Demand Response Minimizing the Impact on the Consumers' Utility Towards Renewable Energy

The demand for electric energy of captive power plants of electrolytic aluminum enterprises is very huge. Under the guidance of price signals, this type of captive power plant has a certain amount of schedulable power load and power generation resources. Aiming at the response of generation and consumption of electrolytic aluminum captive power plants under the time-of-use electricity price, a directed flow chart model of electrolytic aluminum enterprises is established. Further considering the constraints of various load production relations, an integrated mixed integer nonlinear programming model for power generation and consumption of electrolytic aluminum captive power plants is built, solved by the GUROBI software package in MATLAB. The results of the case study show that different pool purchase prices have different effects on the adjustment of the electrolytic aluminum enterprise’s power generation and transferable load adjustment. To obtain the maximum economic benefit, the enterprise must rationally optimize the unit output and adjust the transferable load to reduce the production cost of the electrolytic aluminum enterprise.

Combined optimization of Production Power Consumption and Power Generation of its Own Power Plant in Electrolytic Aluminum Enterprises Based on Price Signal

With the rapid development of intelligent electrical technologies and power demand response (DR), the power consumption scale of industrial users has expanded dramatically. Aiming at satisfying the diverse demands of industrial customers, the paper proposes three typical power optimization schemes for industrial users, which are all based on improved genetic algorithm (GA). Firstly, representative industrial load types and their corresponding demand response modes are put forward. Secondly, according to the respective demands of industrial users, a variety of power consumption models under time-of-use pricing are constructed and solved by improved genetic algorithm. Finally, the power optimization schemes proposed in the paper are verified by Matlab simulations. The results indicate that schemes designed by improved GA significantly outperform traditional GA schemes in terms of satisfying the industrial power demands over economy, efficiency and accuracy separately.

Yichen Xu

Papers

Power Optimization Strategy for Typical Industrial Users under the Condition of Time-of-use Pricing