Primal–dual interior-point algorithm for electricity cost minimization in a prosumer-based smart grid environment: A convex optimization approach

Abstract

This study proposes a primal–dual interior-point algorithm, which is used by the prosumers to efficiently manage the operation of their generating and consuming devices, to maximize their own profits while contributing to the stability of the overall electricity grid. The energy management problem investigated in this study is formulated as a convex optimization problem and the primal–dual interior-point algorithm is leveraged to acquire the optimal solution which minimizes the energy cost for prosumers in a smart grid environment. The proposed algorithm considers the cost of energy generation by each available device or the charge of a utility company, as well as the predicted consumption and production levels of the facility, and develops an operating plan that maximizes the prosumer’s profitability. The cost function for energy generation is convex, as are the constraints that must be satisfied. The primal–dual interior-point algorithm is an efficient algorithm and has attracted attention in the optimization community. The proposed algorithm is evaluated on three prosumer profiles that have different generation and storage characteristics. A variable pricing structure for power supplied or bought by the utility company is considered in this study and a scenario in which prosumers are not allowed to sell to the utility company. It is evident from the simulation results of the MATLAB environment that scenario 1 generates the minimum cost operation profiles compared to scenario 2. The effectiveness and the robustness of the proposed algorithm are demonstrated in the optimal solution obtained in solving the energy management problem.