含風(fēng)電場的電力系統(tǒng)多目標(biāo)優(yōu)化調(diào)度
麻利新，翟帥華，李萍
（寧夏大學(xué) 物理與電子電氣工程學(xué)院，寧夏 銀川 750021）
摘 要：針對火力發(fā)電對環(huán)境造成的嚴(yán)重污染問題，建立了含風(fēng)電場的電力系統(tǒng)多目標(biāo)優(yōu)化調(diào)度模型。以火電機組燃料費用和污染氣體排放量最低為目標(biāo)，用虛擬解理論將多目標(biāo)優(yōu)化問題轉(zhuǎn)化為單目標(biāo)優(yōu)化問題，以降低問題的復(fù)雜性；用動態(tài)搜索步長及動態(tài)搜索概率對布谷鳥算法改進(jìn)，用改進(jìn)后的算法求解所建立調(diào)度模型。仿真結(jié)果表明，改進(jìn)算法在符合有功平衡約束、機組出力約束及機組爬坡約束等同樣的前提條件下，具有節(jié)約發(fā)電成本，減少污染物排放，加快系統(tǒng)運行速度的優(yōu)點。
關(guān)鍵詞：風(fēng)電場；污染物排放；多目標(biāo)優(yōu)化；虛擬解；布谷鳥算法
中圖分類號：TM614 文獻(xiàn)標(biāo)識碼：A 文章編號：1007-3175(2019)08-0007-04
Multi-Objective Optimal Scheduling of Power System Including Wind Farm
MA Li-xin, ZHAI Shuai-hua, LI Ping
（School of Physics and Electronic-Electrical Engineering, Ningxia University, Yinchuan 750021, China）
Abstract: Aiming at the serious pollution problem caused by thermal power generation, this paper established a multi-objective optimization scheduling model of power system including wind farms. In order to reduce the complexity of the problem, the multi-objective optimization problem was transformed into a single-objective optimization problem by using the virtual solution theory, aiming at the lowest fuel cost and the lowest emission of polluted gases. The cuckoo algorithm was improved by using dynamic search step size and dynamic search probability, and the improved algorithm was used for solving the established scheduling model. The simulation results show that the improved algorithm has the advantages of saving power generation costs, reducing pollutant emissions and speeding up the system operation under the same preconditions as active power balance constraints, unit output constraints and unit climbing constraints and so on.
Key words: wind farm; pollutant emissions; multi-objective optimization; virtual solution; cuckoo algorithm
參考文獻(xiàn)
[1] 楊德友，劉世宇. 求解電力系統(tǒng)多目標(biāo)環(huán)境經(jīng)濟(jì)調(diào)度的帕累托最優(yōu)MFO算法[J]. 電工電能新技術(shù)，2018，37(2)：30-37.
[2] 劉世宇. 考慮儲能資源的風(fēng)電富集電力系統(tǒng)環(huán)境經(jīng)濟(jì)調(diào)度方法研究[D]. 吉林：東北電力大學(xué)，2018.
[3] 左麗霞， 余愿， 孫慧娟. 電力系統(tǒng)動態(tài)環(huán)境經(jīng)濟(jì)調(diào)度模型研究[J]. 華東交通大學(xué)學(xué)報，2018，35(3)：134-142.
[4] 唐程輝，張凡，張寧，等. 基于風(fēng)電場總功率條件分布的電力系統(tǒng)經(jīng)濟(jì)調(diào)度二次規(guī)劃方法[J]. 電工技術(shù)學(xué)報，2019，34(10)：2069-2078.
[5] 夏偉偉，孫龍明，師揚，等. 含風(fēng)電場的電力系統(tǒng)多目標(biāo)環(huán)境經(jīng)濟(jì)調(diào)度[J]. 電氣開關(guān)，2017(3)：26-29.
[6] YANG X S, DEB S.Cuckoo Search via Lévy Flights[C]//World Congress on Proceedings of Nature & Biologically Inspired Computing，2009：210-214.
[7] MARICHELVAM M K, PRABAHARAN T, YANG X S. Improved cuckoo search algorithm for hybrid flow shop scheduling problems to minimize makespan[J].Applied Soft Computing，2014，19(1)：93-101.
[8] 尹詩德. 基于模擬退火的混合布谷鳥算法求解公交調(diào)度問題[D]. 廣州：華南理工大學(xué)，2018.
[9] 賀飛. 化學(xué)反應(yīng)算法在含風(fēng)電的電力系統(tǒng)動態(tài)經(jīng)濟(jì)調(diào)度中的應(yīng)用[D]. 長沙：湖南大學(xué)，2017.
[10] BASU M.Dynamic economic emission dispatch using nondominated sorting genetic algorithm-II[J].International Journal of Electrical Power & Energy Systems，2008，30(2)：140-149.
