本文選題：新能源消納 + 源荷聯(lián)合��； 參考：《西安理工大學(xué)》2017年碩士論文

【摘要】：風(fēng)能、太陽能等清潔能源發(fā)電形式在緩解化石能源枯竭、減輕環(huán)境污染等方面發(fā)揮著重要作用。但風(fēng)電、光伏發(fā)電間歇、波動(dòng)、不可控的特性給電網(wǎng)運(yùn)行控制帶來顯著影響,逐年加重的棄風(fēng)棄光現(xiàn)象嚴(yán)重阻礙了我國實(shí)現(xiàn)清潔替代與能源轉(zhuǎn)型。為平衡風(fēng)光波動(dòng)、解決大規(guī)模新能源消納矛盾,本文以優(yōu)化全網(wǎng)資源、提升電網(wǎng)動(dòng)態(tài)平衡性能為切入點(diǎn),研究包含新能源的電力系統(tǒng)多目標(biāo)優(yōu)化調(diào)度策略,力求兼顧新能源利用效率和電網(wǎng)安全、經(jīng)濟(jì)運(yùn)行。首先從電網(wǎng)調(diào)度層面協(xié)調(diào)“源”“荷”雙側(cè)資源,深入分析風(fēng)力、光伏發(fā)電、梯級水電、火電的短期運(yùn)行及互補(bǔ)特性和柔性負(fù)荷響應(yīng)特性,確定源荷聯(lián)合優(yōu)化運(yùn)行可行性;針對柔性負(fù)荷資源數(shù)量多、難以直接控制等特點(diǎn),結(jié)合我國市場建設(shè)現(xiàn)狀,探索基于負(fù)荷聚合商調(diào)度架構(gòu)和雙邊合同互動(dòng)方式的需求側(cè)優(yōu)化調(diào)控策略。本文以減棄增效和提高系統(tǒng)經(jīng)濟(jì)性為優(yōu)化目標(biāo),將柔性負(fù)荷資源作為“虛擬互動(dòng)電廠”參與電量平衡和備用,構(gòu)建最優(yōu)潮流下基于復(fù)雜時(shí)空耦合約束的考慮新能源利用率、常規(guī)火電平穩(wěn)、梯級水電和系統(tǒng)經(jīng)濟(jì)性的源荷聯(lián)合多目標(biāo)調(diào)度模型,將其解耦為具有優(yōu)化時(shí)序的風(fēng)光火荷多方協(xié)調(diào)和梯級水電站經(jīng)濟(jì)分配兩階段優(yōu)化。其次,提出基于Pareto最優(yōu)和精英歸檔機(jī)制的多目標(biāo)螢火蟲算法(MOFA)用于求解高維復(fù)雜多目標(biāo)模型。針對螢火蟲算法搜索效率低的缺點(diǎn),采用粒子群算法中全局最優(yōu)指導(dǎo)飛行方向的思想和種群合并等策略對其改進(jìn),通過標(biāo)準(zhǔn)測試系統(tǒng)驗(yàn)證了算法的正確性。應(yīng)用多目標(biāo)螢火蟲算法和單目標(biāo)螢火蟲算法先后求解兩階段優(yōu)化模型。最后在IEEE-30標(biāo)準(zhǔn)測試系統(tǒng)下,對比不同新能源接入水平下不同場景的調(diào)度計(jì)劃,結(jié)果表明本文所建模型的合理性和源荷聯(lián)合運(yùn)行在提高經(jīng)濟(jì)、社會(huì)、環(huán)境效益上的有效性;所提算法在電力系統(tǒng)多目標(biāo)模型求解中表現(xiàn)出收斂速度快、尋優(yōu)效果佳的性能,具有較強(qiáng)的適應(yīng)性。
[Abstract]:Clean energy, such as wind energy and solar energy, plays an important role in alleviating fossil energy depletion and environmental pollution. However, the intermittent, fluctuating and uncontrollable characteristics of wind power, photovoltaic power generation have a significant impact on power grid operation and control. The phenomenon of abandonment of wind and light has seriously hindered the realization of clean substitution and energy transformation in China. In order to balance the fluctuation of scenery and solve the problem of large scale new energy consumption, this paper studies the multi-objective optimal dispatching strategy of power system including new energy by optimizing the whole network resources and improving the dynamic balance performance of the power network. Strive to take into account the efficiency of new energy use and grid security, economic operation. Firstly, coordinating the "source" and "load" resources from the grid dispatching level, deeply analyzing the short-term operation and complementary characteristics and flexible load response characteristics of wind power, photovoltaic power generation, cascade hydropower, thermal power, and determining the feasibility of combined optimization operation of source and load. In view of the large quantity of flexible load resources and the difficulty of direct control, combined with the current situation of market construction in China, this paper explores the demand-side optimal regulation strategy based on load aggregator scheduling architecture and bilateral contract interaction. In order to reduce the efficiency and improve the system economy, this paper takes flexible load resource as "virtual interactive power plant" to participate in the power balance and reserve, and constructs a new energy utilization factor based on complex space-time coupling constraints under the optimal power flow. The conventional thermal power stable cascade hydropower and system economy combined multi-objective dispatching model is decoupled into the multi-coordination of wind-fire load with optimal time series and the two-stage optimization of economic distribution of cascade hydropower stations. Secondly, a multi-objective firefly algorithm (MOFA) based on Pareto optimization and elite archiving mechanism is proposed to solve the complex multi-objective model with high dimension. Aiming at the low search efficiency of the firefly algorithm, the particle swarm optimization (PSO) algorithm is improved by using the idea of global optimal flight direction guidance and the strategy of population merging. The correctness of the algorithm is verified by a standard test system. The multi-objective firefly algorithm and the single-objective firefly algorithm are used to solve the two-stage optimization model. Finally, in the IEEE-30 standard test system, the scheduling plans of different scenarios under different new energy access levels are compared. The results show that the rationality of the proposed model and the effectiveness of the combined operation of source and load in improving economic, social and environmental benefits; The proposed algorithm has the advantages of fast convergence, good optimization effect and strong adaptability in solving the multi-objective model of power system.
【學(xué)位授予單位】：西安理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM73

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本文編號：2068138