Energy Management Strategy And Power Coordination Control For A Standalone PV/wind/battery Hybrid Energy System

This paper presents a standalone PV/wind/battery hybrid energy system for power supply in remote areas. Aiming at the standalone feature and multiple operating modes of the hybrid system, the researches mainly focus on the energy management strategy(EMS) in upper level and the power tracking control in lower level, to improve the power quality and reliability and keep power balance.Firstly, this paper presents a particle swarm optimization(PSO) algorithm-based EMS to realize the optimal power distribution for the hybrid system. The EMS can optimally compute the power references via PSO algorithm for PV system, wind system and battery according to the weather conditions and load requirement. Simultaneously, it can restrict battery state of charge(So C) within reasonable limits and reduce battery charging and discharging frequency.Secondly, power tracking controllers are designed for PV system and wind system respectively. The power tracking control of PV system is realized by a switching controller which consists of a maximum power point tracking(MPPT) controller based on perturb and observe(P&O) algorithm and a given power tracking(GPT) controller based on PI control method. The MPPT control and GPT co ntrol of PV system can be switched by the switching signal. The power tracking control of wind system is realized by the model predictive control(MPC) method. Also the MPC controller can realize the MPPT control and GPT control. In order to satisfy the fast sample requirement of wind system, the pre-feedback control for reducing the computational burden and a continuation/GMRES method for fast computation are adopted to solve the MPC optimization problem.Finally, the performance of PSO-based EMS and power tracking controllers are verified in MATLAB/Simulink. In order to verify the performance of PSO-based EMS, the simulation results under PSO-based EMS are compared with the results under rule-based EMS at different working conditions. In order to verify the performance of the switching controller and MPC controller, the dynamic and steady performance of PV system and wind system are analyzed respectively.