Centralized Stochastic Energy Management Framework of an Aggregator in Active Distribution Network

This paper develops a detailed and sequential procedure for short term operation of an aggregator to minimize the cost of the consumer and risk of the aggregator, which includes day-ahead (DA) and real-time (RT) operation. DA operation has two stages: consumer load scheduling and risk-based energy procurement. Consumer load scheduling implemented over a radial distribution network by a cost minimization objective function which considers electricity price and solar photovoltaic (PV) uncertainty, peak-to-average ratio, and phase unbalance. This model is formulated as a mixed integer nonlinear program. In the second stage, a risk-based energy procurement is formulated. Here, the aggregator has the choice of energy procurement from wholesale market, either in DA market or RT market, to meet the scheduled power. In RT operation, the aggregator takes a decision on share of RT purchases and battery schedules to minimize the cost of scheduled load power deviations. In order to realize this, a rolling window optimization is implemented, which is modeled as a mixed integer problem. The framework is demonstrated with a detailed case study of 15-node radial active distribution network consisting of 420 residential customers.