| Summary/Abstract |
Peak reduction is an important problem in the context of the electricity grid and has led to conservation programs in various jurisdictions. For example, in Ontario, Canada, residential customers are charged higher prices during peak times, while large industrial and commercial customers pay heavy surcharges that depend on their load during Ontario’s five peak-demand days. Reducing these surcharges is a challenging problem for large consumers due to the difficulty of predicting peak days in advance.
We study the impact of this peak reduction program, called 5 Coincident Peaks (5CP), on consumers by analyzing the difficulty of predicting peak-demand days and peak hours on those days. We find that even the state-of-the art peak-prediction algorithms require consumers to curtail load ten or more times, and even then, they may not identify all five peak-demand days. We also analyze alternative policies that cold help reduce peak demand in Ontario.
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