Journal
IET GENERATION TRANSMISSION & DISTRIBUTION
Volume 11, Issue 15, Pages 3713-3721Publisher
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-gtd.2016.1916
Keywords
energy management systems; electric vehicles; multi-agent systems; smart power grids; energy storage; power system stability; voltage control; pricing; oligopoly; solar power stations; wind turbines; wind power plants; multiagent transactive energy management system; renewable energy source; electric vehicles; smart grids; EVs; energy storage systems; ESSs; voltage stability; TEMS; profit maximization; real-time pricing; Cournot oligopoly competition model; voltage regulation constraints; merit order effect; indirect control method; modified IEEE 37-bus test system; wind turbines; solar plants; RESs oscillation; customer cost minimization; capacitor bank
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Funding
- ICT Consilience Creative Program [IITP-2015-R0346-15-1007]
- NRF, Korea [NRF-2015R1C1A1A01053788]
- National Research Foundation of Korea [2015R1C1A1A01053788] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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The future smart grids (SGs) consist of considerable amount of renewable energy sources (RESs), electrical vehicles (EVs), and energy storage systems (ESSs). The uncertainties associated with EVs and uncontrollable nature of RESs have magnified voltage stability challenges and the importance of an effective energy management system (EMS) in SGs as a practical solution. This study presents a multi-agent transactive energy management system (TEMS) to control demand and supply in the presence of high levels of RESs and EVs, and maximises profit of each participant in addition to satisfying voltage regulation constraints. For this purpose, a real-time pricing is considered based on Cournot oligopoly competition model for demand and merit order effect for production to compensate RESs' fluctuations in real time by an indirect control method. Simulations are conducted in the modified IEEE 37-bus test system with 1141 customers, 670 EVs, two solar plants, four wind turbines, and one ESS. The results show that the proposed multi-agent TEMS can indirectly control EVs, elastic loads, and ESSs to balance the RESs oscillation, minimise customers cost, and regulate voltage in a real-time manner.
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