One of the emergent prospects for active distribution networks is to establish new roles to the distribution company (Disco). The Disco can act as an aggregator of the resources existing in the distribution network, also when parts of the network are structured and managed as microgrids (MGs). The new roles of the Disco may open the participation of the Disco as a player trading energy in the wholesale markets, as well as in local energy markets. In this paper, the decision making aspects involving the Disco are addressed by proposing a bi-level optimization approach in which the Disco problem is modeled as the upper-level problem and the MGs problems and day-ahead wholesale market clearing process are modeled as the lower-level problems. To include the uncertainty of renewable energy sources, a risk-based two-stage stochastic problem is formulated, in which the Disco's risk aversion is modeled by using the conditional value at risk. The resulting non-linear bi-level model is transformed into a linear single-level one by applying the Karush-Kuhn-Tucker conditions and the duality theory. The effectiveness of the model is shown in the application to the IEEE 33-bus distribution network connected to the IEEE RTS 24-bus power system.

The operation problem of a micro-grid (MG) in grid-connected mode is an optimization one in which the main objective of the MG operator (MGO) is to minimize the operation cost with optimal scheduling of resources and optimal trading energy with the main grid. The MGO can use incentive-based demand response programs (DRPs) to pay an incentive to the consumers to change their demands in the peak hours. Moreover, the MGO forecasts the output power of renewable energy resources (RERs) and models their uncertainties in its problem. In this paper, the operation problem of an MGO is modeled as a risk-based two-stage stochastic optimization problem. To model the uncertainties of RERs, two-stage stochastic programming is considered and conditional value at risk (CVaR) index is used to manage the MGO’s risk-level. Moreover, the non-linear economic models of incentive-based DRPs are used by the MGO to change the peak load. The numerical studies are done to investigate the effect of incentive-based DRPs on the operation problem of the MGO. Moreover, to show the effect of the risk-averse parameter on MGO decisions, a sensitivity analysis is carried out.