Electric companies, electricity industry stakeholders, and regulators are placing an increasing emphasis on accurately representing distributed energy resources in electric company resource planning efforts. While there is substantial literature on the qualitative advantages and disadvantages of distributed energy resource modeling methods, there has been little research that quantitatively assesses implications across methods. This study follows a prior study on energy efficiency to quantitatively demonstrate the impact of approaches to representing demand response (DR), another distributed energy resource, in electric company resource planning models on planning results.
Two approaches to improving the representation of DR in integrated resource planning (IRP) modeling are evaluated: (1) a method of accounting for the relationship between incentive payments and enrollment in DR programs, allowing the IRP model to identify the incentive payment that maximizes cost-effective enrollment and system benefits; and (2) an approach to quantifying the “investment flexibility value” of DR, which refers to the ability to ramp investment in DR up or down in response to deviations from the resource planning load forecast. The robustness of the findings to various modeling assumptions for both methods is tested through sensitivity analysis.
A comparison of key planning results, such as DR investment costs and total system costs, has shown that accounting for the relationship between DR incentive payments and costs can lead to greater DR investment and an associated net reduction in system costs. Quantifying the investment flexibility value of DR may support adjustments to the assumed costs or benefits of DR in IRP modeling, though that will depend in part on expectations around whether future load is more likely to grow at a rate that is faster or slower than the planning load forecast.