Grid-Specific Co-Optimization of Incentive for Generation Planning in Power Systems With Renewable Energy Sources

Enhancement in efficiency of renewable energy sources, raised concern about greenhouse gas emission, significant power losses within transmission and distribution networks, unpredictable and unreliable fossil fuel cost, and expansion of reliable communication infrastructure offered by smart grids have all contributed to an increasing interest in deployment of renewable energy sources in energy mix. However, the widespread utilization of renewable energy sources in an open energy market without proper grid-based incentives for aimed contribution levels is uncertain. This article proposes a co-optimization algorithm to find the minimum incentives that result in the desired level of renewable energy source penetration in energy supply chain and optimal distribution of power sources in the electric power grid. The algorithm first finds the proper incentive based on the power-flow losses, then it uses a novel optimization approach to solve a mixed integer non-linear programming optimization of generation planning to minimize the energy cost. Unlike other incentive design methodologies, the proposed algorithm is not only supply specific, but also it depends on the demand and the structures of the grid. The method finds an exclusively designed set of incentives for electric energy supplies that do not emit greenhouse gases or heat to the atmosphere.