Unit commitment in Virtual Power Plant with estimation of Carbon Emission

Abstract

The Virtual Power Plant system is integration of renewable energy generating sources as a unique power plant to take part in the energy market. The renewable energy sources may be distributed in geographical area but with the concept of Virtual Power Plant (VPP) they can participate in maintaining the balance between the supply and demand. This increases the system reliability, profit, security and efficiently uses the renewable energy resources. For the proper and economic operation of the energy market the participating units should be committed as per operator scheduled. The vital factor is the carbon emission reduction in this environment. This work proposes the integration of unit commitment scheduling of energy market with carbon market. The risk factor to participate in the carbon market is given by Conditional Value-at- risk <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\text{CVaR})$</tex> represented as expected shortfall and the carbon price forecasting with Artificial Neural Network method. The improved particle swarm optimization technique has been proposed for finding the best solution and also compares two different scenarios for carbon price calculations. The proposed methodology is validated with the IEEE-30 bus system.