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《可再生能源》2016,(1)
针对含风电场的电力系统调度中存在的风电消纳问题,提出一种基于第二代非劣支配排序遗传算法(Non-dominated Sorting Genetic Algorithm II,NSGA-II)的多目标优化调度方法。为使电力系统在消纳尽可能多的风电同时,兼顾经济性、安全性和环保性,分别以风电消纳、发电成本和污染物排放量为目标建立了含风电场电力系统双目标及三目标调度模型,采用NSGA-II进行优化求解,并详细分析了不同目标组合策略下电力负荷、机组组合和优化目标对风电消纳的影响程度,同时引入伪权向量法为决策者提供非劣解信息,辅助决策者完成优化调度。分析结果表明,该方法有助于评估机组组合、目标组合等因素对电力系统优化调度的影响程度,对合理提高含风电场电力系统的风电消纳能力有一定的指导意义。 相似文献
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为解决中国"三北"地区供热期间"风热冲突"问题,在风电消纳困难的电网末端加装蓄热式电锅炉,利用弃风电量进行供热以促进风电就地消纳。该文以弃风消纳最大和运行成本最小为目标建立基于风电-蓄热式电锅炉联合供暖的风电消纳多目标优化模型,提出双层优化求解的思想,并采用改进型多目标粒子群优化算法进行求解,对生成的Pareto解集使用模糊隶属度法进行筛选。基于中国吉林省某示范工程的实际数据的仿真结果验证了该方法能够有效降低运行成本,提高风电消纳水平。 相似文献
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《可再生能源》2017,(1)
随着风电的大规模入网,其间隙性和随机性导致弃风现象严重,电动汽车的快速发展为风电消纳提供了新途径。文章以风电消纳最多、负荷方差最小和火电机组发电成本最低为目标函数,综合考虑电力系统的功率供需平衡、火电机组和风电出力等约束条件,建立了基于分时充电电价的电动汽车消纳风电的机组调度优化模型。根据电动汽车负荷对充电电价的响应,得出电动汽车的充电负荷,进而得到电力系统总负荷,以此为基础采用分步优化的方法对模型进行求解。首先以负荷方差最小和风电消纳最多为目标,通过多目标遗传算法NSGA-II对风电出力进行优化;然后以火电机组的发电成本最低为目标对火电机组的出力进行优化,达成风火机组的联动调度。算例结果表明,对电动汽车实行分时充电电价能够提升风电的消纳能力,平滑负荷曲线,降低火电机组的发电成本。 相似文献
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为解决中国"三北"地区风电消纳问题,从提升电力系统调节能力的角度出发,通过在供热侧配置储热、供电侧配置抽水蓄能,与常规机组共同参与电网优化调度,形成电热联合系统多源协调运行的调度模式。在研究电热负荷与风电出力分布特性的基础上,深入分析电热联合系统多源协调对风电消纳的影响机理,以风电消纳电量最大和系统运行成本最小为目标建立电热联合系统多源协调优化模型,并采用多目标和声搜索算法对模型进行求解。以6节点系统为例验证了模型的有效性,结果表明电热联合系统多源协调运行可有效降低系统运行成本,提高风电消纳水平。 相似文献
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文章基于鲁棒优化理论建立了虚拟发电厂最优经济调度模型。首先以虚拟发电厂发电净收益最大为目标函数,计及出力计划约束、机组运行约束、机组启停约束、储能运行约束等必要约束条件建立系统优化运行模型;然后考虑风光出力区间不确定性,以风光出力为自然决策者,以虚拟发电厂为系统决策者,分别制定博弈策略和支付,建立虚拟发电厂最优经济调度鲁棒优化模型,并对其Nash均衡点进行分析;基于两阶段松弛法将所建立的鲁棒优化模型转化为有限可解的步骤;最后通过一个算例验证了所建立的模型在制定虚拟发电厂运行计划方面的经济优势。 相似文献
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针对高比例可再生能源并网,提出含风、光、火、蓄的高比例新能源电力系统多目标日前优化调度模型。该模型考虑在火电机组深度调峰及频繁爬坡等新工况下的火电机组运行成本、污染物惩罚成本以及可再生能源弃电成本,以系统运行成本最低、风光出力最大以及净负荷波动最小为优化目标,采用NSGA-Ⅱ算法进行优化求解。通过对某典型日不同调度场景进行仿真计算,结果表明所建立的系统运行总成本计算模型能够兼顾该系统的经济、环保与消纳,所提出的多目标优化调度策略能够促进高比例可再生能源的消纳,缓解火电机组的调峰压力,降低系统运行总成本,指导电力系统火电灵活性改造,保证电力系统安全、稳定、经济运行。 相似文献
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Optimal reactive power dispatch (ORPD) problem is an important problem in the operation of power systems. It is a nonlinear and mixed integer programming problem, which determines optimal values for control parameters of reactive power producers to optimize specific objective functions while satisfying several technical constraints. In this paper, stochastic multi-objective ORPD (SMO-ORPD) problem is studied in a wind integrated power system considering the loads and wind power generation uncertainties. The proposed multi objective optimization problem is solved using ε-constraint method, and fuzzy satisfying approach is employed to select the best compromise solution. Two different objective functions are considered as follow: 1) minimization of the active power losses and 2) minimization of the voltage stability index (named L-index). In this paper VAR compensation devices are modeled as discrete variables. Moreover, to evaluate the performance of the proposed method for solution of multi-objective problem, the obtained results for deterministic case (DMO-ORPD), are compared with the available methods in literature. The proposed method is examined on the IEEE-57 bus system. The proposed models are implemented in GAMS environment. The numerical results substantiate the capability of the proposed SMO-ORPD problem to deal with uncertainties and to determine the best settings of control variables. 相似文献
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由于风机的无功耗变,电网电压稳定性随着风力渗透的增加而降低.针对风电场接入的配电网系统无功优化调度问题,本文提出了一种基于ADMM算法的两级无功优化调度方法.与现有的无功优化控制方法相比,该方法采用两阶段优化结构实现分布式无功优化调度.此外,在分区概念下,不需要一致性协议来解决优化问题.该方法在控制设计中也考虑了各个风... 相似文献
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A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reduction in power system integrated wind power 总被引:2,自引:0,他引:2
Gwo-Ching Liao 《Energy》2011,36(2):1018-1029
An optimization algorithm is proposed in this paper to solve the economic dispatch problem that includes wind farm using the Chaotic Quantum Genetic Algorithm (CQGA). In addition to the detailed models of economic dispatch introduction and their associated constraints, the wind power effect is also included in this paper. The chaotic quantum genetic algorithm used to solve the economic dispatch process and discussed with real scenarios used for the simulation tests. After comparing the proposed algorithm with several other algorithms commonly used to solve optimization problems, the results show that the proposed algorithm is able to find the optimal solution quickly and accurately (i.e. to obtain the minimum cost for power generation in the shortest time). At the end, the impact to the total cost savings for power generation after adding (or not adding) wind power generation is also discussed. The actual implementation results prove that the proposed algorithm is economical, fast and practical. They are quite valuable for further research. 相似文献
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《International Journal of Hydrogen Energy》2019,44(56):29409-29417
In this paper, an integrated energy system (IES) consisting of wind turbine unit, photovoltaic cell unit, electrolytic hydrogen unit, fuel cell unit, and hydrogen storage unit is proposed, and the construction of multi objectives for day-ahead power dispatching of the IES considering both operation and environment cost is discussed. By adopting piecewise linearization method, the optimization variables are divided into 24 periods, and the day-ahead power dispatching optimization problem is transformed into a 24-h piecewise optimization problem. On the basis, a complete non-linear mixed integer dynamic scheduling optimization model is established. An improved non-dominated sorting genetic algorithm (NSGA-II) is applied to solving the model. In optimization process, an interactive strategy is adopted to solve the coordination between discretization of variables and restriction of switching times of electrolyzer. Optimization results show that, compared with the single objective of minimizing operating costs, the multi-objective optimization scheme can reduce carbon emissions by 3.5% with 2.8% increase of operating cost. Compared with the single objective of minimizing environmental, the multi-objective optimization scheme can reduce operating cost carbon by 5.12% with 2.6% increase of environmental cost. 相似文献
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