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.     

Reliability assessment of restructured power systems using optimal load shedding technique

Power systemrestructuring and deregulation has changed the strategy of reliabilitymanagement of a power system. Load shedding, and generation and reserve re-dispatch methods used in the existing reliability evaluation techniques have to be improved to incorporate these changes. An optimisation technique, incorporating those changes, is proposed in this study to determine load curtailment and generation re-dispatch for each contingency state in the reliability evaluation of restructured power systems with the Poolco market structure. The problem is formulated using the optimal power flow (OPF) technique. The objective of the problem is to minimise the total system cost, which includes generation, reserve and interruption costs, subject to market and network constraints. A model for the contingency management of a Poolco power market is presented to include generation and reserve biddings, reliability considerations and transmission network constraints in reliability evaluation. Both supply side reliability for a generation company (Genco) and demand-side reliability for a customer can be calculated using the technique. The proposed technique can be used to evaluate both conventional and restructured power systems, and can provide both economic and reliability information for the independent system operator to manage system reliability, for Gencos to enhance their reliability, and for customer to select suppliers. The modified IEEE-RTS with the Poolco market has been analysed to illustrate the techniques. The results obtained using the proposed technique have been compared with those from the existing load shedding techniques.     

泛在电力物联网在电力市场应用中的展望

随着电力体制改革的不断深化,电力用户借助分布式发电、储能系统和电动汽车等新兴技术已经具备了参与电力交易的能力,但传统电力系统的运行控制方式却难以适应新时代开放电力市场的需求。国家电网有限公司所提出的泛在电力物联网（ubiquitous power internet of things,UPIoT）战略可以实现电力系统各环节互连、状态全面感知和优化控制,是建设开放电力市场的有效技术支撑。基于此,分析了新时代电力系统发展所面临的挑战以及建设泛在电力物联网的必要性;研究了泛在电力物联网在开放电力市场中的典型应用;对面向电力市场的泛在电力物联网关键技术进行了讨论,为构建现代化开放电力市场提供参考。     

Towards reactive power markets

Two major contributions are discussed in this part of a two-part set. first, it presents a new concept of market reactive power requirement (qreq) for every participant in both bilateral and pool markets. this qreq is defined as the reactive power loss allocation to each bilateral transaction using current adjustment factor (CAF) method that has been proposed in part 1. when a transaction is allowed to provide reactive power more than its qreq, it contributes to system reactive power needs and it is considered a reactive power provider. on the other hand, if it cannot produce its qreq, it relies on other reactive power sources to ship its contracted power and it is considered a reactive power consumer even though it may generate some reactive power. the concept then is extended to participants in a pool market. secondly, this paper proposes a new general concept of differentiated reactive power requirements for every participant in electricity markets. it assumes that qreq of a participant depends on its allocated losses using any appropriate loss allocation method. the proposals help system operators and market participants to trade reactive power as well as real power effectively and fairly. the simulation results show validity and consistency of the proposals.     

Re-defining the reactive power dispatch problem in the context of competitive electricity markets

This study proposes a novel reactive power dispatch model that takes into account both the technical and economical aspects associated with reactive power dispatch in the context of the new operating paradigms in competitive electricity markets. The main objective of the proposed model is to minimise the total amount of dollars paid by the system operator to the generators for providing the required reactive power support. The real power generation is decoupled and assumed fixed during the reactive power dispatch procedures; however, because of the effect of reactive power on real power, a re-schedule in the real power generation is allowed within given limits. The 32-bus CIGRE benchmark system is used to illustrate the proposed reactive power dispatch technique. The developed model is generic in nature and designed to be adopted by system operators in any electricity market structure, as demonstrated by its application to Ontario's grid considering its market rules for reactive power payments.     

浅析电力计量的标准化管理

电能在日常生活中是一种必不可少的能源,电能的商品化是现代电力市场的主要特点之一。电力计量则是衡量用户用电情况的最直接方式,同时计量的标准化程度也是衡量供电企业的服务水平的重要标准。电力计量的标准化管理主要包括技术标准化、管理标准化、人员与服务标准化等等。本文首先通过对电力计量的特点及常用的计量技术进行简单分析与介绍,进而引出电力计量标准化管理的概念,并展开分析介绍。     

A heuristic for formulating within-plant manufacturing focus

The concept of manufacturing focus suggests that each plant is assigned a unique set of manufacturing tasks derived from the firm's competitive strategy. Many empirical studies have verified the importance and benefits of manufacturing focus in enhancing a firm's competence in the market. Nonetheless there is no methodology offered for designing such a manufacturing system with considerations of resource requirements although the need has been recognized. In this study, we propose a methodology that can help managers arrive at a manufacturing focus design within a plant. Because of the large size and nonlinear nature of the problem, a heuristic solution is proposed. The heuristic translates the strategic concept of competitive priorities into management parameters, thereby allowing incorporation of market factors into manufacturing process design. Experimental results show that the proposed methodology offers managers the opportunity to generate and assess alternative focus designs which are otherwise unavailable. The use of the heuristic is straightforward in practical situations and should greatly facilitate the achievement of manufacturing focus with minimal resource requirements. Overall, this research provides an analytical framework for further research in focused manufacturing.     

Swarm intelligence-based strategic bidding in competitive electricity markets

In the competitive electricity markets, formation of supply bid is one of the main concerns, where suppliers have to maximise their profit under incomplete information of other competing generators. An environment is described in which suppliers bid strategically to sell electricity in a pool market. The bidding decision is optimised from a single supplier's viewpoint in both block-bid and linear-bid models of an electricity market. To include uncertain behaviour of other competing suppliers, two different probabilistic models are used. Their bids are constructed using probability distribution functions obtained from the decision-maker's observations of historical market data. Single supplier's decision-making problem is solved by a modern population-based heuristic algorithm, known as particle swarm optimisation (PSO). Search procedure of PSO is based on the concept of combined effect of cognitive and social learning of the members in a group. The effectiveness of the proposed method is tested with examples and the results are compared with the solutions obtained using the genetic algorithm approach.     

Jaya Learning-Based Optimization for Optimal Sizing of Stand-Alone Photovoltaic,Wind Turbine,and Battery Systems

Renewable energy sources (RESs) are considered to be reliable and green electric power generation sources. Photovoltaics (PVs) and wind turbines (WTs) are used to provide electricity in remote areas. Optimal sizing of hybrid RESs is a vital challenge in a stand-alone environment. The meta-heuristic algorithms proposed in the past are dependent on algorithm-specific parameters for achieving an optimal solution. This paper proposes a hybrid algorithm of Jaya and a teaching–learning-based optimization (TLBO) named the JLBO algorithm for the optimal unit sizing of a PV–WT–battery hybrid system to satisfy the consumer’s load at minimal total annual cost (TAC). The reliability of the system is considered by a maximum allowable loss of power supply probability (LPSP_max) concept. The results obtained from the JLBO algorithm are compared with the original Jaya, TLBO, and genetic algorithms. The JLBO results show superior performance in terms of TAC, and the PV–WT–battery hybrid system is found to be the most economical scenario. This system provides a cost-effective solution for all proposed LPSP_max values as compared with PV–battery and WT–battery systems.     

电动汽车参与风电场输出功率波动平抑方法研究

由于风电固有的随机性与间歇性,使得风电场输出功率往往具有较大的波动。然而考虑到储能装置的昂贵成本,单独为风电场配置储能装置不利于其经济运行。为此,文中针对考虑电动汽车参与的风电场输出功率波动平抑方法进行了研究。根据国家标准中风电“有功功率变化”的要求,通过爬坡率概念来描述风电场输出功率变化率。采用鲁棒优化的方法处理风电出力的不确定性,建立风电机组和电动汽车协调控制的双层优化模型：上层模型决策者是风电场,以风电场售电收益最大化为目标函数;下层模型决策者是电动汽车车主,以电动汽车电费支出成本最小化为目标函数。通过线性规划对偶定理和Karush-KuhnTucker（KKT）最优性条件将此鲁棒优化模型转化为混合整数线性规划问题进行求解。最后,通过仿真结果验证了所提模型和方法的有效性。     

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     

A model for the seismic reliability assessment of electric power transmission systems

A comprehensive model to evaluate the seismic reliability of electric power transmission systems is presented. The model provides information on the probability of structural failure of critical equipment at the major substations, from which the corresponding probabilities of power disruption to a given service area are determined. With the proposed methodology earthquake ground motions are defined as stochastic processes, and seismic capacities of electrical equipment are determined on the basis of available test data and simple modeling, from which fragility functions of critical equipment and specific substations are developed. Probabilities of power disruption resulting from network disconnectivity and abnormal power flow are assessed through Monte Carlo simulation. As a case study, the proposed model is applied to the electric power network in San Francisco and vicinity under the 1989 Loma Prieta earthquake, and the probabilities of power interruption are contrasted with the actual power failures observed during that earthquake.     

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.     

Enhanced reliability analysis method for multistate systems with epistemic uncertainty based on evidential network

Evidential network is considered to have superiority in conducting reliability analysis for complex engineering systems with epistemic uncertainty. However, existing methods tend to result in combinational explosion when multistate systems are involved in the reliability analysis, which means the reliability analysis cost increases exponentially with the number of components and that of functioning states. Therefore, an enhanced reliability analysis method is proposed in this paper for reliability analysis and performance evaluation of multistate systems with epistemic uncertainty, through which the combination explosion can be significantly alleviated. Firstly, the functioning states of each component are sequenced according to utility functions. Secondly, the basic belief assignment (BBA) of each component is reassigned in terms of commonality function, through which the BBA defined in the power set space is represented by two extreme BBA distributions defined in the frame of discernment. Thirdly, the reliability intervals of the system states are calculated through evidential network, and the system performance level is computed. Two multistate system numerical examples are investigated to demonstrate the effectiveness and efficiency of the proposed method.     

One step-ahead ANFIS time series model for forecasting electricity loads

In electric industry, electricity loads forecasting has become more and more important, because demand quantity is a major determinant in electricity supply strategy. Furthermore, accurate regional loads forecasting is one of principal factors for electric industry to improve the management performance. Recently, time series analysis and statistical methods have been developed for electricity loads forecasting. However, there are two drawbacks in the past forecasting models: (1) conventional statistical methods, such as regression models are unable to deal with the nonlinear relationships well, because of electricity loads are known to be nonlinear; and (2) the rules generated from conventional statistical methods (i.e., ARIMA), and artificial intelligence technologies (i.e., support vector machines (SVM) and artificial neural networks (ANN)) are not easily comprehensive for policy-maker. Based on these reasons above, this paper proposes a new model, which incorporates one step-ahead concept into adaptive-network-based fuzzy inference system (ANFIS) to build a fusion ANFIS model and enhances forecasting for electricity loads by adaptive forecasting equation. The fuzzy if-then rules produced from fusion ANFIS model, which can be understood for human recognition, and the adaptive network in fusion ANFIS model can deal with the nonlinear relationships. This study optimizes the proposed model by adaptive network and adaptive forecasting equation to improve electricity loads forecasting accuracy. To evaluate forecasting performances, six different models are used as comparison models. The experimental results indicate that the proposed model is superior to the listing models in terms of mean absolute percentage errors (MAPE).     

Relative electrical distance concept for evaluation of network reactive power and loss contributions in a deregulated system

With the liberalisation of electricity market it has become very important to determine the participants making use of the transmission network. Transmission line usage computation requires information of generator to load contributions and the path used by various generators to meet loads and losses. In this study relative electrical distance (RED) concept is used to compute reactive power contributions from various sources like generators, switchable volt-amperes reactive (VAR) sources and line charging susceptances that are scattered throughout the network, to meet the system demands. The transmission line charge susceptances contribution to the system reactive flows and its aid extended in reducing the reactive generation at the generator buses are discussed in this paper. Reactive power transmission cost evaluation is carried out in this study. The proposed approach is also compared with other approaches viz., proportional sharing and modified Y-bus. Detailed case studies with base case and optimised results are carried out on a sample 8-bus system. IEEE 39-bus system and a practical 72-bus system, an equivalent of Indian Southern grid are also considered for illustration and results are discussed.     

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.     

Nodal probabilistic production cost simulation considering transmission system unavailabilty

A nodal probabilistic production cost simulation method is described for power system long-term expansion planning considering unavailability and delivery limitation constraints of the transmission system. This new nodal production cost simulation model includes capacity constraints and unavailabilities of generators as well as transmission lines. This simulation methodology comes from the nodal composite power system equivalent load duration curve (CMELDC), based on a new effective load model at load points developed by the authors. The nodal CMELDC can be obtained from convolution integral processing of the outage capacity probability distribution function of the fictitious generator and the original LDC. It is expected that the new simulation model based on the nodal CMELDC proposed here will provide solutions to many problems based on nodal and decentralised operation and control of electric power systems under a competition environment. The nodal CMELDC based on the new model at load points can extend application areas of nodal probabilistic production cost simulation, probabilistic congestion cost assessment, analytical outage cost assessment and nodal reliability evaluation and so on at load points. The characteristics and effectiveness of this new proposed methodology are illustrated by a small system case study using a network flow and enumeration method.     

Complex dynamics of Cournot game with bounded rationality in an oligopolistic electricity market

In order to accurately simulate the dynamic decision-making behaviors of market participants, a novel dynamic Cournot game model with bounded rationality of electricity market that considers the constraints of realistic power networks is proposed in this paper. This model is represented by discrete difference equations embedded within the optimization problem of consumption benefits. The Nash equilibrium of electricity market and its stability are quantitatively analyzed. It is found that there are different Nash equilibriums with different market parameters corresponding to different operating conditions of power network, i.e. congestion and non-congestion, and even in some cases there is no Nash equilibrium at all. Numerical simulations with the 2-node and IEEE 30-node systems are carried out to evaluate the dynamic behaviors of electricity market, especially the periodic and chaotic behaviors when the market parameters are beyond the stability region of Nash equilibrium.     

Behavioural analysis of a hydroelectric production power plant under reworking scheme

By high calibre of the fundamental nature of electric power, both of our economic and personal interests, a system is expected to supply as electrical energy as possible with the highest degree of quality and reliability. This research work aimed to evaluate the reliability measures of a hydroelectric power station. The results of this study are deliberate to provide the improved criteria for upcoming proposals, and serves as a basis for generation expansion planning of hydroelectric power stations. This paper presents a Markov-process based mathematical model for a hydroelectric power plant. The important reliability measures have been derived and discussed with the help of failure and repair rates through the analysis. This research gives a clear view of how the hydropower plants are modelled by defining the states under the failure and repair rates.