Stochastic Optimization of an Active Network Management Scheme for a DER-Rich Distribution Network Comprising Various Aggregators

With large-scale acceptance of solar and wind energy generation into electric grids, large energy storage is expected to provide sufficient flexibility for the safe, stable and economic operation of power systems under uncertainty. Active Network Management (ANM) allows this to happen without having to enlarge the system. This paper presents an ANM-based cost minimization and curtailment model for day-ahead operational planning of active distribution systems. Electric Vehicles (EVs) are managed by EV Aggregators for profit purposes under different parking characteristics in the Vehicle-to-grid mode. A pricing mechanism that defines interaction between the Distribution System Operator (DSO) and EV Aggregators is proposed. Uncertainty terms involve the wind power outputs, solar power outputs and the power demand. The stochastic optimization model created 27 scenarios and solved the minimization problem which involves the grid supply point power, the non-firm power and the aggregator power. This is applied to IEEE-33 bus system and implemented in AIMMS. Results show how the impact of various aggregators' availability profiles help to reduce network operating cost and curtailment of non-firm DGs and improve voltage profiles.