This thesis presents optimal operations for three renewable energy storage systems: off-grid photovoltaic (PV) system with batteries, grid-connected PV system with batteries and PV system with electric vehicles. An idea of model predictive control (MPC) is proposed as the operation method to minimize the operation cost in these systems. The objective is to optimize the charge/discharge of batteries and operation of the systems with the prediction information of solar power generation, load consumption and unit electricity price from grid.

As for the off-grid PV system with batteries, MPC operation method is compared with the rule-based control strategy. Experiments are carried out in Nansha, Guangzhou, China and the results are analyzed to prove the creditability of the system...[ Read more ]

This thesis presents optimal operations for three renewable energy storage systems: off-grid photovoltaic (PV) system with batteries, grid-connected PV system with batteries and PV system with electric vehicles. An idea of model predictive control (MPC) is proposed as the operation method to minimize the operation cost in these systems. The objective is to optimize the charge/discharge of batteries and operation of the systems with the prediction information of solar power generation, load consumption and unit electricity price from grid.

As for the off-grid PV system with batteries, MPC operation method is compared with the rule-based control strategy. Experiments are carried out in Nansha, Guangzhou, China and the results are analyzed to prove the creditability of the system model and effectiveness of the optimal operation method. In terms of the grid-connected PV system, simulation results of the optimal operation method show that the system can earn profits for customers compared with off-grid PV system. As the battery in the power storage system is a high investment for customers, electric vehicle is introduced to replace the battery and an optimal charge/discharge method of an electric vehicle is proposed.