Application of Differential Evolution for Congestion Management in Power System

Abstract

In the emerging restructured power system, the congestion management (CM) has become extremely important in order to ensure the security and reliability of the system. This paper proposes an algorithm for congestion management in a pool based electricity market based on differential evolution (DE). The aim of the proposed work is to minimize deviations from preferred transaction schedules and hence the congestion cost. Numerical results on test system namely IEEE 30 Bus System is presented for illustration purpose and the results are compared with Particle swarm optimization (PSO) in terms of solution quality. The comprehensive experimental results prove that the DE is one among the challenging optimization methods which is indeed capable of obtaining higher quality solutions for the proposed problem.

Real-Power Rescheduling of Generators for Congestion Management Using a Novel Satin Bowerbird Optimization Algorithm

“…The effectiveness of the proposed approach was put to the test on various networks, namely, a modified IEEE 30-bus system [9], modified IEEE 57-Bus test system [9], and IEEE 118-Bus test system [22]. The load bus lower and upper voltage were taken as 0.9 p.u.…”

“…From Table 5, it is made clear that overloaded lines are totally relieved by generation rescheduling with the cost of 12,336.05 $/h, which is the lowest when compared with all other optimization algorithms enlisted in [22] such as evolutionary programming algorithm (EP), real coded genetic algorithm (RCGA), particle swarm optimization (PSO), hybrid particle swarm optimization (HPSO), and differential evolution (DE). The loss of the total system before CM is 277.301 MW, and is then decreased to 230.505 MW.…”

An evolutionary algorithm for consumer welfare optimisation of a contingent power network

“…Hence management of dispatch and determination of price of electricity are among important control activities in a power system [1]. One of the major responsibilities of an independent system operator (ISO) in a competitive market environment is to facilitate the complete dispatch of the power that gets contracted among the market players.…”

Review of congestion management methods for distribution networks with high penetration of distributed energy resources

“…How to decide the weights for different customers is not discussed by the authors of [20].  in [21], the up and down regulation prices in the pool based electricity market are used as the weights of the up adjustments (negative) and down adjustments (positive) respectively in the summation of the objective function, where the line losses are not considered. In this way, the congestion costs, i.e.…”