Thermal rating assessment of overhead lines by Affine Arithmetic

The increasing complexity of transmission networks can raise significantly the load flows during and following serious system disturbances. In this context accurate thermal rating assessment of overhead lines represents an essential requirement in order to obtain a sensible increase of the infrastructure exploitation assuring at the same time a reliable functioning of the power networks.This necessitates reliable calculation models which should be able to predict the thermal behaviour on short and long time horizons and in the presence of data uncertainties deriving from several sources such as non stationary load and fluctuating operating conditions.To address this problem, in the paper the use of Affine Arithmetic, an enhanced model for numerical computation, is proposed. Using AA, the thermal rating solution is computed taking into account the model parameter uncertainty interdependencies as well as the diversity of uncertainty sources.Simulation studies are presented and discussed in order to prove the effectiveness of the proposed methodology in addressing the problem of uncertainty analysis in both static and dynamic thermal rating assessment.     

A framework for uncertainty quantification and economic dispatch model with wind–solar energy

More and more renewable energy generations are being connected to power system, such as wind power, solar power, together with the load forecasting deviation, so there is a growing need to study impacts of multiple different uncertainties on system. It is important that operators understand how these stochastic characteristics of uncertainties affect the stable operation of power system. In this paper, the combinations of uncertainties that are power fluctuation due to forecasting deviation of wind speed, solar radiation and load. Framework is established including joint probabilistic models of several uncertainties and the risk models of load shed under two different scenarios. An economic dispatch model considering unit commitment is proposed to minimize the generation cost and operational cost and starting-up cost of conventional power units, combined heat and power (CHP) units and heat-only units. However, high/low risk of load shed does not represent large/small of load loss in fact, thus the load loss is defined as multiplying of load shed risk and load loss amount, which is described by methodology of α-superquantile. Effectiveness of proposed model is examined by case studies and the numerical results are presented.     

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.     

基于样本熵的新能源电力系统净负荷分时段调度

新能源电力系统源—荷功率具有强不确定性,采用经典的日前调度策略,传统火电机组出力将随净负荷的波动而频繁调整,影响发电设备运行效率和系统运行的经济性,甚至需要改造火电机组,以适应系统能量平衡控制要求。提出一种基于样本熵的新能源电力系统净负荷分时段调度策略。该策略最大化可再生能源利用效率,基于样本熵理论,评估净负荷时间序列复杂度,以此确定火电机组运行模式,并对调度时段进行适应性划分,有效地减少火电机组随系统净负荷波动产生的上、下行爬坡功率,同时增加抽水蓄能机组的参与度。文中以十机组测试系统为例,验证了调度策略的合理性和有效性。     

Analysis of interruptible electric power in deregulated power systems

Assuring appropriate levels of generation capacity adequacy at the minimum possible cost using market-based approaches is a contemporary issue attracting much attention in deregulated power systems. Introduction of interruptible electricity contracts could provide a possible solution to such a problem. However, theoretical frameworks for examining the impacts of these contractual arrangements on system operations have not been maturely developed. This paper presents a probabilistic production simulation based framework for modeling and analyzing interruptible electricity contracts. The interdependence between the pricing models of interruptible electric power and the operations of the whole system is addressed and solved by an iterative coordinating algorithm. The probabilistic production simulation framework allows the uncertainties inherent in both the forced outages of generators and system load demand at the contract delivery time to be taken into account. The proposed approach is capable of achieving comprehensive analysis and systematic pricing for interruptible electric power. A numerical case study is presented to illustrate the effectiveness and validity of the methodology.     

A fuzzy logic controlled superconducting magnetic energy storage,SMES frequency stabilizer

This paper presents application of fuzzy logic controlled superconducting magnetic energy storage device, SMES to damp the frequency oscillations of interconnected two-area power systems due to load excursions. The system frequency oscillations appear due to load disturbance. To stabilize the system frequency oscillations, the active power can be controlled via superconducting magnetic energy storage device, SMES. The error in the area control and its rate of change is used as controller input signals to the proposed fuzzy logic controller. In order to judge the effect of the proposed fuzzy logic controlled SMES, a comparative study is made between its effect and the effect of the conventional proportional plus integral (PI) controlled SMES. The studied system consists of two-area (thermal–thermal) power system each one equipped with SMES unit. The time simulation results indicate the superiority of the proposed fuzzy logic controlled SMES over the conventional PI SMES in damping the system oscillations and reach quickly to zero frequency deviation. The system is modeled and solved by using MATLAB software.     

基于信息间隙决策理论的电网负荷恢复鲁棒优化

停电电网的恢复过程中,负荷恢复的不确定性可能影响电网恢复过程的安全,需要在负荷恢复中考虑负荷的不确定性。考虑到准确的负荷不确定性分布模型难以获取,文中提出了基于信息间隙决策理论(IGDT)的电网负荷恢复鲁棒优化方法,使负荷恢复方案在负荷波动范围内均能满足要求,而无需已知负荷的不确定性分布。首先,基于IGDT,将确定性负荷恢复优化模型转变为在负荷波动范围内均能达到最低恢复要求的鲁棒优化模型,同时综合考虑负荷恢复过程中的负荷最大恢复量、单次最大投入量、电网潮流等约束条件,再利用人工蜂群算法对优化模型进行求解,最后以新英格兰系统和江苏系统为例验证了所提方法的有效性。     

Short term hydro–wind–thermal scheduling based on particle swarm optimization technique

Hydro–wind–thermal scheduling is one of the most important optimization problems in power system. An aim of the short term hydrothermal scheduling of power systems is to determine the optimal hydro, wind and thermal generations in order to meet the load demands over a scheduled horizon of time while satisfying the various constraints on the hydraulic, wind and thermal power system network. In this paper we present optimal hourly schedule of power generation in a hydro–wind–thermal power system applying PSO technique. The simulation results inform that the proposed PSO approach appears to be the powerful to minimize fuel cost and it has better solution quality and good convergence characteristics than other techniques.     

火电厂厂级负荷分配的多目标优化和决策研究

火电厂的负荷优化分配系统通常是以机组煤耗特性为基础的,其经济分配对应于满足稳态工况下全厂发电成本最低的要求。对于自动发电控制方式下的厂级负荷运行分配还要满足调整时间的要求,以尽可能快的速度满足目标负荷的调整。考虑机组运行的经济性和快速性,将基于进化算法的多目标优化技术与多属性决策方法联合运用,针对火电厂厂级负荷优化分配的问题进行研究。对于多目标优化问题,采用改进的非支配解排序的多目标遗传算法,求出Pareto最优解,由Pareto最优解构成决策矩阵,使用客观赋权的信息熵方法对最优解的属性进行权值计算,然后用逼近理想解的排序方法进行多属性决策研究,对Pareto最优解给出排序。文中给出了10台机组负荷分配的优化设计算例。     

AI approach to optimal VAr control with fuzzy reactive loads

This paper presents an artificial intelligence (AI) approach to the optimal reactive power (VAr) control problem. The method incorporates the reactive load uncertainty in optimizing the overall system performance. The artificial neural network (ANN) enhanced by fuzzy sets is used to determine the memberships of control variables corresponding to the given load values. A power flow solution determines the corresponding state of the system. Since the resulting system state may not be feasible in real-time, a heuristic method based on the application of sensitivities in an expert system is employed to refine the solution with minimum adjustments of control variables. Test cases and numerical results demonstrate the applicability of the proposed approach. Simplicity, processing speed and ability to model load uncertainties make this approach a viable option for online VAr control     

Multi-objective market clearing of electrical energy,spinning reserves and emission for wind-thermal power system

This paper proposes energy and spinning reserve market clearing mechanism for wind-thermal power system, including uncertainties in wind power generation and load demand forecasts. The impact of wind power and load demand volatility on the energy and spinning reserve market is taken into account. This paper considers reserve offers from the conventional thermal generators. The stochastic behavior of wind speed, and wind power is represented by Weibull probability density function (PDF), and the load demand uncertainty is represented by Normal PDF. This paper considers two objectives: energy and spinning reserves cost minimization, and emission minimization. The energy and spinning reserves cost minimization objective includes cost of energy provided by conventional thermal generators and wind generators, cost of reserves provided by conventional thermal generators. It also includes costs due to over-estimation and under-estimation of available wind power, and load demand. The proposed market clearing model provides a compromise solution by optimizing both the objectives simultaneously using multi-objective Strength Pareto Evolutionary Algorithm 2+ (SPEA 2+). The effectiveness of the proposed approach is established from the results on IEEE 30 bus system.     

Available transfer capability and first order sensitivity

A method of calculating available transfer capability and the exploration of the first order effects of certain power system network variables are described. The Federal Energy Regulatory Commission has ordered that bulk electrical control areas must provide to market participants a “commercially viable” network transfer capability for the import, export and throughput of energy. A practical method for deriving this transfer capability utilizing both linear and nonlinear power flow analysis methods is developed that acknowledges both thermal and voltage system limitations. The available transfer capability is the incremental transfer capability derived by the method reduced by margins. A procedure for quantifying the first order effect of network uncertainties such as load forecast error and simultaneous transfers on the calculated transfer capability of a power system snapshot are explored. The quantification of these network uncertainties can provide information necessary for system operation, planning and energy market participation     

基于DW分离模糊负荷模型的无功功率优化

提出了一种大区域电网无功功率/电压最优化控制的数学模型,其目的是研究在当前时段内各负荷值的情况下使功率损耗最小.该模型运用模糊集理论,结合DW分离法,成功地解决了多目标优化中描述不确定性以及处理不同量纲相互矛盾的问题,另一方面降低了问题计算的复杂度.算例表明,该模型具有较强的适应性和通用性,在全局收敛性、算法复杂度及运算效率等方面显示了一定的优势,为系统在各负荷值条件下的性状提供了总的解答.     

基于相变储能系统主动响应能力挖掘的配电网经济调度

为了解决配电网面临的供电电压不合格和潮流分布欠优等问题,提出基于相变储能系统(PCMTESS)需求响应的配电网经济调度策略。介绍PCMTESS的构造和工作机理,分析热力侧的能耗规律,建立计及热耗散的热力侧和计及无功调节能力的电力侧封装模型。在此基础上,考虑潮流分布约束和分布式新能源出力特性,以配电网的购电成本最小化为目标,在综合考虑光伏、风机、负荷不确定性的条件下,建立统一的配电网调度模型。提出主、子问题交互迭代的求解策略,实现优化模型的高效求解。基于IEEE 41节点配电网的仿真结果表明,所提PCMTESS在维持室温舒适的前提下,能够优化配电网的潮流分布和改善电网的电能质量;所提调度模型为配电网的安全经济调度和综合能源消纳问题的解决提供了一个崭新的视角。     

计及不确定性的区域综合能源系统双层优化配置规划模型

针对综合能源系统规划运行时缺乏对负荷、可再生能源预测误差和购能价格波动不确定性的考虑,构建了基于粒子群优化-区间线性规划的双层优化模型,用于求解计及不确定性的综合能源系统规划问题。为了说明所提优化配置模型能够显著提高系统运行的灵活性,给出了评价系统参与需求响应项目的潜力指标,量化分析了系统在响应电网削负荷指标和应对购能价格变化方面的优势。算例结果不仅验证了所提模型的有效性和可行性,还表明了在能源互联替代的背景下,天然气价格和电负荷的波动直接影响能源服务公司的收益区间,可通过所提模型优化配置各类储能设备以提高能源利用率、抑制系统运营收益的波动。     

Load frequency control of a realistic power system with multi-source power generation

In this paper, load frequency control (LFC) of a realistic power system with multi-source power generation is presented. The single area power system includes dynamics of thermal with reheat turbine, hydro and gas power plants. Appropriate generation rate constraints (GRCs) are considered for the thermal and hydro plants. In practice, access to all the state variables of a system is not possible and also their measurement is costly and difficult. Usually only a reduced number of state variables or linear combinations thereof, are available. To resolve this difficulty, optimal output feedback controller which uses only the output state variables is proposed. The performances of the proposed controller are compared with the full state feedback controller. The action of this proposed controller provides satisfactory balance between frequency overshoot and transient oscillations with zero steady state error in the multi-source power system environment. The effect of regulation parameter (R) on the frequency deviation response is examined. The sensitivity analysis reveals that the proposed controller is quite robust and optimum controller gains once set for nominal condition need not to be changed for ±25% variations in the system parameters and operating load condition from their nominal values. To show the effectiveness of the proposed controller on the actual power system, the LFC of hydro power plants operational in KHOZESTAN (a province in southwest of Iran) has also been presented.     

Effects of load modeling on minimum loss,minimum emission,and multiple-objective optimal hydrothermal power flow

The effects of incorporating load models in three formulations of hydrothermal optimal power flow are considered in this paper. The formulations are transmission loss minimization, NO_x minimization, and the multiple objectives of minimum NO_x emission and minimum cost. The conventional algorithms and those incorporating load models were tested using a 14-bus and a 30-bus test system. Solutions are obtained using the MINOS optimization package. The computation time requirements of the conventional algorithm are lower than those incorporating load models. In all cases, there are measurable differences in the optimal voltage magnitudes for the systems tested. Incorporating load models yields lower active power generations and transmission losses, lower thermal fuel costs and reduced environmental impact than the conventional formulations.     

基于结构化负荷模型的电力负荷概率区间预测

为了考虑电力负荷的不确定性,概率和区间预测成为电力负荷预测的重要方式之一。针对传统的负荷概率及区间预测方法没有考虑不同负荷成分的不确定性对电力负荷影响的问题,在分析电力负荷成分的基础上,基于结构化电力负荷模型提出一种电力负荷概率及区间预测方法。首先,对电力负荷的成分进行分析,针对不同负荷成分分别进行建模,构成结构化电力负荷模型;然后,基于历史负荷数据采用变分贝叶斯估计算法训练模型参数的后验概率分布;最后,基于训练完成的模型对未来负荷的概率分布进行预测,从而实现电力负荷概率区间预测。采用实际电力负荷数据进行验证,并与其他方法进行对比。实验结果表明,所提方法取得了较高的预测区间覆盖率和较窄的预测区间宽度。     

计及需求侧响应日前-日内两阶段鲁棒备用优化

为增强电力系统应对不确定性因素的能力,提高电网运行效率,提出一种计及需求侧响应日前—日内两阶段鲁棒备用优化模型。一方面,在模型中协同优化价格型与激励型需求侧响应提高电网运行的灵活性;另一方面,综合考虑风电出力不确定性与电力设备N-k强迫停运,增强电力系统应对不确定性因素的鲁棒性。基于鲁棒模型对系统运行备用进行优化,最小化电网在最恶劣运行场景下的调整成本,保证电网的安全可靠运行,并采用列和约束生成算法对两阶段三层优化问题进行求解。修改的6节点系统与IEEE RTS-79测试系统算例验证了所提模型与算法的有效性。结果表明,综合考虑多重不确定性因素进行备用优化,可以提升电网应对极端运行场景的能力;同时,需求侧响应的实施可以大大提高电网运行的灵活性。其中,激励型需求侧响应通过直接控制负荷,对于增强电网运行鲁棒性的作用更加明显;而电价型需求侧响应在要求保障负荷供电的场景下更为适用。     

考虑源荷不确定性的风光火储系统低碳经济调度

为提高以新能源为主体的新型电力系统运行的低碳经济性和能源利用率,提出一种考虑源荷不确定性的风光火储发电系统低碳经济调度模型。将碳交易成本引入传统经济调度中,细化碳排放源;用随机机会约束处理源荷两侧不确定性;立足供给电源侧资源禀赋来改善清洁能源的波动性和消纳率。以IEEE 30节点系统进行算例分析,通过随机模拟粒子群算法对模型进行求解,结果证明所提调度模型可减少碳排放量、提升系统的经济运行、促进新能源消纳。