Day-Ahead scheduling of centralized energy storage system in electrical networks by proposed stochastic MILP-Based bi-objective optimization approach

Abstract

Recently, employing environmentally-friendly devices such as Energy Storage Systems (EESs) and Renewable Energy Resources (RERs) has been one of the remarkable ways to reduce electricity generation cost as well as environmental issues. Due to the stochastic nature of injected power through the RERs resulting from variable weather conditions, serving the devices and systems to the electrical grid in order to alleviate the output fluctuations of these resources should be taken into consideration. Installation of energy storage units can be one of the applicable ways that lessens the power variations of RESs by exchanging the required real power into the network through a day. In the current paper, the day-ahead scheduling of ESS in the presence of wind farm uncertainty has been obtained by implementing the proposed stochastic Mixed Integer Linear Programming (MILP)-based bi-objective optimization approach. The suggested objective functions are the daily electricity generation cost and emission pollutants released through the thermal power plants. Based on the presented framework, a simultaneous cost-emission minimization scheme is carried out by deriving Pareto optimal solutions by epsilon-constraint technique. It is noteworthy that one strategy is required to determine optimal ESS operation according to the decision maker's point of view. Thus, the Fuzzy satisfying method as a selection criterion has been exploited to obtain the appropriate solution by compromising between the objective functions. The case study is the IEEE-30BUS system. According to simulation results derived from implementing the proposed framework, it has been concluded that during off-peak periods of the day, the hourly electricity generation cost and emission are increased. On the other hand, the hourly cost and emission have been reduced during on-peak hours. The daily cost and emission are reduced by employing the energy storage unit. Moreover, peak-shaving and peak-shifting resulting from the suitable ESS operation are illustrated in this paper.