Study on economic dispatching of wind power consumption considering dynamic game time-of-use price

Abstract

Abstract. In the view of the anti-peaking characteristics of wind power, the electric power companies and the users were selected as the object to study and formulate reasonable demand side hourly price mechanism and the demand response model was established based on dynamic game time-of-use price. Proposed model combined with the scheduling optimization of wind power, thermal power and demand response of the three kinds of power generation resources to improve absorptive capacity of wind power and reduce the cost of the system scheduling, and the model mentioned above was solved by an improved particle swarm algorithm in which the simulated annealing theory was introduced. Simulation results showed that compared with the scheduling optimization model under fixed time-of-use electricity price, the model adopted in this paper could effectively reduce the amount of abandoned wind, enhance the running level of the unit and the economy of the system, and prove the effectiveness of the model.

Data‐driven‐based dynamic pricing method for sharing rooftop photovoltaic energy in a single apartment building

“…In this paper, 5000 samples of electricity prices and load demands are used for training and testing the NN. The electricity price samples are generated according to the historical data [41]. Then the collected electricity price data is fed into the lower‐level energy sharing models (3) and (4) to obtain the optimal load demand.…”