發(fā)布時間：2018-06-24 00:27

  本文選題：獨立微網(wǎng) + 多目標優(yōu)化��； 參考：《電力系統(tǒng)保護與控制》2017年23期

【摘要】：針對目前獨立微網(wǎng)優(yōu)化運行中微源類型與場景設(shè)計較為簡單、未充分考慮可控負荷作用等問題,以可控負荷作為網(wǎng)內(nèi)功率平衡的輔助手段,研究多源獨立微網(wǎng)的調(diào)度優(yōu)化問題。建立了使發(fā)電成本、切負荷補償成本及微網(wǎng)環(huán)境效益最優(yōu)的多目標優(yōu)化模型。根據(jù)工作日、周末和晴、陰雨天組合設(shè)計了四種典型場景,在滿足功率平衡等約束的前提下實現(xiàn)獨立微網(wǎng)的經(jīng)濟調(diào)度。針對優(yōu)化變量多、場景復(fù)雜的微網(wǎng)優(yōu)化模型,提出了改進的混沌粒子群算法(Chaos Particle Swarm Optimization,CPSO)用于優(yōu)化問題求解,驗證了模型和算法對不同場景微網(wǎng)優(yōu)化問題的有效性。
[Abstract]:Aiming at the simple design of microsource type and scene in the optimal operation of independent microgrid, the problem of scheduling optimization of multi-source independent microgrid is studied by using controllable load as the auxiliary means of power balance in the network. A multi-objective optimization model is established to optimize generation cost, load cutting compensation cost and environmental benefit of microgrid. Four typical scenarios are designed according to the combination of workday, weekend and sunny, rainy weather, and the economic scheduling of independent microgrid is realized under the condition of satisfying power balance and other constraints. An improved chaotic particle swarm optimization algorithm (Chaos Particle Swarm Optimization) is proposed to solve the problem of microcellular optimization with multiple variables and complex scenes. The effectiveness of the model and algorithm for different scenarios of microcellular optimization is verified by using the improved chaos Particle Swarm Optimization (CPSO) algorithm.
【作者單位】： 云南電網(wǎng)有限責(zé)任公司電力科學(xué)研究院;新能源電力系統(tǒng)國家重點實驗室(華北電力大學(xué));澳大利亞國立大學(xué)環(huán)境與社會學(xué)院;美國伊利諾伊大學(xué)厄巴納-香檳分校;
【基金】：云南省新能源重大科技專項(2013ZB005) 云南電網(wǎng)有限責(zé)任公司科技項目(YNKJQQ00000280) 新能源電力系統(tǒng)國家重點實驗室開放課題(LAPS16007,LAPS16015)~~
【分類號】：TM727

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相關(guān)期刊論文 前10條

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本文編號：2059134