Flattening Energy-Consumption Curves by Monthly Constrained Direct Load Control Contracts
研究提出一种整数随机动态优化模型，利用直接负荷控制合同在高峰时段削减用电，结合“降至阈值”策略平抑能耗曲线，经加州实际数据验证可降低约4%成本，对电力公司优化电网稳定性和成本有参考价值。
California Utility Firm Implements Innovative Model, Reducing Costs by 4% A California utility firm has successfully implemented a pioneering model to balance electricity demand and supply while minimizing costs. By utilizing direct load control contracts (DLCCs), the firm can reduce energy consumption during peak hours. Researchers developed an integer stochastic dynamic optimization problem that considers monthly and annual constraints, allowing for effective execution of DLCCs. Incorporating a “reduce-to-threshold” policy to flatten energy-consumption curves during high demand, the model was verified using real data from the California Independent System Operator. When implemented, the utility firm achieved an impressive cost reduction of approximately 4%. Sensitivity analysis was conducted to enhance customer experience and improve DLCC contract features. The success of this innovative model highlights the potential of DLCCs and advanced optimization techniques in the energy sector, offering a blueprint for other utility companies seeking to optimize grid stability and reduce costs.