Sizing refers to determining the appropriate capacity, dimensions, or specifications of a system, component, or resource to meet specific performance requirements. In energy systems, sizing applies to batteries, solar panels, generators, and other infrastructure to ensure efficiency, reliability, and cost-effectiveness. Proper sizing optimizes performance, prevents over- or under-utilization, and balances factors like demand, storage, and operational constraints in various engineering and industrial applications.
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This paper presents a method to determine optimal energy and power capacity of distributed Energy Storage Systems (ESS) in behind-the-meter applications to maximize local Photovoltaic (PV) utilization or minimize Demand Charge (DC) cost. The problem is solved as a multi-objective optimization model to obtain a set of Pareto optimal solutions for each scenario in each month. An approach is then presented to map the monthly Pareto fronts into a single yearly Pareto front. A cost benefit analysis has also been carried out to show the compromise between PV utilization, DC cost, and ESS cost.
