【摘要】：隨著經(jīng)濟(jì)的發(fā)展,國民經(jīng)濟(jì)水平的提高,夏季空調(diào)負(fù)荷成為很多城市電力負(fù)荷峰谷差不斷增大的主要原因之一,加深了我國夏季高峰時(shí)段的電力供需矛盾。公共樓宇大規(guī)模空調(diào)負(fù)荷具備一定的調(diào)峰能力,因此挖掘公共樓宇大規(guī)�？照{(diào)負(fù)荷的調(diào)峰潛力,并采用合理的調(diào)控手段削減高峰負(fù)荷,對(duì)減緩電網(wǎng)的壓力具有很重要的意義。為解決公共樓宇大規(guī)�？照{(diào)的虛擬調(diào)峰問題,本文主要進(jìn)行了了如下研究：(1)分析了公共樓宇大規(guī)�？照{(diào)負(fù)荷的預(yù)測技術(shù)。準(zhǔn)確的公共樓宇大規(guī)�？照{(diào)負(fù)荷預(yù)測對(duì)于掌握公共樓宇空調(diào)負(fù)荷可調(diào)度容量從而參與電網(wǎng)調(diào)控具有重要意義。提出了一種考慮夏季氣溫積溫效應(yīng)的基于Elman神經(jīng)網(wǎng)絡(luò)預(yù)測模型。將有效積溫、溫度、濕度、五日滑動(dòng)平均溫度作為氣象因素考慮進(jìn)Elman神經(jīng)網(wǎng)絡(luò)預(yù)測模型中,預(yù)測預(yù)測歳的公共樓宇大規(guī)�？照{(diào)負(fù)荷值。(2)研究了公共樓宇大規(guī)�？照{(diào)負(fù)荷參與電網(wǎng)虛擬調(diào)峰的調(diào)度方案的設(shè)計(jì)。公共樓宇大規(guī)模中央空調(diào)參與電網(wǎng)的調(diào)峰,需要充分考慮電網(wǎng)常規(guī)機(jī)組和公共樓宇的特點(diǎn),所以立足于調(diào)度方案的設(shè)計(jì),圍繞框架建立、評(píng)估等方面開展研究。研究分析了公共樓宇大規(guī)模空調(diào)負(fù)荷參與的電網(wǎng)的日前、日內(nèi)、實(shí)時(shí)的調(diào)度的調(diào)度技術(shù)框架,和有第三方負(fù)荷代理機(jī)構(gòu)參與的公共樓宇大規(guī)�？照{(diào)負(fù)荷參與調(diào)度架構(gòu),具體闡述了雙層調(diào)度目標(biāo)及約束條件,提出了公共樓宇大規(guī)�？照{(diào)負(fù)荷參與調(diào)度效果在線評(píng)估指標(biāo)及計(jì)算方法,可為公共樓宇大規(guī)�？照{(diào)負(fù)荷參與調(diào)度優(yōu)化協(xié)調(diào)系統(tǒng)提出參考,最后給出了公共樓宇大規(guī)�？照{(diào)負(fù)荷參與調(diào)度方案的優(yōu)化調(diào)整流程。(3)研究了公共樓大規(guī)�？照{(diào)負(fù)荷虛擬調(diào)峰的策略。首先分析了公共樓宇大規(guī)模中央空調(diào)系統(tǒng)的物理模型構(gòu)成以及主要功能,然后對(duì)中央空調(diào)進(jìn)行物理建模,把中央空調(diào)的功率分為五大主要耗能部分,包含制冷機(jī)組耗能,冷凍水泵耗能,風(fēng)機(jī)盤管耗能,冷卻塔耗能和冷卻水泵的耗能,并對(duì)五大耗能部分主要影響因素進(jìn)行建模分析；然后針對(duì)中央空調(diào)的主要耗能部分的分析得到中央空調(diào)的可優(yōu)化部分,分析了對(duì)公共樓宇大規(guī)模中央空調(diào)進(jìn)行柔性調(diào)控的策略,包括全局的溫度控制、增加冷凍機(jī)水溫、風(fēng)機(jī)盤管的關(guān)閉等,并分析得到了公共樓宇大規(guī)模參與柔性調(diào)控的流程。(4)建立了公共樓宇大規(guī)�？照{(diào)負(fù)荷虛擬調(diào)峰組合優(yōu)化算例。公共樓宇大規(guī)�？照{(diào)組合參與電網(wǎng)日前調(diào)度,不同空調(diào)用戶,根據(jù)自身的實(shí)際特征,可采取的調(diào)控策略不同。首先分析了公共樓宇大規(guī)模空調(diào)柔性調(diào)控組合方案,對(duì)中央空調(diào)典型用戶的空調(diào)負(fù)荷特性進(jìn)行曲線擬合,然后得到典型的中央空調(diào)參與的電網(wǎng)調(diào)控預(yù)設(shè)方案。實(shí)例分析了針對(duì)公共樓宇大規(guī)模中央空調(diào)參與電網(wǎng)日前調(diào)度的雙層優(yōu)化組合方案,采用的CPLEX優(yōu)化軟件包進(jìn)行組合優(yōu)化,得到早高峰、腰高峰和晚高峰的調(diào)控組合方案。
[Abstract]:With the development of economy and the improvement of national economy, air conditioning load in summer becomes one of the main reasons for the increasing peak and valley difference of power load in many cities, which deepens the contradiction between power supply and demand during the peak period of summer in China. The large-scale air conditioning load of public buildings has certain peak-shaving ability, so it is of great significance to excavate the peak-shaving potential of large-scale air-conditioner load of public buildings and to reduce the peak load by adopting reasonable control measures, which is of great significance to reduce the pressure of power grid. In order to solve the problem of virtual peak-shaving of large-scale air conditioning in public buildings, this paper has mainly carried out the following research: (1) the forecasting technology of large-scale air conditioning load in public buildings is analyzed. Accurate prediction of large-scale air conditioning load in public buildings is of great significance for grasping the dispatching capacity of air conditioning load in public buildings and participating in the regulation and control of power grid. This paper presents a prediction model based on Elman neural network considering the effect of accumulated temperature in summer. The effective accumulated temperature, humidity and five-day moving average temperature are taken into account as meteorological factors in the prediction model of Elman neural network. The large scale air conditioning load of public buildings is forecasted. (2) the design of dispatching scheme for large-scale air conditioning load of public buildings to participate in the virtual peak-shaving of power grid is studied. The large scale central air conditioning of public buildings takes part in the peak-shaving of power grid, which needs to fully consider the characteristics of conventional units and public buildings. Therefore, based on the design of dispatching scheme, the research is carried out around the establishment of framework, evaluation and so on. This paper studies and analyzes the pre-day, in-day, real-time scheduling technical framework of large-scale air-conditioning load in public buildings, and the large-scale air-conditioning load scheduling framework of public buildings with third-party load agents. In this paper, the double layer dispatching target and constraint condition are expounded, and the online evaluation index and calculation method of large-scale air conditioning load participating in dispatching of public buildings are put forward, which can be used as a reference for the optimization and coordination system of large-scale air conditioning load participation in public buildings. Finally, the optimization and adjustment process of large-scale air conditioning load in public buildings is given. (3) the strategy of virtual peak-shaving for large-scale air conditioning load in public buildings is studied. Firstly, the physical model and main functions of large-scale central air conditioning system in public buildings are analyzed, and then the physical model of central air conditioning system is built. The power of central air conditioning system is divided into five main energy consumption parts, including the energy consumption of refrigeration units. Cooling pump energy consumption, fan coil energy consumption, cooling tower energy consumption and cooling pump energy consumption. Then, according to the analysis of the main energy consumption part of the central air conditioning system, the optimizable part of the central air conditioning system is obtained. The flexible control strategy for large-scale central air conditioning in public buildings is analyzed, including the overall temperature control, increasing the water temperature of the freezer. The process of large-scale participation in flexible control of public buildings is obtained. (4) A virtual peak-shaving optimization example of large-scale air conditioning load in public buildings is established. Large scale air conditioning combinations of public buildings participate in daily dispatching of power grid. According to their actual characteristics, different air conditioning users can adopt different control strategies. Firstly, the large-scale flexible control scheme of public buildings is analyzed, and the curve fitting of the load characteristics of typical central air conditioning users is carried out, and then the presupposition scheme of power grid regulation and control in which typical central air conditioners participate is obtained. An example is given to analyze the bilevel optimal combination scheme for large-scale central air conditioning in public buildings to participate in the daily dispatching of power network. The CPLEX optimization software package is used to optimize the combination of the early peak, middle peak and late peak to obtain the control combination of early peak, low peak and late peak.
【學(xué)位授予單位】：東南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TM73

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