1Institute for Globally Distributed Open Research and Education (IGDORE), Cleveland, Middlesbrough, TS1 4JE, United Kingdom
2Mehran University of Science and Technology, Indus Hwy, Jamshoro Sindh, 76062, Pakistan
3University of Bradford, Richmond Rd, Bradford, BD7 1DP, United Kingdom
BibTex Citation Data :
@article{IJRED39295, author = {Zahid Ullah and Nayyar Mirjat and Muhammad Baseer}, title = {Optimisation and Management of Virtual Power Plants Energy Mix Trading Model}, journal = {International Journal of Renewable Energy Development}, volume = {11}, number = {1}, year = {2022}, keywords = {Renewable energies, Distributed energy resources; Power systems integration; Electricity market}, 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}, pages = {83--94} doi = {10.14710/ijred.2022.39295}, url = {https://ejournal.undip.ac.id/index.php/ijred/article/view/39295} }
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Energy trading support decision model of distributed energy resources aggregator in day-ahead market considering multi-stakeholder risk preference behaviors
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The Development of a Cross-Border Energy Trade Cooperation Model of Interconnected Virtual Power Plants Using Bilateral Contracts
The impact of Energy Storage System on the flexible operation of the Renewable-Based Virtual Power Plant
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Last update: 2024-11-22 09:31:26
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