Variability of electricity load patterns and its effect on demand response: A critical peak pricing experiment on Korean commercial and industrial customers
| Autor: | Jae Jeung Rho, Dongsik Jang, Jiyong Eom, Min Jae Park |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
business.industry
020209 energy media_common.quotation_subject 02 engineering and technology Management Monitoring Policy and Law Environmental economics Payment Demand response Microeconomics General Energy Incentive Critical peak pricing On demand Dynamic pricing 0202 electrical engineering electronic engineering information engineering Predictive power Business Electricity media_common |
| Zdroj: | Energy Policy. 88:11-26 |
| ISSN: | 0301-4215 |
| DOI: | 10.1016/j.enpol.2015.09.029 |
| Popis: | To the extent that demand response represents an intentional electricity usage adjustment to price changes or incentive payments, consumers who exhibit more-variable load patterns on normal days may be capable of altering their loads more significantly in response to dynamic pricing plans. This study investigates the variation in the pre-enrollment load patterns of Korean commercial and industrial electricity customers and their impact on event-day loads during a critical peak pricing experiment in the winter of 2013. Contrary to conventional approaches to profiling electricity loads, this study proposes a new clustering technique based on variability indices that collectively represent the potential demand–response resource that these customers would supply. Our analysis reveals that variability in pre-enrollment load patterns does indeed have great predictive power for estimating their impact on demand–response loads. Customers in relatively low-variability clusters provided limited or no response, whereas customers in relatively high-variability clusters consistently presented large load impacts, accounting for most of the program-level peak reductions. This study suggests that dynamic pricing programs themselves may not offer adequate motivation for meaningful adjustments in load patterns, particularly for customers in low-variability clusters. |
| Databáze: | OpenAIRE |
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