Minimizing The Expected Energy Deficiency of A Distributed Generation System Using Dynamic Optimal Power Management

The tradeoff between cost and reliability increases the challenge to achieve cost-effective and highly reliable power routing in a microgrid power system. Moreover, the presence of energy storage system that requires smart management and the intermittency of renewable energy resources adds additional complexity. The work proposed in this paper deals with these problems and has three major goals that aim to efficiently manage the power flow in a microgrid power system. The first goal is to use optimal short-term power flow planning to optimize the power flow routing between different power sources supplying variable loads. The second goal is to enhance the reliability of the microgrid by minimizing the expected energy deficiency (EED) under both steady state and transient conditions. The third goal is to employ the energy redundancy concept as a tool to dynamically schedule the battery state of charge (SOC) limits, which, in turn, increase the battery age and enables the system to utilize the SOC minimum level as a reserve margin to enhance the transient stability by maintaining maximum stipulated energy deficiency level. Short term forecasting of the demand, the generation, and the variable grid tariff is considered in this optimization, as well as, employing the energy index of reliability (EIR) as a measure of the deficiency level of the system. Two different cases; namely, a grid connected and autonomous microgrid operations are considered to show the effectiveness of the proposed algorithm. Particle swarm optimization (PSO) is used as power flow optimizer. The simulations are carried out using MATLAB/SIMULINK platform to achieve the optimal power sharing.