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Operational Planning and Design of Market-Based Virtual Power Plant with High Penetration of Renewable Energy Sources Zahid Ullah; Muhammad Baseer
International Journal of Renewable Energy Development Vol 11, No 3 (2022): August 2022
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2022.44586

Abstract

Renewable energy sources (RESs) are becoming more prevalent as a source of clean energy, and their integration into the power market is speeding up. The fundamental reason for this is the growing global concern about climate change. However, their weather-dependent and uncertain nature raise questions about grid reliability particularly, when photovoltaics (PVs) and wind turbines (WTs) technologies are used. As a result, rationally managing Energy Storage Systems (ESSs) under the virtual power plant (VPP) setting is being encouraged as a way of minimizing the impact of the uncertain nature of renewable energies. A VPP is comparatively a new concept that aggregates the capacities of dispatchable and non-dispatchable energy sources, electrical loads, and energy storage systems for the purpose of improving energy supply and demand imbalance. It enables individual consumers and producers to participate in the power markets. In this study, a new market-based (MB)-VPP operational planning model is designed and developed with the aim to evaluate the optimal active power dispatched by (WT, PV, and ESS) operating in the day-ahead power market to maximize the social welfare (SW) of the market. SW can be described as the maximization of the consumer’s benefit function minus the cost of energy generation. The optimization process was carried out by using a scenario-based approach to model the uncertainties of renewable energy sources (i.e, WTs & PVs) and load demand. The proposed model and method performance is validated by simulation studies on a 16-bus UK generic distribution system (UKGDS). The simulation results reveal that the proposed approach maximizes overall system social welfare. The capacity of total active power dispatched by (WT, PV, and ESS) has a positive impact on the VPP profit maximization. This empirical study could be used as a reference baseline model for other energy services providers interested in conducting similar research in the future.
Optimisation and Management of Virtual Power Plants Energy Mix Trading Model Zahid Ullah; Nayyar Hussain Mirjat; Muhammad Baseer
International Journal of Renewable Energy Development Vol 11, No 1 (2022): February 2022
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2022.39295

Abstract

. In this study, a robust optimisation method (ROM) is proposed with aim to achieve optimal scheduling of virtual power plants (VPPs) in the day-ahead electricity markets where electricity prices are highly uncertain. Our VPP is a collection of various distributed energy resources (DERs), flexible loads, and energy storage systems that are coordinated and operated as a single entity. In this study, an offer and bid-based energy trading mechanism is proposed where participating members in the VPP setting can sell or buy to/from the day-ahead electricity market to maximise social welfare (SW). SW is defined as the maximisation of end-users benefits and minimisation of energy costs. The optimisation problem is solved as a mixed-integer linear programming model taking the informed decisions at various levels of uncertainty of the market prices. The benefits of the proposed approach are consistency in solution accuracy and traceability due to less computational burden and this would be beneficial for the VPP operators. The robustness of the proposed mathematical model and method is confirmed in a case study approach using a distribution system with 18-buses. Simulation results illustrate that in the highest robustness scenario, profit is reduced marginally, however, the VPP showed robustness towards the day-ahead market (DAM) price uncertainty