主動(dòng)配電網(wǎng)的全壽命周期分布式電源規(guī)劃問(wèn)題研究-文庫(kù)吧資料
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【正文】 電池的額定光照強(qiáng)度和實(shí)際光照強(qiáng)度。1 不確定性建模與傳統(tǒng)配電網(wǎng)相比，主動(dòng)配電網(wǎng)中增加了大量分布式能源（DER），如光伏發(fā)電（Photovoltaic Generation，PV）、風(fēng)力發(fā)電（Wind Power Generation）、微型燃?xì)獍l(fā)電（Microturbine，MT）、燃料電池（Fuel Cell）等分布式電源（Distributed Generation，DG），各類儲(chǔ)能設(shè)備以及需求響應(yīng)策略下的各類柔性負(fù)荷。利用帶自適應(yīng)變異因子的改進(jìn)粒子群算法對(duì)上、下層模型進(jìn)行求解。而下層模型則以最小化DG切除功率為目標(biāo)，利用主動(dòng)管理模式對(duì)DG的運(yùn)行進(jìn)行優(yōu)化。鑒于此，本文基于配電網(wǎng)電源側(cè)的全壽命周期成本分析，建立了考慮主動(dòng)管理模式的主動(dòng)配電網(wǎng)雙層規(guī)劃模型以得到最優(yōu)的電源規(guī)劃方案。文獻(xiàn)[89]結(jié)合ADN中的主動(dòng)管理模式建立多目標(biāo)雙層分布式電源規(guī)劃模型，上層模型以最小化DG年投資運(yùn)行成本和網(wǎng)損為目標(biāo)，形成DG的布點(diǎn)定容方案，而下層模型則在上層結(jié)果的基礎(chǔ)上對(duì)DG的出力進(jìn)行主動(dòng)管理，將DG的有功出力切除量反饋給上層便于引導(dǎo)決策。此外，考慮到不可控DG的間歇性，在傳統(tǒng)配電網(wǎng)規(guī)劃中一般采用多場(chǎng)景技術(shù)[5]、機(jī)會(huì)約束理論[6]或模糊數(shù)學(xué)理論[7]采用確定性或不確定彈性約束的方式對(duì)DG出力的不確定性進(jìn)行描述。在傳統(tǒng)配電網(wǎng)環(huán)境下的DG優(yōu)化配置問(wèn)題中，中壓配電網(wǎng)往往作為電力系統(tǒng)的被動(dòng)負(fù)荷，在無(wú)故障情況下不會(huì)自動(dòng)操作，因此其網(wǎng)架結(jié)構(gòu)較為固定。然而，當(dāng)前DG接入配電網(wǎng)仍采用“安裝即忘記”的被動(dòng)管理模式，沒(méi)有充分考慮不可控DG出力的間歇性和隨機(jī)性對(duì)電網(wǎng)造成的不利影響，同時(shí)也未充分發(fā)揮DG靈活調(diào)控對(duì)于降低網(wǎng)損、改善支路潮流等方面的積極作用。關(guān)鍵詞：主動(dòng)管理；多目標(biāo)雙層規(guī)劃；分布式電源；粒子群算法；中圖分類號(hào)：TM71 文獻(xiàn)標(biāo)識(shí)碼：B 文章編號(hào)：10011390（2018）03000000Research on distributed generation planning of active distribution network considering life cycle costZheng Bowen, Yang Jun, Yang Chengchen, Bao Xiaofeng(Yuxi Power Supply Bureau, Yuxi 653100, Yunan, China)Abstract: The key features of Active active Distribution distribution Network network (ADN) which include active management and active control exacerbate the difficulty of its generation planning. Based on flexible adjustment capability of ADN, a multiobjective Bibilevel programming model about distribution generation considering active management mode was proposed in this paper. The objective of upper level model was to minimize the total life cycle cost of power supply side in the system, thus the installation and configuration plan was obtained after optimization. Whereas the lower level model was aimed at minimizing active power curtailment value, and operation optimization of distributed generation (DG) was obtained through applying DG output control, onloadtapchanging transformer adjustment, reactive power pensation device adjustment and other active management modes. The upper and lower model weremodels were solved by improved particle swarm optimization (PSO) algorithm with adaptive mutation, which could improve the solution speed and the global optimal effectiveness. Besides, the simulation analysis of the IEEE 33node system was carried out to verify the rationality of the model.Keywords: active management, multiobjective bilevel planning, distributed generation, improved particle swarm optimization optimizationalgorithm0 引 言電源規(guī)劃是配電網(wǎng)規(guī)劃中的一個(gè)至關(guān)重要的環(huán)節(jié)，其涉及到負(fù)荷預(yù)測(cè)、電力電量平衡、廠址選擇、機(jī)組類型和規(guī)模、燃料來(lái)源及運(yùn)輸條件、系統(tǒng)運(yùn)行、網(wǎng)絡(luò)規(guī)劃和各種技術(shù)經(jīng)濟(jì)指標(biāo)的選擇等一系列問(wèn)題[1]。利用帶自適應(yīng)變異的改進(jìn)粒子群（IPSO）算法對(duì)上下層模型進(jìn)行求解，提高了算法的求解速度并有效得到全局最優(yōu)解。本文基于ADN的靈活管控特性提出了考慮主動(dòng)管理模式的分布式電源多目標(biāo)雙層規(guī)劃模型。第44卷 第504期 電測(cè)與儀表 2007年 第12期 Elect
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