Bi‐level planning of distributed energy resources into existing transmission grids: Pathway to sustainable energy systems

This paper presents a novel stochastic planning framework for the integration of renewable distributed energy resources (DERs) into existing power systems without relying on new investments in the transmission networks. The upper‐level problem of the proposed model aims at minimizing the total expected social cost of supplying demand that includes the expected cost of getting energy from conventional generating units and DERs, the congestion cost of transmission networks, and the greenhouse gas (GHG) emission cost, while each of the privately invested DER satisfies a specified rate of return. The lower‐level problem clears the electricity market to find locational marginal prices (LMPs) and operation status of the system. The proposed framework is formulated as a bi‐level optimization problem that is recast as a single‐level problem using the duality technique. The non‐linear terms are then linearized using the “bigM” method and the complementary slackness conditions. The uncertainties in the power production of renewable resources and the future electric loads are captured using the scenario technique in which the copula method is employed for considering the correlation between uncertainties. Finally, the effectiveness and applicability of the proposed method are validated on a 3‐bus test system and the modified IEEE RTS 24‐bus system.