Optimization and Simulation Based Cost-Benefit Analysis on a Residential Demand Response : Applications to the French and South Korean Demand Response Mechanisms.

Summary Because of the global concern about CO2 emissions, climate change and energy transition, we are paying more attention to electricity demand management. In particular, with electricity load shedding, we can enjoy several benefits, such as increasing the efficiency of the whole electricity market, enhancing the security of electricity supply, and making investment more efficient and desirable as well as benefiting the environment and supporting renewable energy. In Europe, France started the NEBEF mechanism at the end of 2013, and South Korea launched the market-based load shedding program in late 2014. Among a number of issues and assumptions we need to consider in terms of load shedding, estimating the reference curve is one of the most important and fundamental elements. In this research, based on the rescaled consumption profile for an average household, several methods of estimating the reference curve are established and examined for both French and Korean load shedding mechanisms. This investigation on the estimation methods could contribute to the search for a better and more accurate estimation method that will increase the incentives for participants. With the estimated reference curves, cost-benefit analyses were performed, which were used in the decision analysis for the participants. To perform the cost-benefit analyses, a simple mathematical model using linear algebra is created and modified to properly represent the parameters of each of the load shedding mechanisms. This model allows us an intuitive and clear understanding of the mechanisms. This generic model can be used for different countries and sectors, residential, commercial and industrial, with some model modifications. Monte Carlo simulation is used to reflect the stochastic nature of reality, and optimization is also used to represent and understand the rationality of the participants, and to provide microeconomic explanations of the participants' behaviors. In order to derive meaningful implications for a better architecture of the clearing market, several sensitivity analyses are performed on key elements of the model for the mechanisms.