Physics

Nonlinear system

Scheduling (production processes)

Risk management

Mathematics

Statistics

Conic section

Mathematical optimization

Linearization

Stochastic programming

Management

Economics

Grid

Geometry

CVAR

Computer science

Flexibility (engineering)

Quantum mechanics

Applied mathematics

Controllability

Expected shortfall

IEEE Transactions on Sustainable Energy

This paper proposes a risk-averse time-series joint scheduling method to release inherent benefits for improvements on operational cost, voltage profile and risk control, through flexibility extraction from grid-storage-demand resources in active distribution networks (ADNs). In particular, a flexibility analytical framework is developed to fully harness the controllability of various resources in both spatial and temporal scales, and is available for future analysis. The expected operational cost and the risks imposed by uncertainties are simultaneously addressed via conditional value at risk while satisfying physical and operating constraints, in which a sample weighted average approximation (SWAA) technique is employed for approximating the faced uncertainties. The SWAA-based stochastic scheduling problem is further transformed into a second-order cone programming problem via linearization and conic relaxation. Numerical simulations on 33-bus and 123-bus test systems verify the effectiveness of the proposed method.

Flexibility Provisions in Active Distribution Networks With Uncertainties