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Integration of large-scale energy storage systems (ESSs) is desirable nowadays to achieve higher reliability and efficiency for smart grids. Controlling ESS operation usually depends on electricity market prices so as to charge when the price is low and discharge when the price is high. On the other hand, the market-clearing price itself is determined based on the net demand, i.e., including energy storage output, at every hour. Therefore, it is crucial to develop a mathematical model to determine the optimal ESS operation as well as the market-clearing prices. The problem is formulated as a mixed complementarity problem (MCP) that allows the representation of special (incentive) prices, which cannot be represented in a single optimization model. The proposed model is useful for power system operators to determine the optimal storage dispatch simultaneously with the market-clearing price in addition to the conventional generation dispatch. The impact of energy storage size and location on market price, total generation cost, energy storage arbitrage benefit, and total consumer payment is further investigated in this paper. The latter analysis provides some guidelines for power system planners to identify the optimal size and location for installing large-scale ESSs.Index Terms-Energy storage systems (ESSs), mixed complementarity problem (MCP), smart grids.

The future smart grid is expected to be an integration of intelligent microgrids featured by localized electricity generation, storage, and consumption. Wireless communication is a promising means to facilitate pervasive microgrid monitoring and control at a high flexibility and low deployment cost. In order to avoid a single point of failure, multiagent system (MAS) based decentralized microgrid control is widely considered. In this article, we present a consensus theory based multiagent coordination scheme for information discovery in microgrids via wireless networks. The information discovery process is fully distributed such that each agent only needs to communicate with its direct neighbors. The multiagent coordination is investigated in the presence of interference due to wireless transmissions. Specifically, the communication links among multiple agents may not be established simultaneously to avoid transmission collisions. In order to assure the accuracy of the information discovered by each agent, the convergence of the multiagent coordination is studied. We present the mechanism and principles for the multiagent coordination to achieve convergence in a microgrid via wireless network based on the characteristics of the information to be discovered. Three protocols with different complexities are proposed for normal microgrid operation, which can be readily implemented to off-the-shelf wireless communication devices. The protocols are further extended to achieve microgrid fault recovery by restricting the information exchange in a disconnected region to improve recovery speed. The performance of the proposed protocols is evaluated via a case study based on the network topology and configuration of a realistic microgrid test system. Open research issues and directions are outlined.