Abstract
This study presents the procurement of electrical energy and operating reserve ancillary services (ORASs) by the simultaneous clearing of the wind integrated power market under the pool-based deregulated environment. This investigation is important due to the intermittent output of wind generators, which is a serious concern for medium and high wind penetration and requirement of high operating reserves for maintaining the security of such systems. The market model is presented for the clearing of energy and ORAS market, where both thermal generators and demand response offers supply the reserves. This model is analysed for energy and spinning reserve (ESR) cost minimisation, emission minimisation, and co-optimisation of ESR cost and emission. The non-dominated sorting multi-objective gravitational search algorithm is employed to obtain Pareto optimal solutions. The efficacy of the presented method is investigated on IEEE 30-bus, IEEE 118-bus, and IEEE 300-bus test systems for different levels of wind uncertainty. The results are compared with multi-objective particle swarm optimisation.
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