Congestion Management Based on Optimal Rescheduling of Generators and Load Demands Using Swarm Intelligent Techniques

Surender Reddy Salkuti

Congestion Management Based on Optimal Rescheduling of Generators and Load Demands Using Swarm Intelligent Techniques

Číslo: 5/2017
Periodikum: Advances in Electrical and Electronic Engineering
DOI: 10.15598/aeee.v15i5.2258

Klíčová slova: Congestion management; demand response offers; Generation rescheduling; Meta-heuristic algorithms; Swarm intelligent algorithms, Řízení přetížení; poptávky po nabídce; Generování splátkového kalendáře; Meta-heuristické algoritmy; Inteligentní algoritmy rojů.

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Anotace: This paper presents the Congestion Management (CM) methodologies and how they get modified in the new competitive framework of electricity power markets. When the load on the system is increased or when some contingency occurs in the system, some of the lines may become overloaded. Thus, the loadability of the system should be increased by generating and dispatching the power optimally for the secure operation of power system. In this paper, the CM problem is solved by using the optimal rescheduling of generating units and load demands, and the Swarm intelligent techniques are used to handle this problem. Here, the CM problem is solved by using the Particle Swarm Optimization (PSO), Fitness Distance Ratio PSO (FDR-PSO) and Fuzzy Adaptive-PSO (FA-PSO). First, the generating units are selected based on sensitivity to the over-loaded transmission line, and then these generators are rescheduled to remove the congestion in the transmission line. This paper also utilizes the demand response offers to solve the CM problem. The effectiveness of the proposed CM methodology is examined on the IEEE 30 bus and Indian 75 bus test systems.