Abstract
This paper proposes an optimal generation scheduling approach based on linear relaxation and mixed integer programming, which is used to solve the generation dispatch problem. The quadratic transmission loss constraint of each transmission line is converted into linear constraints by using the linear relaxation and mixed integer programming technique. Consequently, the original optimal generation scheduling problem is formulated as a quadratic programming or mixed integer quadratic programming problem that can be solved by commercial optimization solver. In order to improve the efficiency of algorithm, this paper further analyses the generation scheduling model and deletes the redundant variables and constraints. Three test systems, including IEEE 30-node system, IEEE 118-node system, and Polish 2746-node system, are employed to examine the effectiveness of the proposed method. The comparative results obtained by the proposed method, quadratically constrained quadratic programming method (QCQP), and solving constraint integer programs solver (SCIP) verify the effectiveness of the proposed method in solving the optimal generation scheduling problem.
Highlights
As a major energy consumer, the power industry’s slight improvement in generation scheduling will have a significant impact on the national economy and social environment
With the proportion of renewable energy generation increasing, in order to effectively solve the generation scheduling problem considering network losses, this paper proposes an optimal generation scheduling approach based on linear relaxation and mixed integer programming
The comparative results obtained by the proposed method, quadratically constrained quadratic programming method (QCQP), and solving constraint integer programs solver (SCIP) verify the effectiveness of the proposed method in solving the optimal generation scheduling problem
Summary
As a major energy consumer, the power industry’s slight improvement in generation scheduling will have a significant impact on the national economy and social environment. (1) The first scheduling model is focus on reasonably arrange the power generation of different power plant generators on the premise of satisfied the load demand to achieve the effect of allocating electricity and saving energy and reducing emissions [7], [8], [10] (2) The DC optimal power flow model is a simple and efficient generation scheduling model [12], [13] This model considers the transmission constraints of each line, but the model is based on a lossless network and lacks consideration of transmission loss constraints of each transmission line on the generation scheduling plan. With the proportion of renewable energy generation increasing, in order to effectively solve the generation scheduling problem considering network losses, this paper proposes an optimal generation scheduling approach based on linear relaxation and mixed integer programming. The comparative results obtained by the proposed method, quadratically constrained quadratic programming method (QCQP), and solving constraint integer programs solver (SCIP) verify the effectiveness of the proposed method in solving the optimal generation scheduling problem
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