achiluzzi & Kirushaanth Kobikrishna & Abenayan Sivabalan & Carlos Sabillon & Bala Venkatesh, 2020. "Optimal Asset Planning for Prosumers Considering Energy Storage and Photovoltaic (PV) Units: A Stochastic Approach," Energies, MDPI, vol. 13(7), pages 1-20, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:7:p:1813-:d:343256
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    1. Akhtar Hussain & Van-Hai Bui & Hak-Man Kim, 2017. "Fuzzy Logic-Based Operation of Battery Energy Storage Systems (BESSs) for Enhancing the Resiliency of Hybrid Microgrids," Energies, MDPI, vol. 10(3), pages 1-19, February.
    2. Nian, Victor & Jindal, Gautam & Li, Hailong, 2019. "A feasibility study on integrating large-scale battery energy storage systems with combined cycle power generation – Setting the bottom line," Energy, Elsevier, vol. 185(C), pages 396-408.
    3. Zafar Iqbal & Nadeem Javaid & Saleem Iqbal & Sheraz Aslam & Zahoor Ali Khan & Wadood Abdul & Ahmad Almogren & Atif Alamri, 2018. "A Domestic Microgrid with Optimized Home Energy Management System," Energies, MDPI, vol. 11(4), pages 1-39, April.
    4. Frida Berglund & Salman Zaferanlouei & Magnus Korpås & Kjetil Uhlen, 2019. "Optimal Operation of Battery Storage for a Subscribed Capacity-Based Power Tariff Prosumer—A Norwegian Case Study," Energies, MDPI, vol. 12(23), pages 1-24, November.
    5. Xiaohan Fang & Jinkuan Wang & Guanru Song & Yinghua Han & Qiang Zhao & Zhiao Cao, 2019. "Multi-Agent Reinforcement Learning Approach for Residential Microgrid Energy Scheduling," Energies, MDPI, vol. 13(1), pages 1-26, December.
    6. Ho-Young Kim & Mun-Kyeom Kim & San Kim, 2017. "Multi-Objective Scheduling Optimization Based on a Modified Non-Dominated Sorting Genetic Algorithm-II in Voltage Source Converter−Multi-Terminal High Voltage DC Grid-Connected Offshore Wind Farms wit," Energies, MDPI, vol. 10(7), pages 1-21, July.
    7. Claudia Rahmann & Benjamin Mac-Clure & Vijay Vittal & Felipe Valencia, 2017. "Break-Even Points of Battery Energy Storage Systems for Peak Shaving Applications," Energies, MDPI, vol. 10(7), pages 1-13, June.
    8. Tomasz Sikorski & Michał Jasiński & Edyta Ropuszyńska-Surma & Magdalena Węglarz & Dominika Kaczorowska & Paweł Kostyła & Zbigniew Leonowicz & Robert Lis & Jacek Rezmer & Wilhelm Rojewski & Marian Sobi, 2019. "A Case Study on Distributed Energy Resources and Energy-Storage Systems in a Virtual Power Plant Concept: Economic Aspects," Energies, MDPI, vol. 12(23), pages 1-21, November.
    9. Pingping Yun & Yongfeng Ren & Yu Xue, 2018. "Energy-Storage Optimization Strategy for Reducing Wind Power Fluctuation via Markov Prediction and PSO Method," Energies, MDPI, vol. 11(12), pages 1-23, December.
    10. McKenna, Eoghan & Thomson, Murray, 2016. "High-resolution stochastic integrated thermal–electrical domestic demand model," Applied Energy, Elsevier, vol. 165(C), pages 445-461.
    11. Koskela, Juha & Rautiainen, Antti & Järventausta, Pertti, 2019. "Using electrical energy storage in residential buildings – Sizing of battery and photovoltaic panels based on electricity cost optimization," Applied Energy, Elsevier, vol. 239(C), pages 1175-1189.
    12. Ying-Yi Hong & Yong-Zhen Lai & Yung-Ruei Chang & Yih-Der Lee & Chia-Hui Lin, 2018. "Optimizing Energy Storage Capacity in Islanded Microgrids Using Immunity-Based Multiobjective Planning," Energies, MDPI, vol. 11(3), pages 1-15, March.
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    8. Ovidiu Ivanov & Bogdan-Constantin Neagu & Gheorghe Grigoras & Florina Scarlatache & Mihai Gavrilas, 2021. "A Metaheuristic Algorithm for Flexible Energy Storage Management in Residential Electricity Distribution Grids," Mathematics, MDPI, vol. 9(19), pages 1-17, September.
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