本文選題：優(yōu)化調(diào)度　切入點(diǎn)：BP神經(jīng)網(wǎng)絡(luò)　出處：《合肥工業(yè)大學(xué)》2017年碩士論文

【摘要】：隨著我國(guó)經(jīng)濟(jì)的迅猛發(fā)展,人民生活質(zhì)量的穩(wěn)步提升,社會(huì)節(jié)水、節(jié)能意識(shí)的日益增強(qiáng),人們對(duì)供水系統(tǒng)的期望也越來(lái)越高。如何在穩(wěn)定供水的前提下,盡可能的節(jié)約成本已經(jīng)成為社會(huì)關(guān)注的焦點(diǎn)。泵站和清水池作為供水系統(tǒng)中重要的組成部分,尋求更加科學(xué)合理的運(yùn)行模式是我國(guó)供水系統(tǒng)進(jìn)一步發(fā)展的必然要求。目前我國(guó)泵站管理水平相對(duì)比較落后,傳統(tǒng)的依賴經(jīng)驗(yàn)管理的調(diào)度模式已經(jīng)無(wú)法滿足人們對(duì)日益增長(zhǎng)的供水質(zhì)量的要求,泵站運(yùn)行的優(yōu)化調(diào)度面臨著新的挑戰(zhàn)。本文以蕪湖市三山區(qū)供水系統(tǒng)為依托,運(yùn)用BP神經(jīng)網(wǎng)絡(luò)、遺傳算法、動(dòng)態(tài)規(guī)劃等算法,建立時(shí)用水量預(yù)測(cè)模型、供水系統(tǒng)管網(wǎng)分析模型、泵站優(yōu)化調(diào)度模型以及一、二級(jí)泵站與清水池聯(lián)合優(yōu)化調(diào)度模型,對(duì)泵站優(yōu)化調(diào)度中所涉及的各種內(nèi)容進(jìn)行了系統(tǒng)研究,主要內(nèi)容如下:(1)時(shí)用水量預(yù)測(cè):根據(jù)蕪湖市三山區(qū)時(shí)用水量的變化規(guī)律及各種影響因素,選擇BP神經(jīng)網(wǎng)絡(luò)建立蕪湖市三山區(qū)時(shí)用水量預(yù)測(cè)模型。模型采用3層網(wǎng)絡(luò)結(jié)構(gòu),以過(guò)去24h的時(shí)用水量作為輸入變量,將下一小時(shí)的時(shí)用水量作為輸出變量,對(duì)未來(lái)用水量進(jìn)行科學(xué)預(yù)測(cè)。通過(guò)蕪湖市三山區(qū)實(shí)際數(shù)據(jù)檢驗(yàn)表明,所建模型具有較高的預(yù)測(cè)精度。(2)供水系統(tǒng)管網(wǎng)分析模型:根據(jù)蕪湖市三山區(qū)壓力監(jiān)測(cè)點(diǎn)的布置位置,選擇BP神經(jīng)網(wǎng)絡(luò)建立蕪湖市三山區(qū)供水系統(tǒng)管網(wǎng)分析模型。其中網(wǎng)絡(luò)結(jié)構(gòu)為3層,模型以7個(gè)壓力監(jiān)測(cè)點(diǎn)的時(shí)平均壓力和三山水廠的時(shí)供水流量作為輸入變量,將三山水廠的時(shí)平均供水壓力作為輸出變量。經(jīng)過(guò)蕪湖市三山區(qū)供水管網(wǎng)的實(shí)例檢驗(yàn),所建模型基本能夠模擬管網(wǎng)的運(yùn)行狀態(tài),可以為優(yōu)化調(diào)度服務(wù)。(3)泵站優(yōu)化調(diào)度:研究一、二級(jí)泵站優(yōu)化調(diào)度模型的建模方法,以流量、水壓、水泵性能等為約束,建立三山水廠一、二級(jí)泵站優(yōu)化調(diào)度模型,并運(yùn)用遺傳算法進(jìn)行求解。(4)一、二級(jí)泵站與清水池聯(lián)合優(yōu)化調(diào)度:針對(duì)一、二級(jí)泵站的工作特性,充分利用峰谷電價(jià)差和清水池的調(diào)蓄容積,以一、二級(jí)泵站日運(yùn)行總電費(fèi)最小和水泵機(jī)組啟停次數(shù)最少為雙目標(biāo),建立一、二級(jí)泵站與清水池分級(jí)優(yōu)化調(diào)度模型,并分別運(yùn)用動(dòng)態(tài)規(guī)劃方法、遺傳算法進(jìn)行求解,制定了一、二級(jí)泵站的優(yōu)化調(diào)度運(yùn)行方案。實(shí)例計(jì)算結(jié)果顯示,優(yōu)化后的運(yùn)行方案經(jīng)濟(jì)效益大幅提升。
[Abstract]:With the rapid development of our country's economy, the steady improvement of people's life quality, the increasing consciousness of saving water and energy saving, people's expectation of water supply system is higher and higher. Cost saving as much as possible has become the focus of social attention. Pumping stations and clear water pools are important components of the water supply system. It is necessary to seek more scientific and reasonable operation mode for the further development of water supply system in China. At present, the management level of pump stations in China is relatively backward. The traditional dispatching mode relying on experience management can no longer meet the demand of increasing water supply quality, and the optimal operation of pump station is facing new challenges. This paper relies on the water supply system in Sanshan District of Wuhu City. BP neural network, genetic algorithm, dynamic programming and other algorithms are used to establish water consumption prediction model, water supply network analysis model, pump station optimal dispatching model and the first, second stage pump station and clear water pool joint optimal dispatching model. This paper makes a systematic study on the various contents involved in the optimal dispatching of pumping stations. The main contents are as follows: (1) Prediction of hourly water consumption: according to the changing law of hourly water consumption and various influencing factors in Sanshan District of Wuhu City, BP neural network is selected to establish the forecasting model of hourly water consumption in Sanshan District of Wuhu City. The model adopts a three-layer network structure, takes the hourly water consumption of the past 24 hours as input variable, and takes the hourly water consumption of the next hour as the output variable. Scientific prediction of water consumption in the future is carried out. The results of practical data test in Sanshan District of Wuhu City show that the model has a higher prediction precision and a pipe network analysis model of water supply system: according to the location of pressure monitoring points in Sanshan District of Wuhu City, BP neural network is selected to establish the analysis model of water supply system in Sanshan District of Wuhu City, in which the network structure is three layers. The model takes the hourly average pressure of seven pressure monitoring points and the hourly water supply flow of Sanshan Water Plant as input variables. Taking the average hourly water supply pressure of Sanshan Water Plant as the output variable, the model can basically simulate the running state of the pipe network, and can serve for the optimal dispatching of the pumping station by the example of the water supply network in Sanshan District of Wuhu City. The modeling method of optimal dispatching model of two-stage pumping station is to set up the optimal dispatching model of the first and second stage pumping stations of Sanshan Water Plant with the constraints of flow rate, water pressure and pump performance, and use genetic algorithm to solve the problem. Combined optimal dispatching of two stage pumping stations and clear water pools: according to the working characteristics of the first and second stage pumping stations, the difference between peak and valley electricity prices and the storage capacity of the clear water pool are fully utilized to make use of one, The minimum daily total electricity charge of secondary pumping station and the least number of start-up and stopping times of pump unit are the double objectives. A hierarchical optimal dispatching model of the first, second stage pump station and clear water tank is established, and the dynamic programming method and genetic algorithm are used to solve the problem, and a new model is developed. The calculation results show that the economic benefit of the optimized operation scheme is greatly improved.
【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TV675

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