Bidding in Local Energy Markets Considering Uncertainty from Renewables and Demand

The penetration of distributed energy resources in distribution networks is currently enabling the emergence of local energy markets (LEM). However, considering renewable generation and load demand variability is crucial to realize such transactive energy systems. In this work, we propose a bi-level optimization model for bidding in LEM, considering the uncertainty of renewables and demand. At the upper-level, consumers, prosumers, and producers submit bids in a double-auction LEM to minimize the cost of consumers and maximize the profits of producers considering PV generation and demand variability. The lower-level corresponds to a pool-based LEM that maximizes the energy transactions of players. The problem complexity calls for alternative solutions methods, such as evolutionary computation, to find near-optimal solutions efficiently. Results suggest that the model can account for the uncertainty that may be realized in the day-ahead for load demand and PV generation but at the expense of a higher overall cost.