Modeling, Optimization, and Analysis of a Virtual Power Plant Demand Response Mechanism for the Internal Electricity Market Considering the Uncertainty of Renewable Energy Sources

The penetration of renewable energy sources (RESs) in the electrical power system has increased significantly over the past years due to increasing global concern about climate change. However, integrating RESs into the power market is highly problematic. The output of RESs such as wind turbines (WT...

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Main Authors: Zahid Ullah, Arshad, Hany Hassanin
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/15/14/5296
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author Zahid Ullah
Arshad
Hany Hassanin
author_facet Zahid Ullah
Arshad
Hany Hassanin
author_sort Zahid Ullah
collection DOAJ
description The penetration of renewable energy sources (RESs) in the electrical power system has increased significantly over the past years due to increasing global concern about climate change. However, integrating RESs into the power market is highly problematic. The output of RESs such as wind turbines (WTs) and photovoltaics (PVs) is highly uncertain. Their correlation with load demand is not always guaranteed, which compromises system reliability. Distributed energy resources (DERs), especially demand response (DR) programs and energy storage systems (ESSs), are possible options to overcome these operational challenges under the virtual power plant (VPP) setting. This study investigates the impact of using a DR program and battery energy storage system (BESS) on the VPP’s internal electricity market, and also cost-minimization analysis from a utility viewpoint. Three different constrained optimal power flow (OPF) problems are solved such as base case, DR case, and BESS case to determine total incurred costs, locational marginal prices (LMPs), and generator commitments. A scenario tree approach is used to model the uncertainties associated with WTs, PVs, and load demand. The proposed model is investigated on a 14-bus distribution system. The simulation results obtained demonstrate a favorable impact of DR and a BESS on renewable operational challenges.
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spelling doaj.art-cc2812e55656473fb866a65903dd3ab32023-11-30T23:09:01ZengMDPI AGEnergies1996-10732022-07-011514529610.3390/en15145296Modeling, Optimization, and Analysis of a Virtual Power Plant Demand Response Mechanism for the Internal Electricity Market Considering the Uncertainty of Renewable Energy SourcesZahid Ullah0Arshad1Hany Hassanin2Institute for Globally Distributed Open Research and Education (IGDORE), Cleveland, Middlesbrough TS1 4JE, UKSchool of Computing, Engineering and Built Environment, Glasgow Caledonian University, Glasgow G4 0BA, UKSchool of Engineering, Technology, and Design, Canterbury Christ Church University, Canterbury CT1 1QU, UKThe penetration of renewable energy sources (RESs) in the electrical power system has increased significantly over the past years due to increasing global concern about climate change. However, integrating RESs into the power market is highly problematic. The output of RESs such as wind turbines (WTs) and photovoltaics (PVs) is highly uncertain. Their correlation with load demand is not always guaranteed, which compromises system reliability. Distributed energy resources (DERs), especially demand response (DR) programs and energy storage systems (ESSs), are possible options to overcome these operational challenges under the virtual power plant (VPP) setting. This study investigates the impact of using a DR program and battery energy storage system (BESS) on the VPP’s internal electricity market, and also cost-minimization analysis from a utility viewpoint. Three different constrained optimal power flow (OPF) problems are solved such as base case, DR case, and BESS case to determine total incurred costs, locational marginal prices (LMPs), and generator commitments. A scenario tree approach is used to model the uncertainties associated with WTs, PVs, and load demand. The proposed model is investigated on a 14-bus distribution system. The simulation results obtained demonstrate a favorable impact of DR and a BESS on renewable operational challenges.https://www.mdpi.com/1996-1073/15/14/5296renewable energy sourcesdemand responseenergy storageelectricity marketuncertainty modelinglocational marginal prices
spellingShingle Zahid Ullah
Arshad
Hany Hassanin
Modeling, Optimization, and Analysis of a Virtual Power Plant Demand Response Mechanism for the Internal Electricity Market Considering the Uncertainty of Renewable Energy Sources
Energies
renewable energy sources
demand response
energy storage
electricity market
uncertainty modeling
locational marginal prices
title Modeling, Optimization, and Analysis of a Virtual Power Plant Demand Response Mechanism for the Internal Electricity Market Considering the Uncertainty of Renewable Energy Sources
title_full Modeling, Optimization, and Analysis of a Virtual Power Plant Demand Response Mechanism for the Internal Electricity Market Considering the Uncertainty of Renewable Energy Sources
title_fullStr Modeling, Optimization, and Analysis of a Virtual Power Plant Demand Response Mechanism for the Internal Electricity Market Considering the Uncertainty of Renewable Energy Sources
title_full_unstemmed Modeling, Optimization, and Analysis of a Virtual Power Plant Demand Response Mechanism for the Internal Electricity Market Considering the Uncertainty of Renewable Energy Sources
title_short Modeling, Optimization, and Analysis of a Virtual Power Plant Demand Response Mechanism for the Internal Electricity Market Considering the Uncertainty of Renewable Energy Sources
title_sort modeling optimization and analysis of a virtual power plant demand response mechanism for the internal electricity market considering the uncertainty of renewable energy sources
topic renewable energy sources
demand response
energy storage
electricity market
uncertainty modeling
locational marginal prices
url https://www.mdpi.com/1996-1073/15/14/5296
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