Planning, Operation, and Design of Market-Based Virtual Power Plant Considering Uncertainty

Zahid Ullah, Arshad (), Hany Hassanin, James Cugley and Mohammed Al Alawi
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Zahid Ullah: Institute for Globally Distributed Open Research and Education (IGDORE), Cleveland, Middlesbrough TS1 4JE, UK
Arshad: School of Computing, Engineering and Built Environment, Glasgow Caledonian University, Glasgow G4 0BA, UK
Hany Hassanin: School of Engineering, Technology, and Design, Canterbury Christ Church University, Kent CT1 1QU, UK
James Cugley: School of Engineering, Technology, and Design, Canterbury Christ Church University, Kent CT1 1QU, UK
Mohammed Al Alawi: School of Engineering, Technology, and Design, Canterbury Christ Church University, Kent CT1 1QU, UK

Energies, 2022, vol. 15, issue 19, 1-16

Abstract: The power systems of today seem inseparable from clean energy sources such as wind turbines (WTs) and photovoltaics (PVs). However, due to their uncertain nature, operational challenges are expected when WT and PV energy is added to the electricity network. It is necessary to introduce new technologies to compensate for the intermittent nature of renewable energy sources (RESs). Therefore, rationally implementing a demand response (DR) program with energy storage systems (ESSs) in a virtual power plant (VPP) environment is recommended as a way forward to minimize the volatile nature of RESs and improve power system reliability. Our proposed approach aims to maximize social welfare (SW) (i.e., maximization of consumer benefits while minimizing energy costs). Our method assesses the impact of the DR program on SW maximization. Two scenarios are examined, one with and one without a DR program. Stochastic programming theory is used to address the optimization problem. The uncertain behavior of WTs, PVs, and load demand is modeled using a scenario-based approach. The correctness of the proposed approach is demonstrated on a 16-bus UK generic distribution system. Our results show that SW and active power dispatch capacity of WT, PV, and ESS are fairly increased using the proposed approach.

Keywords: virtual power plant; uncertainty modeling; renewable energy sources; climate change; electricity market; stochastic programming; social welfare (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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