Sustainable Energy Supply Optimization for a Mine in Yazd Province Using Hybrid Renewable Energy Systems

Off-grid and weakly interconnected mining operations are highly energy-intensive and remain heavily dependent on diesel generation, despite the rapidly improving economic viability of renewable energy and battery storage technologies. This paper presents a mixed-integer linear programming (MILP) model, developed in the Pyomo optimization framework, for the simultaneous long-term capacity expansion and hourly operational scheduling of a hybrid photovoltaic-wind-battery-diesel-grid energy system supplying the mine in Yazd Province, Iran. The formulation incorporates discrete equipment sizing, binary investment timing with fixed mobilization costs, diesel generator unit commitment, and battery lifetime modeling through an energy-throughput constraint. Four planning scenarios (business-as-usual, least-cost economic optimum, a ۴۰% decarbonization pathway, and a ۹۵% deep decarbonization pathway) are evaluated over a ۲۰-year horizon. The economic optimum achieves ۸۷% renewable penetration with a net present cost of USD ۱۰۶.۷ million, a ۲۰.۶% reduction from the baseline, while cutting cumulative CO۲ emissions by approximately ۹۰%. A key finding is that the ۴۰% decarbonization scenario is identical to the economic scenario, as the cost-optimal solution already achieves this target. Deep decarbonization (۹۵% reduction) is achieved at nearly the same net present cost (USD ۱۰۶.۹ million) as the economic optimum, in this case, near-zero emissions carry essentially no cost penalty. These results demonstrate that renewable integration in mining is economically superior to continued grid and diesel reliance.

کلیدواژه ها:

hybrid renewable energy systems ، mixed-integer linear programming ، mine electrification ، battery energy storage ، capacity expansion planning ، unit commitment ، Pyomo