KEYWORDS: Power consumption, Power grids, Data modeling, Tunable filters, Switching, Reflection, Linear filtering, Autoregressive models, Algorithm development, Windows
The delegate power purchase mechanism in China’s electricity retail reform requires power grid companies to make accurate user load forecasting and reasonable market decisions, and the result will affect the user’s electricity price. Under this background, a monthly load forecasting method is studied for power grid company considering the impact of customer churn on the agency electricity consumption. Firstly, a customer churn model based on life cycle theory is proposed to predict the customer churn rate of a power grid company in a specific period of the development process of China’s electricity retail reform. The seasonal and trend decomposition algorithm for decomposing user monthly electricity consumption series is presented, based on which the trend, seasonal, and remainder components of user load are predicted respectively by using polynomial curve fitting methods. Then, the monthly load forecasting model for agent users is proposed according to the expected customer churn rate and the prediction of different load components. A simple electricity market is served for demonstrating the proposed method, and the simulation results show that the proposed method has higher accuracy of monthly load forecasting than the other model that does not consider the predicted customer churn rate of power grid companies.
Power usage quota transaction is a process of reallocation of user power usage quota through the market on the basis of orderly electricity utilization. It is an effective power supply mechanism to deal with the extreme power shortage in China’s power market. However, the traditional centralized power usage quota transaction based on user quotation does not consider user energy efficiency and environmental benefits. Therefore, a centralized power usage quota transaction mechanism is proposed in this work considering the energy efficiency priority of users. Firstly, based on the industry energy efficiency target- and benchmark level specified by the government, user energy efficiency priority index is proposed to correct the bid and offer of market players. Then, a market clearing model of power usage quota transaction is constructed based on user corrected quotation, and an optimal bidding model for power usage quota buyer under the proposed mechanism is also proposed. The power usage quota transaction simulation is carried out for users with different energy efficiency. The results show that the proposed centralized trading mechanism can adjust the trading order according to the energy efficiency of users, so as to promote transaction which is more conducive to energy consumption control and environmental benefits.
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