The transition towards sustainable energy systems requires a paradigm shift from purely economic optimization to a holistic framework that internalizes environmental and social externalities. This article integrates social and environmental aspects into the multi-objective dispatch model based on mixed-integer linear programming (MILP) for the economic, environmental, and social dispatch (EEDS) of a polygeneration microgrid. Unlike traditional approaches that treat social impact as a static planning constraint, this study introduces a quantified “Social Shadow Price” into the operational objective function, aiming to operationalize the concept of energy justice. The model is applied to a case study featuring a high-load factor industrial demand profile, integrated with thermal generation, solar PV, wind power, and BESS storage. Results demonstrate that internalizing environmental and social costs significantly alters the merit order dispatch, reducing the utilization of socially contentious technologies while leveraging storage arbitrage to mitigate intermittency. Furthermore, a sensitivity analysis is conducted to determine the optimal capacity of renewable energy sources, revealing that a balanced mix of solar and wind minimizes the composite sustainability index. The findings suggest that this EEDS framework provides a viable pathway for policymakers to achieve a socially equitable energy transition in industrial sectors.
Chicacausa-Niño et al. (Tue,) studied this question.