Muhammad W. Khalid and Ali T. Al-Awami
Coordinated biding strategies, Mixed integer linear programming, Profit maximization, Renewable energy sources, Vehicle to grid services
The minimum up/down time constraints of the thermal units expose them to the risk of operating at low benefits or even at loss at some periods. Also participants with renewable energy sources (RES) are at risk due to their uncertain resources. Energy trading in day-ahead energy market is already risky due to undecided energy and imbalance prices and load demand, whereas participation of RES makes it more risky. Coordinated trading of thermal with RES can mitigate this risk. Moreover, responsive demand can also be used for this purpose. In this paper, the case of a utility that have solar and thermal generators and use electric vehicles (EVs) as responsive demand is investigated. A bidding strategy is proposed for solar-thermal coordination while providing charging EVs through unidirectional vehicle-to-grid (V2G) services. The objective is to maximize the total expected profits of the utility while controlling its risk. The problem is devised as a stochastic mixed integer linear programming (MILP) with four random/stochastic parameters. A realistic case is developed for comparing uncoordinated with coordinated solar-thermal trading utilizing V2G services. Results show that coordination gives rise to higher expected profits and lower risk.
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