本文選題：空調(diào) + 負荷聚合商　； 參考：《工程科學與技術(shù)》2017年S1期

【摘要】：目前,空調(diào)負荷參與電網(wǎng)需求側(cè)管理時,負荷運行特性均按照定頻空調(diào)處理,但定頻空調(diào)在溫度調(diào)節(jié)中即相同的溫度間隔下溫度區(qū)間不同時,運行狀態(tài)數(shù)會發(fā)生變化。為解決此問題,本文研究了空調(diào)負荷群的分類方法,并提出空調(diào)負荷群參與電網(wǎng)調(diào)節(jié)的優(yōu)化調(diào)度策略。針對定頻空調(diào)采用設(shè)定溫度控制和直接啟停控制相結(jié)合的策略,有效地解決了在溫度調(diào)節(jié)過程中由于運行狀態(tài)數(shù)變化所引起的負荷波動問題。對于變頻空調(diào)根據(jù)其運行特性分別建立了穩(wěn)態(tài)、動態(tài)負荷模型,參與用戶側(cè)需求響應。基于定、變頻空調(diào)的負荷模型,建立空調(diào)負荷群優(yōu)化調(diào)度模型,并采用離散粒子群算法對其進行仿真分析。當參與調(diào)控的空調(diào)負荷為定值時,分別對同一削減目標下不同的調(diào)控時長、同一調(diào)控時長下的不同削減量兩類情況下的5種調(diào)控策略進行仿真驗證。結(jié)果表明:在同一削減目標下,調(diào)控標準偏差隨著調(diào)控時段數(shù)的增加而不斷增大;在同一調(diào)控時長下,調(diào)控標準偏差隨著削減目標的增加也不斷增大;在以上兩類情況下其調(diào)控的標準偏差與削減目標的比值均小于3%,從而可以得出在同一削減目標或調(diào)控時長下,空調(diào)負荷群的最大可節(jié)約電能。因此,在一定的調(diào)節(jié)范圍內(nèi),空調(diào)負荷作為需求側(cè)資源可以有效擬合調(diào)控目標,進而負荷聚合商可利用空調(diào)負荷的調(diào)節(jié)能力制定合理的削減目標和削減時段,改善電網(wǎng)負荷的峰谷特性。
[Abstract]:At present, when air conditioning load takes part in the demand side management of power grid, load operation characteristics are treated according to fixed frequency air conditioning, but the temperature range of fixed frequency air conditioning is different under the same temperature interval, and the number of operating states will change. In order to solve this problem, this paper studies the classification method of air conditioning load group, and puts forward the optimal dispatching strategy for air conditioning load group to participate in power grid regulation. Aiming at the fixed frequency air conditioning system, the load fluctuation caused by the change of the number of operating states in the process of temperature regulation is effectively solved by combining the strategy of setting temperature control with direct start and stop control. The steady and dynamic load models are established according to the operating characteristics of variable frequency air conditioners to participate in the user side demand response. Based on the load model of fixed frequency and variable frequency air conditioning, the optimal scheduling model of air conditioning load group is established, and the discrete particle swarm optimization algorithm is used to simulate the model. When the load of air conditioning involved in the control is fixed, the simulation results show that the five control strategies are different under the same reduction target and two kinds of reduction under the same control time. The results show that the regulatory standard deviation increases with the increase of the number of control periods under the same reduction target, and increases with the increase of the reduction target at the same time. In the above two cases, the ratio of the standard deviation to the reduction target is less than 3, so it can be concluded that under the same reduction target or the control time, the maximum energy saving of the air conditioning load group can be obtained. Therefore, in a certain range of regulation, air conditioning load, as a demand side resource, can effectively fit the control objectives, and then load aggregators can make use of the capacity of air conditioning load adjustment to formulate reasonable reduction targets and time periods. To improve the peak and valley characteristics of power grid load.
【作者單位】： 四川大學電氣信息學院;
【基金】：四川省科技廳項目資助(2016GZ0143)
【分類號】：TM73

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本文編號：1940397