Optimal Scheduling of a Microgrid in a Volatile Electricity Market Environment
Abstract
This study proposes an optimal scheduling strategy for a microgrid participating in a volatile electricity market. The microgrid system includes photovoltaic and wind generators, a load, grid connection, and a battery storage. An optimal microgrid operation is achieved by maximizing the utility function represented by the exponential rate of growth of the electricity's market value through electricity transactions between the microgrid and main grid, on the premise of satisfying the power balance and generation limit of system components. The uncertainties occurring during the microgrid operation are represented by generator output, load demand, and electricity price fluctuation. The proposed strategy utilizes the Kelly Criterion, an optimal strategy that maximizes the growth rate of an asset's net worth over repeated investments, coupled with an artificial neural network time series forecast of electricity price to deal with the volatile energy market. It offers significant improvement in robustness, over the conventional optimization strategies, to uncertainties in system parameters. The effectiveness of the proposed approach, and a comparison with a reactive scheduling as well as dynamic real-time optimization is presented through case studies.
Description
Keywords
Energy, Engineering--Electronics and Electrical, Engineering--System Science, Engineering--Operations Research
Citation
Chen, Y. (2017). Optimal Scheduling of a Microgrid in a Volatile Electricity Market Environment (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/27209