Optimal Allocation of Energy Storage Considering N-1 Security Constraints Based on Chance Constraints

In order to solve the problems of energy storage location and capacity in transmission network with high percentage of renewable energy, an optimal method considering N-1 security constraints based on chance constraints was proposed. It can calculate the location, rated capacity and power of energy storage. On the premise of ensuring the security of the transmission network, the economic benefits of the transmission network and the proportion of new energy consumption should be improved. In this paper, the benefits of power plants, renewable plants and energy storage owners were considered. An object function was established to minimize the generating cost, wind-solar energy abandoning cost and maximize energy storage benefits. To acquire the optimal location, rated capacity and power of energy storage, many constraints were introduced, such as conventional generators on-off and power output, charge-discharge state and power of energy storage, N and N-1 security constraints of transmission network. According to the predicted data of typical daily load, wind power and photovoltaic, a simulation example was established for the reliability test system of generation and transmission IEEE RTS-96. The problem was solved by the improved generalized Benders decomposition method. Then, the sensitivity analysis method was used to compare and analyze the optimization results. The analysis results showed that the branch power flow overstepping could effectively eliminated when N-1 fault occurred. The security of the transmission network under N-1 state could be ensured. Compared with the method without considering N-1 security constraints, although slightly lower in economy, the maximum capacity of online units and load rate balance safety indicators are significantly improved, which accordingly improves the security of transmission network after energy storage integration. The proposed method can be used to guide energy storage planning with higher security requirements, and is worth to apply in engineering projects. © 2019, Editorial Department of Advanced Engineering Sciences. All right reserved.