Minimizing Electricity Cost in Multi-Electricity-Market Environment

Since the energy consumption has been increasing, the proportion of nuclear power, wind power and photovoltaic power generation has been on the rise. The study of energy Internet has been an active area of research. As an important part of the energy Internet, the intelligent energy management system has also received great attention. This paper make a study of minimizing the cost of electricity on the user side by utilizing the energy management algorithm in the energy Internet. In considering how to reduce users' cost, most studies focus on reducing the power consumption or reduce their electricity expenditures by responding to real-time prices, electricity can only be bought from the grid in these models, but users can sell excess electricity to the grid in the energy Internet model. This paper studies the problem of minimizing the total electricity cost while guaranteeing quality of service geared to the randomness of device access and time diversity of electricity price. We model the problem as a typical large-scale linear mixed-integer programming model and propose an efficient solution method. We show through simulation that the proposed algorithm can minimize the average charging payment of users and control the electricity trading volume.