Distributed Combined Emission-Economic Dispatch via Coalitional Integration of Wind Turbines

Intermittent and fluctuating renewable energy sources are increasingly becoming integral parts of modern electric power grids. The increasing reliance on renewable energy resources and usage of large-scale distributed generators to replace existing traditional turbines are motivated by the goals of reducing greenhouse gas emissions into the environment and the nation's energy dependency to address the shortage of fossil fuels. However, the intermittent nature of wind energy resources tends to make stability problems more challenging with the continuous mismatch between supply and demand. These challenges have engendered a necessity for the development of effective strategies/algorithms that can enable the resilient operation of power systems. This paper utilizes the concept of cooperative game theory (i.e., Shapley Value) to develop a new strategy for incorporating wind energy cost and transmission line loss in combined emission economic dispatch. The main goals are to integrate distributed wind sources while efficiently trading power, sensibly reduce the use of traditional sources, optimal dispatch generators, and increase spinning reserves to allow more flexible management of system stability issues. The optimization problem is solved hourly for different scenarios of wind energy, demand and traditional sources with three wind farms while maintaining system generation constraints, voltage constraints, area reserve, and ramp rate constraints. The Shapley-value-based algorithm is used for fair distribution of the utility among the coalition members. The proposed model is successfully validated using the IEEE 39 bus system. The developed algorithm is able to accommodate variable wind, and reduce the total cost and real power losses of the system.