An Enhanced Inherited Crossover GA for the Reliability Constrained UC Problem

This paper solves reliability constrained unit commitment problem (UCP) for a composite power system network using network equivalent technique. Here, the integration of generation and transmission system reliability forms a composite power system model. The inclusion of load forecast uncertainty for the solution of unit commitment problem will give more accurate assessment of spinning reserve (SR). Probabilistic techniques help in setting the reserve requirement which is defined by reliability indices such as loss of load probability (LOLP) and expected energy not supplied (EENS). Reliability network equivalent techniques represent each market player in a power market. The unit commitment problem is solved by a genetic algorithm (GA) resulting in near-optimal unit commitment solutions and the required spinning reserve capacity is effectively scheduled according to the desired reliability level. The proposed enhanced inherited crossover operation in GA will inherit more information from the parent chromosomes thereby it improves the convergence fact and quality of solution. The effectiveness of the proposed technique for UCP is validated on IEEE RTS 24 bus system and a South Indian (Tamilnadu) 86 bus system.