本文關(guān)鍵詞： 配網(wǎng)規(guī)劃 分布式電源 定容選址 綜合目標(biāo)優(yōu)化 量子粒子群　出處：《廣東工業(yè)大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：近年來,世界上發(fā)生的幾次大的停電事故,包括2008年雪災(zāi)導(dǎo)致的電力系統(tǒng)事故都充分暴露了單一集中式供電模式的脆弱性。分布式發(fā)電技術(shù)的發(fā)展為集中供電方式提供了有益的補(bǔ)充,風(fēng)、光和水資源的有機(jī)結(jié)合是節(jié)省投資、降低能耗、提高電力系統(tǒng)穩(wěn)定性和靈活性的主要方式,是未來能源領(lǐng)域一個重要的發(fā)展方向。但是,分布式電源在為大電網(wǎng)提供能源補(bǔ)充和電壓支撐的同時,也必然給電力系統(tǒng)的潮流分布、電能質(zhì)量和繼電保護(hù)等方面帶來影響,因此合理規(guī)劃配電網(wǎng)的分布式電源顯得十分重要。 本文根據(jù)配電網(wǎng)規(guī)劃的原則和內(nèi)容,對分布式電源接入配電網(wǎng)的位置和容量進(jìn)行優(yōu)化研究。論文首先詳述了各種不同類型的分布式電源技術(shù),并主要介紹了風(fēng)機(jī)、光伏電池和小水電的三種分布式電源的出力模型。其次,介紹了分布式電源接入系統(tǒng)后對配電網(wǎng)系統(tǒng)的影響,包括對潮流計(jì)算、電能質(zhì)量、繼電保護(hù)系統(tǒng)、系統(tǒng)可靠性和配電規(guī)劃等的影響；再次,詳細(xì)介紹了求解含分布式電源的配電網(wǎng)優(yōu)化規(guī)劃問題的標(biāo)準(zhǔn)粒子群和量子粒子群算法,并利用算法測試三個非線性帶約束條件的函數(shù),驗(yàn)證了量子粒子群算法的有效性和可行性；最后,針對含分布式電源配電網(wǎng)規(guī)劃問題,建立了以有功網(wǎng)損費(fèi)用和DG運(yùn)行費(fèi)用最小的目標(biāo)函數(shù),以電壓、電流和DG容量限制為約束條件,采用懲罰函數(shù)方式將約束條件轉(zhuǎn)換并加入到求解的目標(biāo)函數(shù)中形成綜合目標(biāo)函數(shù),然后以IEEE14節(jié)點(diǎn)系統(tǒng)作為該地區(qū)模擬測試配電網(wǎng),利用量子粒子群算法對分布式電源配置進(jìn)行優(yōu)化,并與基本粒子群算法進(jìn)行比較,仿真結(jié)果表明本文所提出的算法在配電網(wǎng)規(guī)劃中具有較好的全局尋優(yōu)能力和較快的收斂速度。根據(jù)某地區(qū)配電網(wǎng)規(guī)劃實(shí)際情況,利用量子粒子群算法對三種分布式電源兩兩接入或是三種同時接入的配電網(wǎng)方案進(jìn)行對比,以網(wǎng)損費(fèi)用和DG運(yùn)行費(fèi)用之和最小為優(yōu)化目標(biāo),利用DG接入前后的配電網(wǎng)系統(tǒng)節(jié)點(diǎn)電壓和網(wǎng)損變化來說明合理選擇接入DG位置和容量的重要性,為該地區(qū)配電系統(tǒng)規(guī)劃提供參考價(jià)值。
[Abstract]:In recent years, there have been several major blackouts in the world. Including the 2008 snow disaster caused by the power system accidents have fully exposed the vulnerability of a single centralized mode of power supply. The development of distributed generation technology provides a useful supplement to the centralized power supply mode wind. The organic combination of light and water resources is the main way to save investment, reduce energy consumption, improve the stability and flexibility of power system, and is an important development direction in the field of energy in the future. Distributed generation not only provides energy supply and voltage support for large power grid, but also influences power flow distribution, power quality and relay protection of power system. Therefore, it is very important to plan the distributed generation of distribution network reasonably. According to the principles and contents of distribution network planning, this paper studies the location and capacity optimization of distributed generation access to distribution network. Firstly, this paper describes various types of distributed power generation technology. And mainly introduces three kinds of distributed power generation model of fan, photovoltaic cell and small hydropower. Secondly, it introduces the influence of distributed power system on distribution network system, including power flow calculation, power quality. The impact of relay protection system, system reliability and distribution planning; Thirdly, the standard particle swarm optimization and quantum particle swarm optimization algorithm are introduced in detail to solve the distribution network optimization problem with distributed generation, and three nonlinear functions with constraints are tested by using the algorithm. The validity and feasibility of quantum particle swarm optimization (QPSO) are verified. Finally, aiming at the distribution network planning problem with distributed generation, an objective function with minimum active power loss cost and DG operation cost is established, with the constraints of voltage, current and DG capacity as constraints. The constraint condition is transformed by penalty function and added to the objective function to form a comprehensive objective function, and then the IEEE14 node system is used as the simulation test distribution network in the region. Quantum Particle Swarm Optimization (QPSO) is used to optimize the distributed power allocation, and compared with the basic PSO. The simulation results show that the proposed algorithm has better global optimization ability and faster convergence rate in distribution network planning. Quantum Particle Swarm Optimization (QPSO) is used to compare the distribution network schemes with two or three kinds of distributed power supply. The optimal goal is to minimize the sum of loss cost and DG operating cost. The change of node voltage and network loss before and after DG access is used to explain the importance of reasonable selection of DG location and capacity, which provides a reference value for distribution system planning in this area.
【學(xué)位授予單位】：廣東工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM715;TP18

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