Abstract
Background/Objectives: In this paper a clear focus on pricing of the GENeration COmpanies (GENCO) has been dealt with. GENCO participate in day-ahead power pool trading to maximize their profit in the energy market. Methods/Statistical Analysis: Since the self-scheduling problem is a highly non-linear, non-convex mixed-integer optimization problem, conventional methods for optimizing may suffer excessive computational burden. This paper incorporates the method for determining the Locational Marginal Pricing with and without congestion due to over load and gives an observation of the ways to overcome this critical situation in the deregulated energy market using Power World Simulator (PWS) software for 3-bus system and IEEE 9-bus system Findings: In the case of Locational Marginal Pricing (LMP) forecasting, the main challenge is to forecast the volatile prices accurately in a day-ahead market. The PWS software used for test cases considered indicates that the output information is obtained at the short time frame which ultimately reduces the computation burden existed earlier in the conventional method Applications: The proposed methodology will be helpful for the generating company to forecast the Locational Marginal Pricing for both with and without congestion due to over load and rescheduling of generators will be carried out accordingly in the deregulated energy market within a very short time frame.
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