本文選題：微電網(wǎng)經(jīng)濟(jì)調(diào)度 + 蓄電池組��； 參考：《山東大學(xué)》2017年碩士論文

【摘要】：利用風(fēng)力、太陽(yáng)能等可再生能源進(jìn)行發(fā)電的分布式電源越來(lái)越多;分布式電源與附近的負(fù)荷構(gòu)成了一個(gè)微型的發(fā)電、供電系統(tǒng),稱之為微電網(wǎng);微電網(wǎng)相關(guān)技術(shù)解決了可再生能源接入大電網(wǎng)的問(wèn)題。作為新的發(fā)電方式及可再生能源接入的途徑,微電網(wǎng)的經(jīng)濟(jì)調(diào)度問(wèn)題一直是深受關(guān)注的研究課題。本文在分析分布式電源、蓄電池組運(yùn)行特性的基礎(chǔ)上,實(shí)現(xiàn)了某實(shí)際微電網(wǎng)的經(jīng)濟(jì)調(diào)度模型。該模型的目標(biāo)函數(shù)考慮了蓄電池組的使用壽命以及公共電網(wǎng)的峰谷電價(jià)影響。微電網(wǎng)中蓄電池組的使用壽命與其充放電過(guò)程有關(guān),本文基于分布式電源出力及微電網(wǎng)負(fù)荷的預(yù)測(cè)結(jié)果,改進(jìn)了蓄電池組優(yōu)化的充、放電策略,即盡可能地利用分布式電源輸出的剩余功率對(duì)蓄電池組進(jìn)行充電,以減少公共電網(wǎng)對(duì)蓄電池組充電的電費(fèi)成本,同時(shí)為了延長(zhǎng)蓄電池組的使用壽命又要控制蓄電池組在短時(shí)間頻繁充、放電次數(shù)。主要工作說(shuō)明如下:1)改進(jìn)了蓄電池組在微電網(wǎng)經(jīng)濟(jì)調(diào)度中的費(fèi)用損失模型。一般采用充電或放電功率絕對(duì)值與蓄電池組總吞吐量之比計(jì)算蓄電池組單次充電或放電的損失費(fèi)用。這個(gè)方法有不足之處,本文采用放電功率的2倍值與總吞吐量之比來(lái)計(jì)算,可以克服蓄電池組荷電狀態(tài)較低時(shí),充電功率過(guò)大導(dǎo)致充電費(fèi)用較高而不得不減小充電功率的問(wèn)題。同時(shí),在對(duì)微電網(wǎng)的分布式電源與負(fù)荷預(yù)測(cè)的基礎(chǔ)上,通過(guò)出力與負(fù)荷之間的功率平衡,對(duì)蓄電池組的充、放電策略進(jìn)行優(yōu)化,其基本思路是盡可能地采用可再生能源發(fā)出的電能對(duì)其進(jìn)行充電,而在電價(jià)峰時(shí)段且分布式電源出力不足時(shí),則盡可能地利用蓄電池組的儲(chǔ)能對(duì)負(fù)荷進(jìn)行供電。而且通過(guò)控制蓄電池組小功率充電或放電的次數(shù),以提高蓄電池組的使用壽命。2)根據(jù)風(fēng)力發(fā)電機(jī)輸出功率損耗率相關(guān)數(shù)據(jù)與光伏電站逆變環(huán)節(jié)輸出損耗率,分別建立了風(fēng)電機(jī)組與光伏電站在輸出功率時(shí)的費(fèi)用損耗模型。這兩個(gè)模型應(yīng)用于分布式電源出力大于負(fù)荷時(shí)的微電網(wǎng)經(jīng)濟(jì)調(diào)度問(wèn)題。3)實(shí)現(xiàn)了微電網(wǎng)經(jīng)濟(jì)調(diào)度的目標(biāo)函數(shù);在分布式電源出力與微電網(wǎng)負(fù)荷的比較基礎(chǔ)上,將目標(biāo)函數(shù)分成兩段,即當(dāng)分布式電源的出力大于微電網(wǎng)負(fù)荷時(shí),以風(fēng)力及光伏輸出功率損耗最小為調(diào)度目標(biāo);當(dāng)出力小于負(fù)荷時(shí)而需要蓄電池組或公共電網(wǎng)提供額外功率時(shí),則以微電網(wǎng)內(nèi)的用電成本最低為調(diào)度目標(biāo)。4)在滿足微電網(wǎng)相關(guān)約束條件,計(jì)及蓄電池組使用壽命,考慮蓄電池組優(yōu)化充、放電策略,計(jì)及公共電網(wǎng)峰谷電價(jià)的基礎(chǔ)上,采用粒子群算法對(duì)微電網(wǎng)的經(jīng)濟(jì)調(diào)度模型進(jìn)行求解,給出了微電網(wǎng)內(nèi)各單元的經(jīng)濟(jì)調(diào)度結(jié)果并進(jìn)行簡(jiǎn)要分析。本文實(shí)現(xiàn)的經(jīng)濟(jì)調(diào)度模型,基于微電網(wǎng)中各個(gè)分布式電源的實(shí)際情況,兼顧了蓄電池組的壽命損耗與公共電網(wǎng)峰谷電價(jià)的影響,能夠更加全面、有效地實(shí)現(xiàn)微電網(wǎng)用電成本最低的目標(biāo)。通過(guò)采用粒子群算法對(duì)該經(jīng)濟(jì)調(diào)度模型的求解,以及對(duì)經(jīng)濟(jì)調(diào)度結(jié)果的分析,說(shuō)明本文實(shí)現(xiàn)的經(jīng)濟(jì)調(diào)度模型具有一定的參考意義,能夠?yàn)槲㈦娋W(wǎng)的規(guī)劃、調(diào)控提供較強(qiáng)的指導(dǎo)作用。
[Abstract]:A growing number of distributed power sources, such as wind, solar and other renewable sources of energy, are becoming more and more distributed; distributed power and nearby loads constitute a micro power generation, power supply systems, called microgrids; microgrid related technologies have solved the problems of renewable energy access to large power grids as new generation methods and renewable energy access. In this paper, based on the analysis of the distributed power and the running characteristics of the battery group, the economic dispatch model of a real microgrid is realized. The objective function of this model takes into account the service life of the battery group and the influence of the peak valley electricity price of the public grid. The service life of the battery group in the power grid is related to the charging and discharging process. Based on the result of the distributed power supply and the prediction of the micro grid load, this paper improves the charging and discharging strategy of the battery group optimization, that is to use the residual power of the distributed power output to recharge the battery pack as much as possible in order to reduce the public grid to the battery group. At the same time, to prolong the service life of the battery, to prolong the service life of the battery group, and to control the number of batteries in a short time and the number of discharge. The main work is as follows: 1) the cost loss model of the battery group in the economic dispatch of the microgrid is improved. The ratio of the absolute value of the charging or discharging power to the total throughput of the battery group is generally adopted. The loss cost of single charge or discharge of battery group is calculated. This method is inadequacies. In this paper, the 2 times of discharge power is calculated with the ratio of total throughput. It can overcome the problem that charging power is too high and has to reduce charging power when the charge state of battery group is low. At the same time, the micro grid can be used. On the basis of distributed power and load forecasting, through the power balance between the output and the load, the charging and discharging strategy of the battery group is optimized. The basic idea is to use the electricity generated by renewable energy to charge it as much as possible, while in the peak period of electricity price and the shortage of distributed power supply, it is used as much as possible. The storage energy of the battery group supplies power to the load. And by controlling the number of small power charging or discharging of the battery group to increase the service life of the battery group.2), the output power of the wind turbine and the photovoltaic power station is established according to the output loss rate related data of the output power of the wind turbine and the output loss rate of the inverter link of the photovoltaic power station. The two models are applied to the microgrid economic scheduling problem.3 when the distributed power supply exceeds the load. The objective function of the microgrid economic dispatch is realized. On the basis of the comparison of the distributed power supply and the microgrid load, the target function is divided into two segments, that is, when the output of the distributed power is larger than the microelectricity. When the load is on the net, the minimum power loss of the wind and photovoltaic output is the scheduling goal. When the power is less than the load, the battery group or the public grid is required to provide the extra power, the minimum power cost in the micro grid is the.4 of the scheduling target. The service life of the battery group is considered, and the battery group is considered. On the basis of the chemical charging, discharge strategy and the peak valley electricity price of the public grid, the particle swarm optimization algorithm is used to solve the economic dispatch model of the microgrid, and the economic dispatch results of each unit in the microgrid are given and a brief analysis is made. The economic dispatch model realized in this paper is based on the actual situation of the distributed power supply in the micro grid and takes into account the consideration of the actual situation of the various distributed power sources in the microgrid. The life loss of the battery group and the peak valley electricity price of the public grid can be more comprehensive and effective to achieve the lowest cost of the power consumption of the microgrid. By using the particle swarm optimization algorithm to solve the economic dispatch model and the analysis of the results of the economic dispatch, the economic dispatch model realized in this paper has a certain reference meaning. It can provide a strong guidance for the planning and regulation of the microgrid.

【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM73

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 于偉俊;;光伏組件壽命周期影響因素解析[J];通訊世界;2017年01期

2 王昕;黃柯;鄭益慧;李立學(xué);郎永波;吳昊;;基于PNN/PCA/SS-SVR的光伏發(fā)電功率短期預(yù)測(cè)方法[J];電力系統(tǒng)自動(dòng)化;2016年17期

3 李博文;靳斌;李竹;王建林;李興;熊明;;基于C-FS混合算法的微電網(wǎng)經(jīng)濟(jì)調(diào)度[J];現(xiàn)代電力;2016年04期

4 王程;劉念;;基于交替方向乘子法的互聯(lián)微電網(wǎng)系統(tǒng)分布式優(yōu)化調(diào)度[J];電網(wǎng)技術(shù);2016年09期

5 馬天男;牛東曉;黃雅莉;杜振東;;基于Spark平臺(tái)和多變量L_2-Boosting回歸模型的分布式能源系統(tǒng)短期負(fù)荷預(yù)測(cè)[J];電網(wǎng)技術(shù);2016年06期

6 趙勁帥;邱曉燕;馬菁曼;陳科彬;;基于模糊聚類分析與模型識(shí)別的微電網(wǎng)多目標(biāo)優(yōu)化方法[J];電網(wǎng)技術(shù);2016年08期

7 張碧玲;胡凌霄;劉勇;毛京麗;周安石;;采用改進(jìn)粒子群算法的微電網(wǎng)短期調(diào)控模型[J];電網(wǎng)技術(shù);2016年06期

8 胡姚剛;李輝;廖興林;宋二兵;歐陽(yáng)海黎;劉志祥;;風(fēng)電軸承性能退化建模及其實(shí)時(shí)剩余壽命預(yù)測(cè)[J];中國(guó)電機(jī)工程學(xué)報(bào);2016年06期

9 胡曉通;劉天琪;劉舒;何川;劉一奎;;基于動(dòng)態(tài)獎(jiǎng)懲電價(jià)的微電網(wǎng)與配網(wǎng)協(xié)調(diào)優(yōu)化運(yùn)行[J];電力自動(dòng)化設(shè)備;2016年03期

10 黃麒元;劉嬌嬌;王致杰;;Kinetic電池模型在微電網(wǎng)調(diào)度的應(yīng)用研究[J];電力系統(tǒng)保護(hù)與控制;2016年04期

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