Generation of Urban Power Grid Operation Mode Based on Adaptive Discrete Harmony Search Algorithm

To address the complex optimization challenges posed by high-penetration renewable energy integration and diversified load access in New-type Power Systems, this research proposes an Improved Adaptive Discrete Harmony Search Algorithm (IADHS)-based methodology for multi-objective generation of Operation Modes in Urban Power Grids (UPDs). The study initially constructs a multi-objective optimization model targeting minimized network losses, reduced voltage deviations, and diminished load loss under N-1 contingency, while comprehensively considering power flow constraints, voltage limitations, line capacity restrictions, and electromagnetic loop network constraints. To overcome the limitations of conventional algorithms in discrete topology optimization, we innovatively design a dual-harmony memory collaboration mechanism that dynamically partitions the population into elite and ordinary sub-memories, effectively balancing global exploration and local exploitation. A discrete refinement strategy incorporating reversed harmony operations and stochastic mutation is proposed to adapt to optimization requirements across different search phases, complemented by Lévy flight perturbation to enhance solution space traversal capability. Practical case validation demonstrates that the Pareto-optimal solution sets generated by this methodology effectively coordinate multidimensional objectives including economic efficiency, voltage quality, and power supply reliability. This approach provides UPDs with an intelligent planning tool that harmonizes security considerations with economic viability.