AI Summary & Key Takeaways
AI InsightThus, it is shown that the PSPA can also be used in the solution of the environmental economic power dispatch problem.
📌 3 Key Takeaways
Abstract
In this study, an environmental economic active power dispatch problem is transformed into an optimization problem with a single-objective function by applying the weighted sum method (WSM) and the conic scalarization method (CSM). A pseudo spot price of electricity algorithm (PSPA) is used to solve the transformed problem. This is demonstrated on an example problem, which is a lossy electrical power system having only thermal units The WSM and CSM methods are applied to the example problem, and the weight factor values of these methods is increased from 0 to 1 by a step size of 0.1. For each possible value of the coefficient, a different total generation cost rate that is to be minimized is obtained, and an optimal solution is also calculated for it (Pareto optimal solutions). Solutions obtained from both methods are not onlycompared with each other, but also compared with other solutions obtained using different methods such as the first order gradient method, the lambda iteration method, nonlinear programming, linear programming, and fuzzy linear programming. In this study, the CSM is used for the first time in the transformation of an environmental economic active power dispatch problem into a single-objective optimization problem. Thus, it is shown that the PSPA can also be used in the solution of the environmental economic power dispatch problem.
Özet
In this study, an environmental economic active power dispatch problem is transformed into an optimization problem with a single-objective function by applying the weighted sum method (WSM) and the conic scalarization method (CSM). A pseudo spot price of electricity algorithm (PSPA) is used to solve the transformed problem. This is demonstrated on an example problem, which is a lossy electrical power system having only thermal units The WSM and CSM methods are applied to the example problem, and the weight factor values of these methods is increased from 0 to 1 by a step size of 0.1. For each possible value of the coefficient, a different total generation cost rate that is to be minimized is obtained, and an optimal solution is also calculated for it (Pareto optimal solutions). Solutions obtained from both methods are not onlycompared with each other, but also compared with other solutions obtained using different methods such as the first order gradient method, the lambda iteration method, nonlinear programming, linear programming, and fuzzy linear programming. In this study, the CSM is used for the first time in the transformation of an environmental economic active power dispatch problem into a single-objective optimization problem. Thus, it is shown that the PSPA can also be used in the solution of the environmental economic power dispatch problem.