Simulation of the impact of wind power on the transient fault behavior of the Nordic power system

In this paper the effect of wind power on the transient fault behavior of the Nordic power system is investigated. The Nordic power system is the interconnected power system of the countries Norway, Sweden, Finland and Denmark. For the purpose of these investigations the wind turbines installed and connected in eastern Denmark are taken as study case. The current and future wind power situation in eastern Denmark is modeled and short circuit faults in the system simulated. The simulations yield information on (i) how the faults impact on the wind turbines and (ii) how the response of the wind turbines influences the post-fault behavior of the Nordic power system.     

Scenario selection in composite reliability assessment of deregulated power systems

Power market analysis should be incorporated in reliability assessments of deregulated power systems. For the Nordic power system, this is done by using The Multi-area Power-market Simulator (EMPS) for long-term power market analysis, where EMPS finds the optimal socio-economic dispatch on a weekly basis, with respect to, e.g., hydro reservoir levels. The EMPS analysis results in a set of load and generation scenarios, and these scenarios are interpreted as a sample of future power market behaviour, and is used as basis for a reliability assessment. These load and generation scenarios are referred to as power market scenarios.The power market analysis produces a large number of power market scenarios, and to include all these scenarios in a reliability assessment results in excessive computation time. The scenario selection method is presented and discussed. Scenario selection is used to pick out a subset of the generated power market scenarios, to only use this subset of scenarios as a basis for the reliability assessment. The paper provides some general guidelines for application of the scenario selection method. It is shown that the scenario selection method can reduce the scenario set by about 90%, with little loss of accuracy in the reliability assessment.     

基于风电不确定性的电力系统备用容量获取

针对风电功率预测的不确定性对电力系统备用容量的影响,建立了基于风电不确定性的备用容量获取模型。首先利用场景法模拟生成风电功率、负荷及常规机组的不确定性模型,进而对生成场景进行概率统计得出系统差额概率密度函数,得出系统电量不足期望(EENS)和风能浪费风险(EWWR)指标,并通过EENS和EWWR指标及备用容量成本从系统可靠性和经济性两方面折中进行系统正、负备用容量的确定。最后通过10机系统仿真,验证了该方法在满足可靠性前提下有效地减少了备用成本和弃风量。     

Improving large-disturbance stability through optimal bifurcation control and time domain simulations

This paper presents an approach for improving, through practical assumptions, the stability of power systems subjected to large disturbances. The proposed method is composed of two steps, solved iteratively. The first step solves an optimal bifurcation control problem that guarantees the small-signal stability of the equilibrium point. The proposed optimal bifurcation control addresses saddle-node and Hopf bifurcations. The second step is an N − 1 contingency analysis computed through time domain simulations. The second step guarantees the large-disturbance stability of the equilibrium point. The WSCC 9-bus and New England 39-bus systems are used to illustrate and test the proposed technique.     

A nonlinear two‐cluster Gaussian mixture scenario model for wind power

To overcome the low precision and poor flexibility of the wind power scenario model, this paper proposes a nonlinear two‐cluster Gaussian mixture scenario model for wind power based on the expectation maximization (EM) algorithm according to Wasserstein optimal scenario theory. First, the EM algorithm is used to classify the wind speed data and establish the Gaussian mixture model (GMM). Second, the Wasserstein distance scenarios of two Gaussian distributions with different parameters are calculated based on wind speed data and nonlinear wind turbine power curve, respectively. Finally, a cross combination of the two scenarios is used to obtain the nonlinear two‐cluster mixture scenario model with a mixture Gaussian probability parameters. The obtained results show that the nonlinear two‐cluster Gaussian mixture scenario model is applicable not only to the regular wind speed probability distribution but also to that with irregular and two‐peak characteristics. Moreover, the generated energy deviation can be controlled within 2.5%. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Assessing the benefits of regulating power market integration in Northern Europe

The expected increase of intermittent electricity production from renewable sources in Northern Europe poses rising challenges to the balancing of the power system. The Nordic hydro based power system, particularly the Norwegian, is in a favourable position to provide the necessary balancing services. In order to provide these services to continental Europe an integration of markets for balancing services (regulating power market) might be advantageous. Contemporaneously the European Union enforces the liberalisation and integration of national European power markets, including the regulating power markets. To investigate the possible outcome of such an integrated market, a regulating power market model is developed, which is based on a common day-ahead market, including Nordic and northern continental Europe.The proposed model considers the procurement of regulating reserves as well as their activation, taking into account available transmission capacity. Different steps of regulating power market integration are studied. The analysis confirms, that there is a socio-economic benefit by integrating regulating power markets. The benefit mainly results from a provision of reserve capacity from the Nordic to the continental European power system, the netting of imbalances and hence the reduced activation of regulating reserves in the continental power system.     

电力市场中基于情景分析的电网规划方案适应性

对电网规划方案进行适应性评估是电网规划工作的一个重要补充。在市场环境下,原有的电网规划方案是否适应未来市场交易的要求,是评估工作面临的新挑战。鉴于电力系统以及电力市场中诸多不确定性因素的影响,本文基于电力市场模拟的原理,将情景分析引入到电力市场环境下电网规划方案的适应性评估之中,并以电价不确定性的分析为例,详细描述了电力市场中对不确定性因素进行情景分析的基本思想、方法、流程。文中采用了情景出现概率及其重要程度两个指标来衡量各个情景的评估次序,为从大量情景中进行高效的筛选提供了一个便捷的途径。将该整体思路应用于东北电网规划方案的评估中,结合东北区域电力市场运营规则,进行了2010年电网规划的市场化模拟与评估。实际应用表明,所提出的评估方法能够很好地筛选出电力市场中的重要情景,为市场环境下电网规划方案适应性评估提供了一个有力的工具,具有较大的实用价值。     

基于隐式最大似然估计的风电出力场景生成

随着风电渗透率的日益提高,如何有效地描述风电出力的不确定性成为了配电网运行和规划所面临的巨大挑战,为此,提出一种基于隐式最大似然估计的风电出力场景生成方法。针对风电出力曲线的数据特征,设计适用于风电出力场景生成的损失函数和网络结构。通过无监督训练使得场景生成器能够学习到高斯噪声与风电出力场景之间的映射关系。仅需调节模型中相关的参数,采用所提方法就能够生成不同时间尺度的风电出力场景。仿真结果表明,所提方法的预测区间平均宽度和预测区间覆盖率均优于现有的生成对抗网络,且所提方法对于不同的风电场具有一定的普适性。     

含风电和光伏的可再生能源场景削减方法

以风电和光伏为代表的可再生能源渗透率不断增加,其出力不确定性导致的大规模时序场景给电力系统的优化分析带来很高的计算复杂度。以场景削减技术精准刻画区域风电、光伏出力特性是解决以上问题的有效方法之一。提出一种基于聚类与优化算法相结合的可再生能源场景削减方法。首先对数据进行清洗、降噪等预处理,其次利用肘部法则与轮廓系数判断风电、光伏类别个数并进行聚类。然后,利用粒子群与遗传算法分别提取风电、光伏典型出力曲线,并对两种算法结果进行对比,从而生成典型场景。算例分析以欧洲输电系统运营商Amprion提供的2015年1月1日至2019年12月31日风电、光伏出力数据为研究对象,利用所提方法求得的出力曲线可以有效反映该区域风电、光伏出力典型场景,为后续电力系统规划、运行优化等问题提供数据支撑。     

Modeling Real-Time Balancing Power Market Prices Using Combined SARIMA and Markov Processes

This paper describes modeling of real-time balancing power market prices by using combined seasonal auto regressive integrated moving average (SARIMA) and discrete Markov processes. The combination of such processes allows generation of price series with periods where no demand for balancing power exists. The purpose of the model is simulation of prices to construct scenario trees representing possible realization of the stochastic prices. Such scenario trees can be used in planning models based on stochastic optimization to generate bid sequences to the balancing market. The spread of the prices in the tree and the shape of the scenarios are of central importance. Model parameter estimation methods reflecting the demands on scenario trees have therefore been used. The proposed model is also applied to data from the Nordic power market. The conclusion of this paper is that the developed model is appropriate for modeling real-time balancing power prices.