Probabilistic performance indexes for small signal stability enhancement in weak wind-hydro-thermal power systems

Deterministic strategies are still largely used for small signal stability (SSS) assessment and enhancement in most power systems worldwide. However, the solutions obtained with such strategies are very limited since they are correct just around the particular conditions analysed. Therefore it is essential to develop comprehensive strategies to cope with more operating conditions and random factors in SSS studies. This paper presents the development and application of a probabilistic methodology for SSS assessment and enhancement. The approach accounts for uncertainties of generation and nodal load demands as well as the effects of system element outages. Probabilistic performance indexes based on a combination of Monte Carlo method and fuzzy clustering are calculated. It is shown how properly statistical processing of output variables of interest can be adapted to evaluate the proposed indexes, which are the instability risk index and two additional indexes concerning power system stabiliser location and transfer capability as affected by SSS. The results obtained using a 18-power plant power system are analysed and compared against the results obtained through a deterministic approach. Relevant discussion highlights the viewpoint and effectiveness of the proposed methodology in providing instability risk assessment and useful information that aims at minimising the occurrence and impacts of electromechanical oscillations in the context of power system operation around uncertain load conditions.     

Operating reserve capacity requirements and pricing in deregulated markets using probabilistic techniques

A new probabilistic methodology to evaluate the operating reserve requirements of power systems in deregulated energy markets is presented. The main objectives are the assessment of reserve requirements for all submarkets (i.e. regulation, spinning, non-spinning and replacement), and the determination of the maximum acceptable bid prices in these submarkets and eliminating possible speculations. In order to balance reliability and costs, the proposed methodology is based on merging the loss of load cost index into the capacity bidding process for all operating reserve submarkets, thus avoiding the a priori establishment of an arbitrary risk index as a reference criterion. The results of studies using different test systems, including the IEEE-reliability test system and a configuration of the Brazilian South-Southeastern system, are presented and discussed     

Assessing Performance Risk for Complex Product Development: A Simulation‐Based Model

Assessing and managing performance risk is important for complex product development projects. The performance risk of complex product development can be defined as the probability failing to achieve desired performance level subject to cost and time constraints. This article presents a simulation model based on the graphical evaluation and review technique (GERT) and analyzes the complex product development project using simulation data. The model computes the probability distribution of project duration and cost in a GERT network with multifeedback branches considering activities rework that is caused by probabilistic failure to meet the planned design objective. A simulation strategy is designed to assess the performance risk in both subsystems and system development. With the performance risk assessment methodology, project managers can make a better decision and then minimize the performance risk of product development project. Finally, an obstacle clearance armored vehicle development project is used to illustrate the effectiveness of the proposed model. Copyright © 2012 John Wiley & Sons, Ltd.     

Cooperative Relay Selection Mechanism in Multi-Hop Networks

In this paper, we consider a three-hop relay system based on interference cancellation technique in Underlay cognitive radio (CR) network. Although underlay CR has been shown as a promising technique to better utilize the source of primary users (PUs), its secondary performance will be severely degraded. On one hand, by adapting the Underlay spectrum sharing pattern, secondary users (SUs) would observe the strict power constraints and be interfered by primary users. On the other hand, limited transmit power results in limited transmission range, which greatly degrade the secondary transmission capacity. To solve the problems above, we propose an interference cancellation protocol for multi-hop wireless communication networks in underlay CR, which could develop the long-distance transmission performance and improve the transmission efficiency significantly. As simulation results shows, proposed scheme significantly reduce the secondary outage probability and increase the secondary diversity than the traditional cases.     

Operation margin analysis of zone 3 impedance relay based on sensitivities to power injection

Zone 3 impedance relays (mho relays) on transmission lines have an overreaching protection region. The relays are sensitive to power flow redistribution and to power swing caused by outage or switch operation outside the protected region. Traditionally, the operation margin of mho relays is expressed with impedance. Various load flow schemes that require extensive calculation are necessary to decide the optimal location to control the operation margin. The equivalent expression of the operation margin expressed by a function of bus voltage has been established, and a preventive control model based on the sensitivities of the operation margin to power injection has been proposed. On the basis of the simulation results on the IEEE 14-bus test system, it has been found that: (1) the operation margin can be effectively controlled using the sensitivity method; (2) active and reactive power controls at the same bus may yield opposite control effects; (3) the proposed method is especially effective for stressed power systems; (4) relative control error with is very small as compared to the load flow method and (5) the calculation efficiency is much higher than that of the load flow method     

Short-term hydrothermal optimisation with congestion and quality of service constraints

In short-term hydrothermal coordination (STHC), the transmission network is typically modelled through a DC power flow. However, this modelling can lead to inoperable solutions when verifying with AC power flow. A methodology that includes an AC power flow model to overcome the problem applied to STHC is presented. The approach takes into account issues such as congestion management and control of quality of service, which are often present in large and weakly meshed networks - the typical pattern of Latin American electrical power systems. Generalised Benders- decomposition together with more traditional and well-known optimisation techniques, is used for this problem. The master problem stage defines the generation levels by considering the inter-temporal constraints, whereas the sub-problem stage determines both the active and reactive economical dispatches for each step of the load curve. It meets the electrical constraints (nodal balance, transmission limits and voltage levels) through a modified AC optimal power flow. The methodology was proved over a nine-busbar hydrothermal system and the solution found was validated with a quasi-exhaustive enumeration procedure to prove the optimality of the solution. Also proved over large system was the feasibility to realistic systems.     

高强度钢板U形件热冲压凹模结构拓扑优化

为降低热冲压凹模的生产成本和使用成本,基于板料热冲压数值模拟对凹模结构进行了拓扑优化设计.运用有限元软件ABAQUS建立热力耦合有限元模型,对高强钢板U形件的热冲压成形和淬火过程进行了数值仿真.提取凹模与板料间关键工况下接触应力作为凹模拓扑优化的外在载荷,建立约束凹模结构关键区域节点位移的体积最小化拓扑模型,对热冲压凹模结构进行拓扑优化设计,最终实现结构减重20%,且优化后凹模的变形和应力与优化前的结果相差甚微.研究内容对热冲压过程数值模拟和模具结构拓扑优化研究具有一定参考价值.     

Nodal congestion price estimation in spot power market using artificial neural network

In the world wide increasing trend of restructured power system, open access in transmission system and competition in generation and distribution have introduced a frequently occurring problem of congestion. To establish a proficient price-based congestion management procedure, the nodal pricing strategy is found to be appropriate. From congestion management point of view, the optimal nodal prices are comprised of two basic components. First component is locational marginal price, that is marginal cost of generation to supply load and transmission losses both. Second component is nodal congestion price (NCP), that is the charges to maintain network security. Levenberg-Marquardt algorithm based neural network (LMANN) for estimating NCPs in spot power market by dividing the whole power system into various congestion zones is presented. Euclidian distance based clustering technique has been applied for feature selection before employing LMANN. The purpose of using artificial neural network (ANN) based approach for NCP estimation in spot power market is to exploit the tolerance for any missing or partially corrupted data to achieve tractability, robustness and very fast solution. The proposed ANN method also handles the congestion price volatility by taking continuously varying load and constrained transmission into account. The information provided by the proposed method regarding the formation of different congestion zones and the severity of congestion within a zone instructs both the market participants as well as independent system operator in making effective decisions. The proposed method has been examined for an RTS 24-bus system and is found to be quite promising.     

Impairments Approximations in Assembled mmWave and Radio Over Fiber Network

The fiber nonlinearity and phase noise (PN) are the focused impairments in the optical communication system, induced by high-capacity transmission and high laser input power. The channels include high-capacity transmissions that cannot be achieved at the end side without aliasing because of fiber nonlinearity and PN impairments. Thus, addressing of these distortions is the basic objective for the 5G mobile network. In this paper, the fiber nonlinearity and PN are investigated using the assembled methodology of millimeter-wave and radio over fiber (mmWave-RoF). The analytical model is designed in terms of outage probability for the proposed mmWave-RoF system. The performance of mmWave-RoF against fiber nonlinearity and PN is studied for input power, output power and length using peak to average power ratio (PAPR) and bit error rate (BER) measuring parameters. The simulation outcomes present that the impacts of fiber nonlinearity and PN can be balanced for a huge capacity mmWave-RoF model applying input power carefully.     

Three-phase balancing of distribution feeders using immune algorithm

The immune algorithm (IA) is proposed to derive the rephasing strategy arrangement of laterals and distribution transformers to enhance three-phase balancing of distribution systems. The multi-objective function is formulated by considering the unbalance of phasing currents, the customer service interruption cost (CIC) and labour cost to perform the optimal rephasing strategy. For each feasible rephasing strategy, the number of customers affected with total interruption load demand and outage duration time are used to calculate the impact of system reliability because of rephasing engineering works. To demonstrate the effectiveness of the proposed methodology, a practical distribution feeder in Taipower with 271 customers is selected for computer simulation. By minimising the objective function subjected to the operation constraints, the rephasing strategy has been derived by selecting the laterals and distribution transformers for phasing adjustment. It is found that the neutral current of test feeder has been reduced to be less than the neutral overcurrent limit by executing the rephasing of laterals and distribution transformers.     

Evaluation of the marginal outage costs in generating systems using quantitative power system reliability techniques

Marginal outage costs are an important component of electricity spot prices. This paper describes a methodology based on quantitative power system reliability techniques for calculating these costs in generating systems. The proposed method involves the calculation of the incremental expected unserved energy at a given operating reserve and lead time and the multiplication of this value by the average cost of unserved energy of the generating system. The method is illustrated in this paper by calculating the marginal outage cost profile of a small reliability test system. The effects of selected modelling assumptions and the accuracy of a number of approximate methods for calculating the marginal outage cost are also examined. © 1998 John Wiley & Sons, Ltd.     

A multiperiod stochastic production planning and sourcing problem with service level constraints

We study a stochastic multiperiod production planning and sourcing problem of a manufacturer with a number of plants and/or subcontractors. Each source, i.e. each plant and subcontractor, has a different production cost, capacity, and lead time. The manufacturer has to meet the demand for different products according to the service level requirements set by its customers. The demand for each product in each period is random. We present a methodology that a manufacturer can utilize to make its production and sourcing decisions, i.e., to decide how much to produce, when to produce, where to produce, how much inventory to carry, etc. This methodology is based on a mathematical programming approach. The randomness in demand and related probabilistic service level constraints are integrated in a deterministic mathematical program by adding a number of additional linear constraints. Using a rolling horizon approach that solves the deterministic equivalent problem based on the available data at each time period yields an approximate solution to the original dynamic problem. We show that this approach yields the same result as the base stock policy for a single plant with stationary demand. For a system with dual sources, we show that the results obtained from solving the deterministic equivalent model on a rolling horizon gives similar results to a threshold subcontracting policy. Correspondence to: Fikri KaraesmenThe authors are grateful to Yves Dallery for his ideas, comments and suggestions on the earlier versions of this paper.     

基于改进遗传算法的光伏系统储能优化配置

为应对光伏发电随机性及波动性对电力系统造成的不利影响,可以从系统概率潮流角度分析光伏出力特征,进而研究储能的接入对于抑制该影响的可行方案.首先,建立概率潮流元件分布模型和储能选址定容模型,采用随机行走理论和拉丁超立方理论进行样本分析和排序;其次,以降低储能投资成本、降低支路有功越限概率和减少网络损耗作为优化目标函数并进...     

Transaction charges allocation using sensitivity factor methodology

Deregulation of the electricity industry aims for creating a competitive market to trade electricity, which generates a host of new technical challenges among market participants and power system researchers. One of the major challenges is to establish a cost for system services on a non-discriminatory basis. In this paper, the evaluation of transmission cost is proposed based on sensitivity factor method like AC Power Transfer Distribution Factor (ACPTDF) method for bilateral and multilateral transactions. The transacted power is estimated by ACPTDF method for each transaction. The advantages of the proposed methodology are demonstrated on a sample 6 bus, IEEE 30 bus and Indian Utility 69 bus systems. The solution provides a better pricing approach that can impact a more reasonable economic indicator for transmission cost.     

Comparison of risk-based and deterministic security assessments

The traditional N - 1 security criterion provides only a limited perspective on the actual level of security of a power system and a risk-based approach to security assessment provides considerably more information on which to base operating decisions. It further argues that this risk should be measured in terms of expected outage costs to the consumers. Furthermore, the risk calculation should not be limited to the consideration of a predefined set of contingencies but should factor in the actual probabilities of outages leading to load disconnections. A case study based on the IEEE-Reliability Test System shows that different operating points on the system's deterministic security boundary have very different levels of risk. For a given operating point, the risk level changes considerably between fair, average and bad weather conditions. Finally, the paper shows how, using adaptive deterministic security boundaries, it is possible to compare the cost and benefit of relaxing operating limits.     

Corrected transient energy function-based strategy for stability probability assessment of power systems

A new model describing the uncertainty of fault clearing time for probabilistic transient stability assessment of power systems is proposed. In this, a corrected transient energy function-based strategy is developed to evaluate the probabilistic instability index of systems. The advantage of this approach is that evaluations of critical clearing time in the system stability probability assessment are only conducted for very severe contingencies, an extremely small fraction of all considered contingencies. Hence, the computation efficiency has been remarkably enhanced. Case studies on a representation of the North China power system are reported to show that the proposed assessment strategy is effective and practical.     

考虑运行风险的含储能综合能源系统优化调度

为解决综合能源系统（integrated energy system,IES）中供需双侧不确定因素对运行调度带来的风险问题,提出了一种考虑运行风险的含储能IES优化调度模型。在目标函数中,用设备调整费用、失负荷惩罚费用和弃风弃光惩罚费用来量化系统运行风险。在约束条件中,区分了电能和热能的时间尺度差异,并计及储能的时间耦合性,建立了储能多时段耦合约束。然后提出了一种基于Benders分解的算法进行求解。最后通过算例分析了置信水平、储能功率及容量对IES运行费用及运行风险的影响。     

Independent marginal losses with application to locational marginal price calculation

A new kind of power system marginal loss (or loss sensitivity) for nodal MW/Mvar is developed. First the electricity transmission loss is expressed in terms of source currents. It is thus an analytical function. Then the marginal loss with respect to source current is derived based on calculus and vector algebra. Using each source/load power represents its nodal injection current, the marginal loss with respect to source current is then transformed into the marginal loss with respect to source/load power. The new kind of marginal loss is based on load flow solution. It is exact in algorithm and independent of reference bus, thus called independent marginal loss (IML). The IML exactly leads to double collection of actual system loss. It makes loss components of locational marginal price small in spatial fluctuation compared to the existing marginal losses. Numerical examples including the IEEE 118-bus and PJM [Note 1] 5-bus systems are presented to demonstrate the calculation and effectiveness of the IML.     

Genetic algorithm optimisation of the maintenance scheduling of generating units in a power system

A new method for optimisation of the maintenance scheduling of generating units in a power system is developed. Maintenance is scheduled to minimise the risk through minimisation of the yearly value of the loss of load expectation (LOLE) taken as a measure of the power system reliability. The proposed method uses genetic algorithm to obtain the best solution resulting in a minimal value of the annual LOLE value for the power system in the analysed period. The operational constraints for generating units are included in the method. The proposed algorithm was tested on a Macedonian power system and the obtained results were compared with the results received from the approximate methodology. The results show the improved reliability of a power system with the maintenance schedule obtained by the new method compared to the results from the approximate methodology.