Bi-Level DG Optimization in Distribution Networks with TOU Pricing and Demand Response Using MPA
Main Article Content
Abstract
This study proposes a bi-level optimization model for the optimal allocation of distributed generation (DG) in active distribution networks, taking into account timeof- use (TOU) electricity pricing and demand response (DR) behavior. The upper level represents the decisionmaking of the distribution system operator (DSO), aiming to minimize power losses, voltage deviations, and DG investment costs. At the lower level, responsive consumers optimize their hourly demand profiles to minimize electricity costs under TOU tariffs, subject to behavioral and operational constraints. To enable tractable computation, the original bi-level structure is reformulated into a single-level nonlinear programming problem through the application of Karush-Kuhn-Tucker (KKT) optimality conditions. The resulting model is highly constrained and non-convex. This makes it suitable for solutions using metaheuristic approaches. In this work, the Marine Predators Algorithm (MPA) is adopted due to its superior global search capability and convergence characteristics. Numerical simulations on the IEEE 33-bus and 69-bus test systems confirm the
effectiveness of the proposed approach in reducing both energy losses and operational costs. The results highlight the practical applicability of the MPA-based framework for intelligent DG planning in smart grids under dynamic
pricing environments.
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