Stochastic mid-term generation scheduling incorporated with wind power

A challenge now facing system operator is how to schedule optimally the generation units in a wind integrated power system over a one year time horizon considering the effects of wind forecasting and variability; also, regarding the effects of load uncertainty. By the same token, this paper first develops a new formulation for Stochastic Mid-term Generation Scheduling (SMGS). In the formulation, 2m + 1 point estimate method is developed to accurately estimate the output variables of Mid-term Generation Scheduling (MGS) problem. Then, the formulation is combined with adaptive modified gravitational search algorithm and a novel self-adaptive wavelet mutation strategy for the establishment of new robust algorithm for the present problem. It is noteworthy to say that the classical methods considered certain wind information in the deterministic solution of the MGS problem which is not the realistic approach. However, this study improves modeling of wind–thermal system in the MGS problem by considering possible uncertainties when scheduling the generators of power system. The proposed model is capable of taking uncertainty of load and wind into account. The proposed method is applied on two test cases and the numerical results confirmed the efficiency and stability of the proposed algorithm.     

Interval type-2 fuzzy modeling of wind power generation in Genco's generation scheduling

Wind power is a promising source of electric power generation since it has tremendous environmental and social benefits. The generation scheduling (GS) problem encounters several uncertainties in terms of the system's parameters such as load, reserve and available wind power generation. The modeling of those uncertainties is an important issue in power system scheduling. A fuzzy based modeling approach can be used to develop the generation schedule under an uncertain environment.In this paper, the type-2 fuzzy membership function (MF) is implemented to model the linguistic uncertainty of type-1 MF of available wind power generation which stems from opinions of different experts. The proposed approach is applied to two test systems (six and twenty-six conventional generating units both with two wind farms) and the results of generation scheduling using both fuzzy modeling type-1, and type-2 are presented. These results demonstrate that the advantage of using the type-2 fuzzy to model the linguistic uncertainty of the type-1 MF. This paper demonstrates how unit scheduling in an uncertain environment of type-1 fuzzy MF modeling can be performed just by using a single type-2 fuzzy MF when all type-1 MF were in the footprint of uncertainty (FOU) of type-2 MF.     

一种求解环境经济发电调度的交互式多目标优化方法

针对环境经济发电调度问题,提出一种基于评价函数的交互式多目标优化方法并结合改进的粒子群优化的求解方法。构造的总体协调度评价函数可以较好地平衡节能和减排2个优化目标。决策者可以通过调整各单目标满意度来体现其主观愿望。该方法克服了多目标向单目标转化过程中权重系数选择的困难,增强了决策方案选择的互动性。对一个含6台发电机组的系统进行仿真分析,结果验证了该方法在求解环境经济调度问题方面的可行性和有效性。     

A new model for optimal generation scheduling of power system considering generation units availability

The objective of the short-term combined economic–environmental dispatch is to obtain the optimal power outputs of all generating units in the system given simultaneous minimization of the corresponding fuel cost and the release of gaseous pollutants in the environment. In this paper the classical model of the dynamic combined economic–environmental power dispatch is upgraded considering the availability of the generating units present in the system. The unavailability of power generation is defined as risk index and is considered to be a function of the generating units power level. An efficient multi-objective based genetic algorithm is applied for optimization purposes. Combined hydro-thermal power system is used as a case study system. The results show increase of the availability of power generation followed by small increase of the fuel cost and the gaseous emission.     

一种含风电电力系统的日前发电计划和旋转备用决策模型

提出了一种新的大规模风电并网后日前发电计划和旋转备用决策模型。利用风电和负荷2种随机因素的概率密度函数估算系统的停电损失和弃风损失,并将它们作为风险成本计入发电成本目标函数中,在充分满足机组爬坡和系统安全等约束的前提下,同时求解每台常规机组的日前出力和正负旋转备用量。采用优先列表法和基于最小边际成本法的经济调度算法对模型进行求解。算例分析结果表明,所提模型和方法是有效的。     

发电设备市场竞争关键是创新

在发电设备市场竞争中,价格优势不是万能的。在降低价格的同时,还要提高产品的性能,这就要求企业必须具备不断创新的能力。参与竞争,事前还须“摸底”,只有“知彼知已”才能取胜。     

Energy delivery capacity and generation scheduling in thederegulated electric power market

The generation schedules obtained in traditional hydrothermal scheduling or unit commitment programs are in hourly generation levels. In the new deregulated power market, the power transactions are processed in terms of hourly energy delivery. Failing to fulfil scheduled energy delivery may result in a penalty to the power producers. This paper shows that although ramp-rate constraints are satisfied in hydrothermal scheduling, taking a generation level schedule as an energy delivery schedule may not be realizable. Based on the maximum principle in optimal control theory, the energy delivery capacity across the scheduling horizon is established as a set of recursive equations with given ramp-rate constraints. A sufficient and necessary condition is obtained to check if an energy delivery schedule is realizable. Based on this condition, two cases, where ramp-rate constraints are both satisfied, are analyzed and an unrealizable energy delivery schedule is observed     

基于物理合同的梯级水电厂日前交易电量优化分配

提出物理合同模式下梯级水电厂日前交易电量优化的数学模型,目标函数是梯级总收入最大化,采用逐步优化算法,能够同时进行合同电量和竞价电量的优化分配,为梯级水电厂联合报价和电量申报提供参考。实例应用表明了方法的可行性。     

A novel differential evolution application to short-term electrical power generation scheduling

This paper proposes a new way of applying a differential evolution algorithm to short-term electrical power generation scheduling. Traditionally, the problem is divided into two subproblems. An evolutionary algorithm, which works with binary decision variables, is applied to the first subproblem to find a low cost scheduling of power generators, satisfying some operational constraints. Then, the lambda-iteration method, is used to calculate the power generated by the online generators. In this study, the problem is treated as a whole for the first time in literature and an application of a real-valued differential evolution algorithm is proposed. This approach eliminates the use of an iterative local search technique such as lambda-iteration in all solution evaluations. Through comparisons with results from literature, it is shown that the proposed method achieves a similar solution quality to existing methods, without needing the time consuming lambda-iteration step. Finally, the new approach is applied to real-world data from the Turkish interconnected power network.     

基于公平发电的新能源电站协调调度方法研究

我国新能源电站普遍存在限电现象,限电条件下多个新能源电站如何公平的参与调度成为关键问题。文中提出一种考虑新能源发电公平性的新能源电站协调调度方法。考虑技术性、运营特性、经济性和可靠性等多维度提出新能源电站评价指标体系;提出基于灰色关联度和熵权法的新能源电站评价指标体系综合分析方法,以综合评价新能源电站先进性。基于新能源电站先进性综合排名,提出了包含电网对新能源发电的可消纳空间计算和调度计划公平性分配的新能源电站协调调度方法。通过算例结果表明,所提出的评价指标体系及其分析方法可以正确评价新能源电站先进性,所提出的新能源协调调度方法可以有效保障综合排名高的电站优先发电,提升新能源电站参与调度的公平性。     

四川电网节能发电调度的措施及节能效果

四川省电力公司作为国家首批节能发电调度试点单位,充分利用试点契机,在实际调度工作中,摸索出一系列节能发电调度的有效实施措施。通过分析节能发电调度实施过程中出现的问题,深入研究节能发电调度规则。从节能减排角度出发,完善节能发电调度的实施措施,并通过试运行期间的实际运行结果,验证了这些措施的有效性、正确性。     

含风力发电的电动汽车充电站区间优化调度

针对风机出力的间歇性与波动性和电动汽车充电负荷的随机性使含风力发电的电动汽车充电站内的源、荷在一定范围内变化的问题,需要采用不确定性分析方法对其进行优化调度.不同于其他调度模型,文中以多场景方法模拟出的区间值代替点值作为风机出力和基础负荷的预测结果,并根据区间运算规则建立了含风力发电的电动汽车充电站区间优化调度模型.其...     

电网企业参与分布式发电项目售电竞争环境分析

随着分布式发电项目的快速发展和售电侧改革日益推进,未来分布式发电项目将参与售电竞争。分析电网企业参与分布式发电项目售电竞争的优势与劣势。从电网企业角度,利用SWOT分析理论对分布式发电项目售电竞争内外部环境进行分析,并根据分析结果为电网企业分布式发电项目售电竞争提出参考。     

Optimal security-constrained power scheduling by Benders decomposition

This paper presents a Benders decomposition approach to determine the optimal day-ahead power scheduling in a pool-organized power system, taking into account dispatch, network and security constraints. The study model considers the daily market and the technical constraints resolution as two different and consecutive processes. The daily market is solved in a first stage subject to economical criteria exclusively and then, the constraints solution algorithm is applied to this initial dispatch through the redispatching method. The Benders partitioning algorithm is applied to this constraints solution process to obtain an optimal secure power scheduling.     

考虑分布式电源无功调节的配电网两级动态无功调度策略

针对传统配电网两级动态无功调度策略存在的均衡度低、耗时长的问题,提出了考虑分布式电源无功调节的配电网两级动态无功调度策略。根据分布式电源的无功调节原理,设计了配电网安全态势功能模型,在引入数据处理技术的基础上,评估了配电网的网络安全态势。利用配电网两级的输出信道带宽,构建了影响配电网两级电力负载的期望方程。基于配电网节点耗能因子矩阵,得到了配电网两级动态无功调度的负载输出项,完成配电网两级动态无功调度的统计分析。通过制定配电网两级动态无功调度策略,实现了配电网两级的动态无功调度。实验结果表明,考虑分布式电源无功调节的配电网两级动态无功调度策略的均衡系数大于0.7,调度耗时在5 s以下,不仅具有更高的均衡度,还可以确保配电网两级动态无功调度具有更高的效率。     

水火电力系统短期发电计划优化方法综述

水火电力系统的短期发电计划问题在电力系统的安全可靠和经济运行中发挥着越来越重要的作用，由于其本身的复杂性，很难从理论上找到全局最优解。深入探讨各种优化算法，并加以分类，详细综述各种优化方法在水火电力系统短期发电计划问题中所取得的研究成果和存在的不足之处。     

Multi-area generation scheduling algorithm with regionally distributed optimal power flow using alternating direction method

This paper calls attention to the core issue as to the multi-area generation scheduling algorithm in interconnected electric power systems. This algorithm consists in deciding upon on/off states of generating units and their power outputs to meet the demands of customers under the consideration of operational technical constraints and transmission networks while keeping the generation cost to a minimum. In treating the mixed integer nonlinear programming (MINLP) problem, the generalized Benders decomposition (GBD) is applied to simply decouple a primal problem into a unit commitment (UC) master problem and inter-temporal optimal power flow (OPF) sub-problems. Most prominent in this work is that the alternating direction method (ADM) is introduced to accomplish the regional decomposition that allows efficient distributed solutions of OPF. Especially, the proposed distributed scheme whose effectiveness is clearly illustrated on a numerical example can find the most economic dispatch schedule incorporated with power transactions on a short-term basis where utilities are less inclined to pool knowledge about their systems or to telemeter measured system and cost data to the common system operator and nevertheless the gains from trade such as economy interchange are vital as well.     

Combined genetic algorithm/simulated annealing/fuzzy set approachto short-term generation scheduling with take-or-pay fuel contract

This paper first develops a new formulation for short-term generation scheduling with take-or-pay fuel contract. In the formulation, a fuzzy set approach is developed to assist the solution process to find schedules which meet as closely as possible the take-or-pay fuel consumption. The formulation is then extended to also cover the economic dispatch problem when the fuel consumption is higher than the agreed amount in the take-or-pay contract. The extended formulation is combined with the genetic algorithms and simulated-annealing optimization methods for the establishment of new algorithms for the present problem. The new algorithms are demonstrated through a test example, in which the generation loadings of 13 generators in a practical power system are scheduled in a 24-hour schedule horizon     

A new approach to generation scheduling in interconnected power systems using predictor-corrector proximal multiplier method

The purpose of this paper is to elaborate a new generation scheduling algorithm in the interconnected power systems. Typically, the generation scheduling problem as a mixed integer non-linear programming can be effectively solved by the generalized Benders decomposition technique which decouples an original problem into the master problem and subproblems to tremendously allow fast and accurate solutions of large-scale problems. In order to formulate efficient inter-temporal optimal power flow (OPF) subproblems, we will explore a regional decomposition framework based on predictor-corrector proximal multiplier method. In fact, this scheme can find the most economic generation schedules under the power transactions for a multi-utility system without the exchange of each utility’s own private information and major disruption to existing economic dispatch or OPF adopted by individual utilities.