Holistic planning of a virtual power plant with a nonconvex operational model: A risk-constrained stochastic approach

This paper presents a novel approach for the investment planning of virtual power plant trading energy in an electricity market. The comprises conventional generating units, renewable storage and set flexible demands. In order to maximize its expected profit, has possibility installing new conventional, renewable, units. Such decisions are made under long-term uncertainty associated with future production costs consumption levels demands, market prices, as well short-term variability prices levels. addition, effect generation operation on is precisely characterized by detailed nonconvex formulation. resulting model cast scenario-based two-stage stochastic programming problem wherein conditional value-at-risk used represent risk aversion owner plant. Numerical results from several case studies show that can significantly increase profit expanding assets. Moreover, neglecting operational constraints generally over-investment moderate computational effort required solve instances up 45 candidate assets backs practical applicability proposed approach.