A Bilevel Stochastic Programming Approach for Retailer Futures Market Trading

By Miguel Carrión, J. M. Arroyo, Antonio J. Conejo. IEEE Transactions on Power Systems, 2009

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Local flexibility markets: Literature review on concepts, models and clearing methods (2020, methodology): “A bi-level stochastic programming method was proposed in [177] for a retailer trading market.”
Risk-Constrained Profit Maximization for Microgrid Aggregators With Demand Response (2015, background): “Indeed, CVaR is a wellknown risk measure that has been widely used in various energy management problems for different entities in the electricity market such as retailers [26]–[28], producers [29]– [32], distribution companies [33], energy customers [34], and in generation operation planning [35], ”
Energy-Sharing Model With Price-Based Demand Response for Microgrids of Peer-to-Peer Prosumers (2017, methodology): “For instance, a bi-level stochastic programming was proposed for the retailer to decide the prices that are offered to its potential end users [16].”
Two-stage stochastic bilevel programming over a transportation network (2013, background): “Carrion et al. (2009) present an SBP where a retailer optimizes its medium-term revenue at a given risk level, assuming that pool prices, demand, and competitor Savard). prices are random.”
A bilevel model for electricity retailers' participation in a demand response market environment (2013, methodology): “Using the same approach as in Carrión et al. (2009), we show that this problem allows for an exact linearisation of these terms.”