Transmission Congestion Distribution Factors Research Articles

A FIS-GA combined approach for transmission congestion management in restructured power system

A power system under goes frequent changes due to disturbances. If the power system survives after the disturbance it will be operating in a new steady state, in which one or more transmission lines may be over loaded. The over loading of the transmission line can be eliminated by generator rescheduling and/or load shedding. This paper proposes fuzzy inference system (FIS)-based algorithm for overload indication in transmission line. The system parameters such as line overload factor (OF) and transmission congestion distribution factors (TCDFs) are given as the FIS input. The output from the FIS indicates whether the line is overloaded or not. Then generator rescheduling/load shedding is done to relief the congested line. The effectiveness of the congestion clusters method for CM is discussed by formulating two objective functions. Rescheduling of generation is formulated as an optimisation problem with the objective of obtaining minimum cost and proposed objective of achieving minimum real power loss. Attractive features of genetic algorithm (GA) are used for solving the formulated problem with the objectives considered separately. The effectiveness of the proposed approach has been tested for 5 bus system, 30 bus systems in MATLAB environment.

Congestion Management under Hybrid Electricity Market using Self-organizing Hierarchical Particle Swarm Optimization

This paper proposes an optimal congestion management approach under hybrid electricity market using Self organizing hierarchical particle swarm optimization with Time Varying Acceleration Coefficients (SPSO-TVAC). The aim of the proposed work is to minimize deviations from preferred transaction schedules and hence the congestion cost under hybrid electricity market. The values of Transmission Congestion Distribution factors (TCDFs) are used to select redispatch of generators. Generator reactive power support is considered to lower the congestion cost. Numerical results on IEEE 57 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 SPSO-TVAC is one among the challenging optimization methods which is indeed capable of obtaining higher quality solutions for the proposed problem.

Comparative Study of Two Congestion Management Methods for the Restructured Power Systems

Congestion management is one of the most challenging tasks of a system operator to ensure the operation of transmission system within operating limits. In this paper, cluster/zone method and relative electrical distance (RED) method for congestion management are compared based on the considered parameters. In the cluster/zone method, rescheduling of generation is based on user impact on congestion through the use of transmission congestion distribution factors. In the RED method, the desired proportions of generations for the desired overload relieving are obtained. Even after generation rescheduling, if congestion exists, load curtailment option is also introduced. Rescheduling cost, system cost, losses, and voltage stability parameter are also calculated and compared for the above two methods of congestion management. The results are illustrated on sample 6-bus, IEEE 30-bus, and Indian utility 69-bus systems.

A zonal congestion management approach using ac transmission congestion distribution factors

In a deregulated electricity market, one of the major concerns of system operator (SO) is to ensure the free and fair electricity trading while maintaining system security and stability in meeting the pool and contract demands. Achieving a commercially transparent and technically feasible solution during transmission congestion, therefore, poses a great challenge to SO. Transmission congestion distribution factors (TCDF) based on sensitivity of ac power flow in the lines due to the unit change in the power injection at the buses have been proposed by which the congestion zones are identifies to reschedule the generators and loads in that zone for the congestion management. A conceptually reasonable and computationally feasible approach for the solution of this problem has been developed and is illustrated on two test systems having both pool and contracts loads.

A Zonal Congestion Management Approach Using Real and Reactive Power Rescheduling

In a deregulated electricity market, it may always not be possible to dispatch all of the contracted power transactions due to congestion of the transmission corridors. System operators try to manage congestion, which otherwise increases the cost of the electricity and also threatens the system security and stability. In this paper, a new zonal/cluster-based congestion management approach has been proposed. The zones have been determined based on lines real and reactive power flow sensitivity indexes also called as real and reactive transmission congestion distribution factors. The generators in the most sensitive zones, with strongest and nonuniform distribution of sensitivity indexes, are identified for rescheduling their real power output for congestion management. In addition, the impact of optimal rescheduling of reactive power output by generators and capacitors in the most sensitive zones has also been studied. The proposed new zonal concept has been tested on 39-bus New England system and a 75-bus Indian system.