Assessing the Value of Heterogeneous Elasticities for Incentive-Based Residential Demand Response
Incentive-based demand response (IBDR) programs play a crucial role in enhancing grid stability and reducing peak loads in modern power systems. However, existing IBDR programs often rely on aggregate demand models, overlooking the impact of heterogeneous consumer behaviors and appliance-specific de...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11088113/ |
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| Summary: | Incentive-based demand response (IBDR) programs play a crucial role in enhancing grid stability and reducing peak loads in modern power systems. However, existing IBDR programs often rely on aggregate demand models, overlooking the impact of heterogeneous consumer behaviors and appliance-specific demand elasticities. This study assesses the value of incorporating heterogeneous elasticity values in IBDR programs by developing three optimization models with increasing levels of granularity: 1) an aggregate elasticity model, 2) an appliance-specific elasticity model, and 3) a customer and appliance-specific elasticity model. Furthermore, this study incorporates transmission line losses into the models, providing a realistic assessment of distribution system efficiency. Comparative analysis using realistic residential electricity consumption data reveals that integrating appliance-specific elasticity significantly improves economic efficiency, while adding customer-specific granularity yields marginal additional benefits. Comparative analysis using realistic residential electricity consumption data reveals that integrating appliance-specific elasticity improves economic efficiency by 6.29%, while customer-specific granularity yields only a marginal additional benefit of 0.92%. These findings offer valuable insights for load-serving entities (LSEs) and policymakers in designing more efficient IBDR programs. |
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| ISSN: | 2169-3536 |