Energy System State Optimization Control Based on Cyber-physical Fusion

The output power of renewable generation units fluctuates sensitively with climate change as well as other environmental factors. Various types of energy loads change with the need of users. And energy exchange between electrical power and other types of power units such as thermal, cold, or gas is mostly conducted by the fluctuation of the spot price of electricity. It is necessary to take into account the balance of electrical power generation and its consumption while making sure to keep the balance of supply and demand of multi-type energy production units and consumption units. So, the whole process of state transition of each energy unit must be analyzed mathematically in the model, so as to lead the state trajectory of all energy units to the stable domain all the time. Starting from the real-time state of each energy unit, the state transition path and the path decision process, this paper establishes a model for the whole state control process of the cyber-physical energy system considering the operating cost and the constraints of state variables. The Particle Swarm algorithm is chosen to solve the model and find out the best control strategy. The simulation example shows that the optimal control strategy can maintain the balance of supply and demand of electrical power and other types of energy in the energy system. It can accurately control the state trajectory of cogeneration units, gas boilers and batteries with any control cycle at any time, with the realization of the optimal economic dispatch for the entire energy system.