OPTIMAL MULTI-PERIOD ELECTRICITY MARKET CLEARING USING LINEAR PROGRAMMING: A SOCIAL WELFARE MAXIMIZATION APPROACH

Abstract: This paper presents an optimal electricity market clearing framework based on linear programming (LP), applied to a real-time, multi-period Indian power exchange market. The system operator maximises social welfare by dispatching five generating units against seven demand entities across six trading periods using IEX 2025–26 average data. The dual variable of the energy-balance constraint directly yields the market clearing price (MCP) for each period. A market price forecasting module based on linear regression, using engineered supply–demand features, is integrated to predict clearing prices without re-solving the optimisation, achieving a mean absolute percentage error (MAPE) of 2.47%. Simulation results confirm that the LP clears the market at prices ranging from 5,900 to 8,500/MWh with a total social welfare of 26.87 Million, and the forecasting module provides economically consistent predictions suitable for realtime operator decision support.

Keywords: electricity market clearing, linear programming, social welfare maximisation, market clearing price, price forecasting, Indian power exchange, IEX, day-ahead market.