Optimal dispatch of distributed energy resources in microgrids via virtual power plants for grid resiliency and flexibility using homeostatic PSO algorithm

The integration of distributed energy resources (DERs) into microgrids coordinated via virtual power plants (VPPs) offers a promising strategy to enhance grid resiliency and flexibility. However, the stochastic nature of renewable energy sources (RESs) and dynamic load variations pose challenges to optimal DER dispatch, necessitating advanced optimization strategies. This study proposes a homeostatic particle swarm optimization (HPSO) algorithm to optimize DER dispatch within a VPP framework, minimizing operational costs, expected energy not served (EENS), voltage deviation, and power losses. These objectives address economic efficiency, resiliency against disruptions, and flexibility under varying conditions, respectively. Unlike conventional PSO variants that rely on fixed or linearly scheduled parameters, HPSO embeds a biologically inspired homeostatic feedback layer that dynamically regulates the exploration–exploitation trade-off based on real-time population behavior—constituting its core theoretical contribution. The HPSO algorithm incorporates inertia weight control, progress monitoring, adaptive coefficient adjustment, fitness and distance metrics, velocity correction and update, and position update and boundary handling, dynamically adapting to the optimization landscape to achieve robust performance on complex, multimodal problems. A multi-microgrid test system with photovoltaic (PV) systems, wind turbines (WT), battery energy storage systems (BESS), and microturbines (MT) is modeled, incorporating power balance and BESS state of charge (SOC)equality constraints alongside operational limits. Simulation results demonstrate that the proposed HPSO significantly improves EENS, voltage deviation, and active power loss compared to standard PSO, while achieving greater cost reduction under uncertainty scenarios (e.g., RES outages, load spikes). Sensitivity analysis confirms the robustness of the proposed framework across diverse operating conditions. By incorporating resiliency and flexibility metrics into a scalable, real-time optimization model, this study advances VPP-coordinated DER dispatch, offering practical implications for modern power systems. • Proposes a homeostasis-inspired PSO algorithm (HPSO) for DER dispatch optimization. • Introduces unified quantitative indices for grid resilience and flexibility. • Integrates PV, WT, BESS, MT, FC, and EVs via VPPs in multi-microgrid systems. • Achieves zero EENS and 35% lower losses versus conventional PSO under outage scenarios. • Validates HPSO on CEC 2022 and a 41-bus system with real-world operational constraints.