جریان برق مطلوب با محدودیت های زیست محیطی با استفاده از الگوریتم برنامه ریزی خطی متوالی سریع: کاربرد برای سیستم قدرت الجزایر

Harmful ecological effects caused by the emission of gaseous pollutants like sulfur dioxide (SO2) and nitrogen oxides (NOx), can be reduced by load adequate distribution between power plants. However, this leads to a noticeable increase in their operating cost. In order to eliminate this conflict, and to study the trade-off relation between fuel cost and emissions, an approach to solve this multiobjective environmental/economic load dispatch problem, based on an efficient successive linear programming technique is proposed. Simulation results on the Algerian 59-bus power system prove the efficiency of this method thus confirming its capacity to solve the environmental/economic power dispatch problem.

The economic load dispatch (ELD) problem is to determine the optimal combination of power outputs of all thermal generating units which minimizes the total fuel cost while satisfying load demand and operational constraints [1]. However, due to strict governmental regulations on environmental protection, the conventional operation at absolute minimum fuel cost can not be the only basis for dispatching electric power. Therefore, it is mandatory for electric utilities to reduce pollution from power plants either by design or by operational strategies. The most important emissions considered in the power generation industry due to their effects on the environment are sulfur dioxide (SO2) and nitrogen oxides (NOx). The emission of these pollutants affects not only human beings, but harms other life forms as well causing damage to materials and global warming. Many researchers have studied the environmental/economic dispatch (EED) problem by considering the emission in the objective function or treating them as additional constraints [2], [3], [4] and [5]. Traditionally, different solution approaches have been developed to solve the EED problem. These methods are nonlinear programming techniques with very high accuracy, but their execution time is very long and they can not be applied to real-time power system operations. Since the introduction of the sequential or successive programming techniques, it has become widely accepted that successive linear programming (SLP) algorithms can be effectively used to solve nonlinear optimization problems [6]. In SLP, the original problem is solved by successively approximating the original problem using Taylor series expansion at the current operating point and then moving in an optimal direction until the solution converges. In this paper, a method based on an efficient successive linear programming technique is presented and tested on the Algerian 59-bus power system. Simulation results confirm the advantage of computation rapidity and solution accuracy of the proposed method. These results show great promise for on-line application.

In this paper, a solution was developed using a successive linear programming algorithm to solve the bi-objective problem of economic and emission dispatch. The results offer a reduced NOx emission output with a marginal increase in fuel cost. The approach was tested on the Algerian 59-bus 10-generator system. The main constraints considered are generation capacity constraints and security constraints. Considering the presented cases, the proposed approach appears to be very efficient in particular for its fast convergence to the optimum and its interesting financial profit with a reduced emission. This method is highly appropriate for on-line applications in power systems.