A Two-Step Methodology for Free Rider Mitigation with an Improved Settlement Algorithm: Regression in CBL Estimation and New Incentive Payment Rule in Residential Demand Response
| Autor: | Dongsik Jang, Eunjung Lee, Jinho Kim |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Control and Optimization
020209 energy media_common.quotation_subject Energy Engineering and Power Technology 02 engineering and technology lcsh:Technology Demand response Peak demand incentive payment rule 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Baseline (configuration management) Engineering (miscellaneous) media_common Consumption (economics) lcsh:T Renewable Energy Sustainability and the Environment business.industry baseline estimation Environmental economics Payment Incentive Free rider problem demand response peak-time rebate free rider customer baseline load regression Business Electricity Energy (miscellaneous) |
| Zdroj: | Energies, Vol 11, Iss 12, p 3417 (2018) Energies Volume 11 Issue 12 |
| ISSN: | 1996-1073 |
| DOI: | 10.3390/en11123417 |
| Popis: | Recent demand response (DR) research efforts have focused on reducing the peak demand, and thereby electricity prices. Load reductions from DR programs can be viewed as equivalent electricity generation by conventional means. Thus, utility companies must pay incentives to customers who reduce their demand accordingly. However, many key variables intrinsic to residential customers are significantly more complicated compared to those of commercial and industrial customers. Thus, residential DR programs are economically difficult to operate, especially because excess incentive settlements can result in free riders, who get incentives without reducing their loads. Improving baseline estimation accuracy is insufficient to solve this problem. To alleviate the free rider problem, we proposed an improved two-step method&mdash estimating the baseline load using regression and implementing a minimum-threshold payment rule. We applied the proposed method to data from residential customers participating in a peak-time rebate program in Korea. It initially suffered from numerous free riders caused by inaccurate baseline estimation. The proposed method mitigated the issue by reducing the number of free riders. The results indicate the possibility of lowering the existing incentive payment. The findings indicate that it is possible to run more stable residential DR programs by mitigating the uncertainty associated with customer electricity consumption. |
| Databáze: | OpenAIRE |
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