Abstract
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—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.
Highlights
In demand response (DR) programs, electricity consumers play a significant role in power system operations in terms of reducing their electricity usage during system peak load in response to a time-based rate or incentive payment [1]
June through September in 2017, during which the peak-time rebate (PTR) pilot program was operated from late July to considered the data for all residential customers when we evaluated customer baseline load (CBL) estimation performance; in mid-September
The proposed method consists of two steps, namely, predicting the CBL using regression and implementing a minimum threshold of load for customers to receive incentive settlement
Summary
In demand response (DR) programs, electricity consumers play a significant role in power system operations in terms of reducing their electricity usage during system peak load in response to a time-based rate or incentive payment [1]. DR programs have emerged globally as an interesting approach for accommodating the high penetration of renewable energy sources. Much effort has been made to increase renewable energy uptake to help solve environmental issues, their inherent uncertainties complicate balancing demand against supply. Of the various incentive-based DR programs, this paper focuses exclusively on peak-time rebate (PTR) programs. These programs are normally offered to residential consumers, and they provide
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