Congestion management with distributed generation and its impact on electricity market
Congestion management became more complicated with the increase of complexity in the system. The complexity arose due to restructuring of the utilities alongside the penetration of alternative sources of energy. This paper presents a sensitivity method for allocating distributed generators (DGs) considering congestion relief and voltage security simultaneously. The sensitivities of the overloaded lines with respect to bus injections are considered for ranking the load buses. The new generation capacities for DGs connected at these load buses are then computed by genetic algorithm (GA) with an objective of enhancing the system performance by reducing the system losses and maintaining the voltage profile of the various buses nearest to its nominal value. The N-1 contingency criterion has been taken into account in this work. The expected cost consists of operating cost under normal and contingency states along with their related probabilities to occur. Maximizing social welfare is the objective for normal state while minimizing compensations for generations re-scheduling and load side operation as well as in case of contingency also. Though installation cost of DGs is required, they are useful as cost effective, which can reduce in fact the annual costs for generations re-scheduling and load shedding. It has been shown that the method can assist the ISO to remove the overload from lines in both normal and contingency conditions in an optimal manner. The improvement is measured in terms of available transfer capability (ATC), congestion cost and reliability risk indices of Loss of Load Expectation (LOLE) have also been studied.
congestion distributed generation genetic algorithm sensitivity factor impact analysis