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This paper proposes a Wind-Photovoltaic-Thermal Energy Storage hybrid power system with an electric heater. The proposed system consists of wind subsystem, photovoltaic subsystem, electric heater, thermal energy storage and steam turbine unit. The electric heater is used to convert the redundant electricity from wind or photovoltaic subsystem into heat, which is stored in thermal energy storage. When the system output is less than the load demand, thermal energy storage system releases heat to generate electricity. In this paper, the optimal objective is to minimize the levelized cost of energy and maximize the utilization rates of renewable energy and transmission channel. The fitness function is compiled according to the scheduling strategy, and the capacity optimization problem is solved by particle swarm optimization algorithm in MATLAB. The case analysis show that the proposed system can effectively increase the utilization rate of renewable energy and transmission channel.

With the rapid development of the global economy, there is a sharp shortage of fossil energy sources. Therefore the development of renewable energy technologies such as wind power and solar power has become a hot issue nowadays. However, due to the randomness, intermittency and instability of renewable energy, it is difficult to provide continuous and stable electricity when it runs independently. Hybrid renewable power systems with energy storage can improve the reliability of power supply. Capacity optimization is the key of hybrid renewable power system design and the basis of optimal scheduling. In this paper, the capacity optimization of hybrid renewable power system with energy storage is summarized and classified. According to the different energy storage modes of the hybrid renewable power systems, the capacity optimization models, optimization methods and the software used are introduced.

In this paper, considering the uncertainty of electricity price and the uncertainty of wind power generation and photovoltaic power generation in the day ahead electricity market, a bidding decision-making model of wind solar energy storage complementary power system composed of wind turbine, photovoltaic generator set and energy storage system is constructed by using two-stage stochastic programming method, so as to maximize the interests of system operators. Finally, the rationality of the model is proved by an example.

Based on the daily and monthly characteristics of wind power and photovoltaic output, the wind power / photovoltaic sequence model based on the daily and monthly characteristics is constructed. Considering the generation constraints, energy storage constraints, system power balance constraints and renewable energy consumption rate constraints of each unit, the coordinated optimization planning model of wind photovoltaic storage complementary power system capacity is constructed to determine the different renewable energy consumption rate fields The optimal capacity of wind power, photovoltaic and energy storage. The results show that the optimal installed capacity of wind power, photovoltaic power and energy storage is different under different scenarios of renewable energy consumption rate and tie line utilization rate, but the impact of energy storage capacity is small.