本文關(guān)鍵詞： 抽水蓄能電站 廠用電量 模型 南方電網(wǎng) 支持向量機 模糊 K-means聚類 粒子群算法　出處：《華南理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：廠用電率作為衡量抽水蓄能電站經(jīng)濟運行和節(jié)能降耗的重要技術(shù)經(jīng)濟指標，直接影響抽水蓄能電站經(jīng)營運行效益與節(jié)能減排成效。目前國內(nèi)外針對抽水蓄能電站廠用電方面的深入研究比較少，且大部分都只集中在綜合廠用電量/率的整體研究上。因此，對抽水蓄能電站的廠用電情況進行細化分析，建立科學(xué)的廠用電計算模型，具有重要意義。研究成果能為抽水蓄能電站的廠用電分析與管理考核工作提供科學(xué)依據(jù)，有利于促進電站廠用電的精細化管理、提高節(jié)能管理水平與經(jīng)營運行效益。 本文分析研究了抽水蓄能電站的廠用電構(gòu)成與管理、考核指標及影響因素，提出了將直接廠用電率代替綜合廠用電率作為廠用電考核指標，并闡述其合理性。本文在研究了支持向量機、K-means聚類及粒子群算法的基本理論與應(yīng)用的基礎(chǔ)上，提出了一種基于模糊K-means聚類的樣本優(yōu)化與粒子群的參數(shù)優(yōu)化的支持向量機回歸模型，以實現(xiàn)提高抽水蓄能電站廠用電模型精度，全年整體計算誤差控制在5%以內(nèi)的目標。 本文所研究的抽水蓄能電站廠用電計算模型分為兩部分。一是總體計算模型，基于往年歷史數(shù)據(jù)，運用支持向量機法構(gòu)建直接廠用電量與發(fā)電量、抽水電量、氣溫、水文等關(guān)鍵影響因素之間的回歸模型，模型具有對總體直接廠用電進行擬合計算及預(yù)測的功能；二是模塊化計算模型，將廠用電按系統(tǒng)按模塊進行劃分，，在對各設(shè)備用電量與發(fā)電量、抽水電量、氣溫、水文、運行規(guī)律、出力曲線等因素之間的關(guān)系進行定性分析，對設(shè)備電氣參數(shù)、機組啟停工況及運行時間等數(shù)據(jù)進行定量計算的基礎(chǔ)上，計算各模塊用電量，并同時運用支持向量機法構(gòu)建模塊化擬合模型，該模型具有對各模塊直接廠用電進行計算、擬合及預(yù)測的功能。兩部分模型相互結(jié)合與驗證，可實現(xiàn)對南方電網(wǎng)調(diào)峰調(diào)頻發(fā)電公司抽水蓄能電站本年度廠用電量進行驗算分析與考核、下一年度廠用電量進行預(yù)測的功能。 本文最后建立了惠州抽水蓄能電站直接廠用電計算模型并開發(fā)了配套應(yīng)用軟件，最終計算結(jié)果驗證了模型的準確性和適用性，精度滿足《南方電網(wǎng)“十二五”節(jié)能減排規(guī)劃》中明確要求“調(diào)峰調(diào)頻發(fā)電公司控制其所管轄電廠的廠用電率和標準值誤差在5%以內(nèi)”的節(jié)能減排工作目標。
[Abstract]:As an important technical and economic index to measure the economic operation, energy saving and consumption reduction of pumped storage power station, It has a direct impact on the efficiency of operation and energy saving and emission reduction of pumped storage power plants. At present, there are few in-depth researches on the power supply of pumped storage power plants at home and abroad. And most of them only focus on the overall study of the comprehensive power consumption / rate. Therefore, the detailed analysis of the situation of the pumped storage power station is carried out, and the scientific calculation model of the power consumption is established. The research results can provide a scientific basis for the analysis and management of the power consumption of pumped storage power stations, promote the fine management of the power plants, and improve the level of energy saving management and operation efficiency. In this paper, the composition and management of auxiliary power, the assessment index and the influencing factors of pumped storage power station are analyzed and studied, and it is put forward that the direct power consumption rate should replace the comprehensive service power consumption rate as the test index. This paper studies the basic theory and application of support vector machine (SVM) K-means clustering and particle swarm optimization (PSO). A support vector machine regression model based on fuzzy K-means clustering for sample optimization and particle swarm optimization is proposed to improve the precision of the model and control the overall calculation error within 5%. The model is divided into two parts. One is the overall calculation model. Based on the historical data of previous years, the support vector machine method is used to construct the direct power consumption and generation, pumping capacity, temperature. The regression model between the key influencing factors such as hydrology has the function of fitting and calculating and forecasting the total direct auxiliary power, the second is the modular calculation model, which divides the service power into modules according to the system. Based on the qualitative analysis of the relationship between each equipment's electricity consumption and electricity generation, pumping capacity, air temperature, hydrology, operation law, output curve, and so on, the electrical parameters of the equipment are analyzed. On the basis of quantitative calculation of unit starting and stopping condition and running time, the electricity consumption of each module is calculated. At the same time, the support vector machine method is used to construct the modular fitting model, which can calculate the direct power consumption of each module. The function of fitting and forecasting. By combining and verifying the two models, the function of checking, analyzing and checking the power consumption of pumped storage power station of Southern Power Grid peak-shaving and frequency modulation generation company in this year and forecasting power consumption in the next year can be realized. In the end, the calculation model of direct power supply for Huizhou Pumped-storage Power Station is established, and the corresponding application software is developed. The result of calculation verifies the accuracy and applicability of the model. The precision meets the requirements of the "12th Five-Year Plan for Energy Saving and Emission reduction of Southern Power Grid", which explicitly requires that "peak-shaving and frequency modulation power generation company control the rate of power consumption and the error of standard values of the power plant under its jurisdiction within 5%".
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TV743

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本文編號：1530417