As wind and photovoltaic deployment in industrial parks approaches practical upper bounds, the central planning issue shifts from simply expanding renewable-electricity capacity to identifying where the remaining decarbonisation leverage exists. This study addresses this later-stage planning problem by developing a representative-day bi-objective planning model for an industrial park electricity-heat system integrating wind power, photovoltaic generation, geothermal heat utilisation, thermal energy storage (TES), battery storage, and bidirectional grid interaction, and solves it using multi-objective particle swarm optimisation. The results show that wind and photovoltaic capacities remain close to their feasible upper bounds across representative Pareto solutions, whereas the main structural variation occurs in geothermal deployment and thermal storage. From the carbon-oriented end to the economy-oriented end of the frontier, annualised capital expenditure (CAPEX) decreases from (2691.10 to 977.75) · 10 4 RMB, while carbon reduction decreases from (24.808 to 21.294) · 10 4 t CO₂ (t = tonne = 10 6 g = Mg = 10 3 kg) and the heat deficit ratio increases from 8.50 % to 36.46 %. The representative middle-frontier solution achieves a more balanced outcome, with an economic-efficiency index of 15.212, carbon reduction of 23.090 · 10 4 t CO₂ , and a heat deficit ratio of 6.40 %. Winter representative-day operation shows that TES provides 48.8 % of heat demand, whereas medium- and high-temperature geothermal heat contribute 33.9 % and 10.7 % respectively; by contrast, geothermal electricity remains negligible. Additional heat-adequacy screening and TES cost-sensitivity analyses support the same interpretation. These results indicate that, once electricity-side renewable deployment is high, the main planning lever for balancing investment burden, decarbonisation performance, and heat-service adequacy shifts toward coordinated heat-side design in industrial parks.
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Liu et al. (2026) studied this question.
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