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The purpose of load management and energy management in power networks is reducing economic costs and increasing the reliability of the power grid. Achieving this goal is possible in management both the demand and supply side of electric power system. In this article, two methods of forecasting for electricity demand have been presented. Gray Model (GM) and trigonometric gray prediction approach. These two methods are used to forecast total electricity demand of Kerman province for a period of 2012–2031.then electric power supply system of Kerman province for base year 2012 has been modeled using LEAP software. Then the electric power supply system has been developed for the target year 2031 based on two different scenarios, namely, status quo scenario and cooling loads management scenario (CLM). These scenarios have been evaluated in three sections viz. power generation, cost analysis, and environmental emissions. results indicate that, assuming the implementation of CLM scenarios from 2020, capacity requirement of power plants will be reduced up to 1000 MW in comparison with status quo scenario by the year 2031 which results in a significant reduction in the capital costs, operation and maintenance costs, fuel costs, electricity generation, greenhouse gas emissions from fossil fuel consumption in power plants, and peak load of the electric power system by the year 2031. © 2016 American Institute of Chemical Engineers Environ Prog, 35: 1177–1189, 2016