本文關(guān)鍵詞：含分布式電源的配電網(wǎng)絡(luò)優(yōu)化重構(gòu)　出處：《寧夏大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 配電網(wǎng)重構(gòu) 分布式電源 量子粒子群 粒子群

【摘要】：分布式電源(Distributed Generation,DG)并入配電網(wǎng)后,不僅會使電網(wǎng)由單電源變成多電源的復(fù)雜網(wǎng)絡(luò),而且對網(wǎng)損、電壓、潮流大小與方向以及電網(wǎng)運行的安全可靠性等產(chǎn)生嚴(yán)重的影響。因此,必須改變配電系統(tǒng)的分段開關(guān)與聯(lián)絡(luò)開關(guān)對配電網(wǎng)進(jìn)行優(yōu)化重構(gòu),達(dá)到降低網(wǎng)損、均衡負(fù)荷以及提高節(jié)點電壓的目的。根據(jù)風(fēng)力發(fā)電、光伏發(fā)電、燃料電池和微型燃?xì)廨啓C(jī)四種DG的性能以及并網(wǎng)接口形式,將其分為PQ型、PV型、PI型和PQ(Ⅴ)型,同時建立符合配電網(wǎng)運行的模型;將多種潮流算法進(jìn)行對比,結(jié)合DG的模型,選擇前推回代法對含DG的配電網(wǎng)進(jìn)行潮流計算;以網(wǎng)損最小為目標(biāo)函數(shù),建立配電網(wǎng)重構(gòu)模型,并給出重構(gòu)需要滿足的約束條件;對比二進(jìn)制粒子群算法(Binary Particle Swarms Optimization Algorithm,BPSO)與量子粒子群算法(Quantum Particle Swarm Optimizattion Algorithm,QPSO)的性能,結(jié)合其應(yīng)用到配電網(wǎng)優(yōu)化重構(gòu)的優(yōu)缺點,提出一種改進(jìn)的算法-加權(quán)的二進(jìn)制量子粒子群算法(Weighted Binary Quantum Particle Swarm Optimization Algorithm,WBQPSO);以IEEE 33節(jié)點的標(biāo)準(zhǔn)網(wǎng)絡(luò)為例,分別應(yīng)用BPSO算法和WBQPSO算法對含DG的配電網(wǎng)進(jìn)行優(yōu)化重構(gòu),結(jié)果表明WBQPSO算法的收斂速度與降低網(wǎng)損的能力優(yōu)于BPSO算法,且提高了電壓的穩(wěn)定性,驗證了新算法的可行性。
[Abstract]:Distributed power supply (Distributed Generation, DG) into the distribution network, the complex network will not only make the power grid by a single power supply into power, and the voltage of the network loss, seriously affect the size and direction of flow and the safety of power grid reliability. Therefore, switches and contact switches must change the distribution system optimization of distribution network, reduce network loss, improve voltage and load balancing purposes. According to the wind power, photovoltaic power generation, fuel cell and micro gas turbine four DG performance and grid interface, which can be divided into PQ type, PV type, PI type and PQ type (V), established at the same time in accordance with the operation of the power distribution network model; by comparing various power flow algorithm, combined with the DG model, select the back / forward sweep method for distribution network with DG flow calculation; the minimum network loss as the objective function, establish the model of distribution network reconfiguration, And give the reconstruction needs to meet the constraint condition; comparison of binary particle swarm optimization algorithm (Binary Particle Swarms Optimization Algorithm, BPSO) and the quantum particle swarm algorithm (Quantum Particle Swarm Optimizattion Algorithm, QPSO) performance, combined with the advantages and disadvantages of its application to distribution network reconfiguration optimization, proposed binary quantum particle swarm algorithm is an improved algorithm weighted (Weighted Binary Quantum Particle Swarm Optimization Algorithm, WBQPSO); the standard IEEE 33 bus network as an example, BPSO algorithm and WBQPSO algorithm were used to optimize the reconstruction of distribution network with DG, the results show that the convergence speed of WBQPSO algorithm and BPSO algorithm is better than the ability to reduce the network loss and improve the voltage stability. And verify the feasibility of the new algorithm.

【學(xué)位授予單位】：寧夏大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM711

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