信息物理融合的智能空调响应不确定性尖峰折扣电价的动态优化模型及在线控制

发布时间：2018-10-12 07:46

【摘要】：降低尖峰负荷可获得巨大的经济效益,但尖峰出现时间及持续时长具有很大的不确定性。文中依托信息网络建立了一个电网运行信息、电网价格激励信息、用户室内温度喜好设置信息、外部气象信息融合的智能空调响应不确定性尖峰折扣电价的优化融合模型,采用动态优化区间的模型预测控制实现融合模型控制目标,削减其在电网尖峰期用电量,达到保证在用户定义的舒适性范围内,使用户电费支出最小,也即在电网尖峰期用电量最小的目标。采用6层120区的公共楼宇,72小时432时段,5个随机尖峰激励信息的算例表明,该融合模型及控制策略实现了平价及分时电价机制下对随机尖峰折扣电价的完全响应,在保证舒适性条件下,平价机制下电力峰值最大降幅32.7%,平均降幅25.3%;分时电价下最大降幅34.4%,平均降幅26.6%;用户的电费支出在平价机制下可节约19.9%,在分时电价机制下可节约27.6%。验证了该融合模型及控制策略的强响应能力及灵活适应性。
[Abstract]:Great economic benefits can be obtained by reducing peak load, but the time of peak appearance and duration are uncertain. Based on the information network, this paper establishes an optimal fusion model of the intelligent air conditioning response to the uncertainty peak discount price of intelligent air conditioning, which is based on the information of power grid operation, grid price incentive information, user indoor temperature preference information, and external meteorological information fusion. The model predictive control with dynamic optimization interval is adopted to realize the fusion model control goal, to reduce the power consumption during the peak period of the power network, to ensure the minimum electricity cost within the user-defined comfort range. This is the goal of minimum power consumption during the peak period of the power grid. Five examples of random spike excitation information in public buildings with 72 hours and 432 hours in 6 storeys and 120 districts show that the fusion model and control strategy can achieve the full response to the discounted price of random spike under the mechanism of parity and time-sharing price. Under the condition of ensuring comfort, the peak value of electricity can be reduced by 32.7m, the average decrease by 25.3% under the parity mechanism; the biggest drop 34.4 (26.6b) under the time-sharing price; the electricity expenditure of the user can be saved 19.9g under the parity mechanism, and 27.6b under the time-sharing electricity price mechanism. The strong response ability and flexibility of the fusion model and control strategy are verified.
【作者单位】：广西电力系统最优化与节能技术重点实验室(广西大学);
【分类号】：TM73

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