Decision-focused Conservation Voltage Reduction to Consider the Cascading Impact of Forecast Errors
Qintao Du, Ran Li, Weiyi Lv, Huan Zhou, Moduo Yu, Jianzhe Liu

TL;DR
This paper introduces a decision-focused forecasting framework for multi-stage voltage control that accounts for forecast errors' cascading impacts, improving energy savings and operational safety in CVR.
Contribution
It proposes a bi-level multi-timescale forecasting approach integrated with VVC optimization, enhancing decision accuracy over traditional methods.
Findings
Energy savings increase from 1.50% to 3.41% with more fast-acting devices.
The proposed method outperforms conventional MSE-based approaches.
Numerical results validate improved operational safety and efficiency.
Abstract
Conservation Voltage Reduction (CVR) relies on the effective coordination of slow-acting devices, such as OLTCs and CBs, and fast-acting devices, such as SVGs and PV inverters, typically implemented through a hierarchical multi-stage Volt-Var Control (VVC) spanning day-ahead scheduling, intra-day dispatch, and real-time control. However, existing sequential methods fail to account for the cas-cading impact of forecast errors on multi-stage decision-making. This oversight results in suboptimal day-ahead schedules for OLTCs and CBs that hinder the ef-fective coordination with fast-acting SVGs and inverters, inevitably driving a trade-off between real-time voltage security and CVR efficiency. To improve the Pareto front of this trade-off, this paper proposes a novel bi-level multi-timescale forecasting (Bi-MTF) framework for multi-stage VVC optimization. By integrating the downstream…
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