Power System Reliability Assessment Research Articles

An Appropriate Wind Model for The Reliability Assessment of Incorporated Wind Power in Power Generation System

The use of renewable energy sources (RES) by many power grids companies around the world has increased significantly in recent years. The trend towards the use of RES is mainly due to ecological problems and rising fuel prices related to conventional power generation. Wind power is an approved source for power generation among renewable sources that makes a positive contribution to the global, social and economic environment. Today, wind turbine generator (WTG) is a mature, abundant, and eco-friendly power generation technology, and much of the electricity demand is supplied by wind. However, the uncertain nature of wind speed poses a variety of challenges for the planning and operation of power systems. One of the problems in increasing wind power can be seen in terms of assessment of power system reliability. This paper presents a reliability assessment model of power generation systems (PGS), including WTG, by using an analytical method. The presented model in this paper applied to the Roy Billinton Test System (RBTS). The methodology and results presented in this paper are intended to provide useful information to planners or developers seeking to assess the reliability of PGSs, including WTG.

Reliability Assessment of Power System Considering the Impact of Renewable Energy Sources Integration Into Grid With Advanced Intelligent Strategies

Power industry is incidenting a change from the present electric grid to a more secure, reliable, capable and advanced smart grid. Renewable energy sources such as wind and solar energy systems will be incorporated and potentially in bid scale in order to obtain these aims. Many possible applications of renewable energy sources have been inspected. In this article, reliability enhancement of power system considering the impact of wind and solar energy sources integration into grid with advanced intelligent strategies is focused. Further, different models are utilized to obtain the proposed renewable energy sources operation. Further, a reliability assessment framework is discussed to examine the reliability impact of renewable energy sources integration into the grid. A comprehensive case study and risk analysis has been performed based on the different risk indexes to show the usefulness of the proposed strategies and assessment framework, and to give precious insight on the reliability impact resulting from the wind and solar energy resources integration into the grid. The main advantages of renewable energy sources integration into grid with intelligent techniques are presented here along with the reliability evaluation. The results of the study reveals that the integration of the solar and wind energy systems into the grid enhances overall the reliability of the entire power system

Reliability assessment of composite power systems containing sea wave slot‐coned generators

The generated power of the Sea-wave slot-coned generator (SSG), as one of the high capacity wave energy converters, is dependent on the period and height of the waves. The generated power of this energy-converter changes due to the variation in these parameters. Thus, different aspects of the power systems may be affected that must be investigated by increasing the share of these converters for electricity production in the power-systems. In this paper reliability assessment of composite power-systems containing large-scale SSG is performed. The Xie and Beni (XB) index is calculated for obtaining the optimum number of states in the reliability model of the SSG and fuzzy c-means clustering technique is proposed for reducing the number of states of the model. The contingency analysis method is proposed for calculating the reliability indices of the composite power-system incorporating large-scale SSG. DC load-flow method, which considers line capacity, is used to perform load-flow in the composite power-system including generation and transmission networks. In the proposed technique, a load-shedding program with the goal of minimizing the value of lost load is solved using of the linear programming method based on the interior-point-approach for contingency states leading to the load curtailment.

A probabilistic analysis of power generation adequacy towards a climate-neutral Europe

Over the last decades, the actions aimed to realize an integrated pan-European electricity market brought about profound modifications on the physical, information and communication systems upon which the electricity delivery process occurs. In order to assess some of the techno-economic challenges relating to the single electricity market functioning, including the future needs of electricity, several dispatch models have been developed in recent years in Europe and the rest of the world. In particular, EUPowerDispatch, a minimum cost dispatch model, was originally developed to investigate the need for cross-border transmission investment in Europe. This paper proposes an improved version of EUPowerDispatch that aims at analysing the generation adequacy of the European electricity system in a probabilistic manner. For this purpose, planned and unplanned outages of all single conventional generating units are modelled. The former are optimally and timely allocated while the latter are stochastically generated with chronological Monte Carlo simulations. Data of wind and solar PV production from several meteorological years are accounted for as well as hydro series of run-of-river and natural inflows to the hydro reservoirs. The case study is composed of 33 European countries/regions which are linked through interconnectors. Indexes for the reliability assessment of electric power systems are calculated in order to study the generation adequacy of the European electricity system in 2025.

Reliability assessment and congestion management of power system with energy storage system and uncertain renewable resources

The high penetration of Renewable Energy Sources (RES) makes the power system unreliable due to its uncertain nature and to deal with this uncertainties installation of an Energy Storage System (ESS) is suggested. In this paper, the quantifying impact of ESS capacity on power system network reliability and relieving the congestion is analyzed. The proposed reliability assessment and congestion relief problem is formulated by considering generation cost and demand interruption cost for N-1 contingency criteria. The proposed algorithm manages the optimal charging and discharging of ESS to mitigate the uncertainties associated with RES and relieving the congestion. The impact of ESS capacity on reliability indices Expected Energy not Supplied (EENS) and Expected interruption Cost (ECOST) for Generating Companies (GENCOs), Transmission Companies (TRANSCOs), customers, and entire power system are calculated. The appropriate size of ESS is selected by the trade-off between investment cost of ESS and percentage change in EENS and ECOST value for the entire power system, GENCOs, TRANSCOs, and customers. The effectiveness of the proposed approach is tested on the modified IEEE RTS 24 bus system. The problem is modeled in the Generic Algebraic Solver (GAMS) environment and solved using CONOPT as an NLP solver.

Modern power system reliability assessment with cyber‐intrusion on heat pump systems

In smart power systems, information and communication technologies are being broadly installed and two-way communications are being established more effectively and efficiently. However, they are vulnerable to cyber-physical interactive threats and their impact depends on the system infrastructure, degree of interaction, degree of vulnerability, and the intensity and the frequency of the attack. The study addresses this problem and proposes: (i) an innovative Markov-chain based framework of the cyber-intrusion process to implement operating conditions in a smart power system; (ii) an advanced algorithm for power system reliability assessment, incorporating cyber-intrusion process and a detailed model of a heat pump system; and (iii) a new impact assessment framework for different cyber-intrusion detection-time distributions driven by Monte Carlo simulation. The cyber-detection and system recovery process with the presence of cyber-physical interactive operation models suggest that a significant level of impacts could be generated by the interactive operation of the smart power system and a quantitative assessment is needed in order to assess true impacts.

Wind power system reliability and maintenance optimization considering turbine and wind uncertainty

PurposeWind power is an important source of renewable energy and accounts for significant portions in supplying electricity in many countries and locations. The purpose of this paper is to develop a method for wind power system reliability assessment and condition-based maintenance (CBM) optimization considering both turbine and wind uncertainty. Existing studies on wind power system reliability mostly considered wind uncertainty only and did not account for turbine condition prediction.Design/methodology/approachWind power system reliability can be defined as the probability that the generated power meets the demand, which is affected by both wind uncertainty and wind turbine failures. In this paper, a method is developed for wind power system reliability modeling considering wind uncertainty, as well as wind turbine condition through health condition prediction. All wind turbine components are considered. Optimization is performed for maximizing availability or minimizing cost. Optimization is also conducted for minor repair activities to find the optimal number of joint repairs.FindingsThe wind turbine condition uncertainty and its prediction are important for wind power system reliability assessment, as well as wind speed uncertainty. Optimal CBM policies can be achieved for optimizing turbine availability or maintenance cost. Optimal preventive maintenance policies can also be achieved for scheduling minor repair activities.Originality/valueThis paper considers uncertainty in both wind speed and turbine conditions and incorporates turbine condition prediction in reliability analysis and CBM optimization. Optimization for minor repair activities is studied to find the optimal number of joint repairs, which was not investigated before. All wind turbine components are considered, and data from the field as well as reported studies are used.

Optimal Technique of reliability and quality Assessment of two-area interconnected power systems

Optimal Technique of reliability and quality Assessment of two-area interconnected power systems

Reliability Assessment of Electric Power System with Distributed Generation Facilities

Modern power supply systems that have distributed generation and are connected to the electric power system, renewable energy sources, and storage devices, require changes in the assessment of their reliability indices. The complexity of the energy, technological, and organizational structures of power systems with distributed generation does not allow the traditional concept of "failure" to be used to assess their reliability. Many technological solutions used in the distributed generation projects can become sources of vulnerabilities in the infrastructure of an intelligent electrical network. The study shows that power systems with distributed generation are the structures with overlapping service areas, which determines their specific features represented by an integral characteristic - efficiency. It characterizes the extent to which the use of distributed generation facilities in various operating conditions is feasible. The paper proposes an approach to quantifying the efficiency of such systems. The presented examples demonstrate the calculation of relatively simple power systems with the distributed generation that perform several tasks simultaneously.

Design of Power Security Protection System Based on Neural Network Algorithm

Power safety is closely related to production and life, so an essential part of the power safety protection system. Safety accidents are inseparably linked to equipment and the environment. Electricity safety accidents are not rare in causing loss of life and property. The neural network algorithm-based power security system uses the analytic hierarchy process to layer multiple logical structures of the power grid, evaluates the factors that affect safety, obtains the weight of each influencing factor, and selects the higher impact on power system safety interference according to the weight Factors. Now neural network algorithms have begun to be widely used, and electrical safety systems based on neural network algorithms play a significant role in power safety. Combining neural network algorithms with power safety protection systems can effectively guide functions such as aging monitoring, life prediction, and fault identification of power equipment, and can also improve the accuracy of power system reliability assessment.

An innovative fractional order LMS algorithm for power signal parameter estimation

Parameter estimation is an important issue for the quality monitoring and reliability assessment of power systems. In this study, an innovative fractional order least mean square (I-FOLMS) adaptive algorithm is presented for an effective parameter estimation. The I-FOLMS algorithm exploits the fractional gradient in its recursive parameter update mechanism, because its performance can be tuned by means of the fractional order. High values of the fractional order are good for fast convergence, but lead to steady state mis-adjustments. While, low values provide a smooth steady state behavior, but require a compromise in the convergence rate. The effective performance of I-FOLMS is verified and validated through two numerical examples of power signals estimation for different levels of noise variance and values of the fractional orders.

Reliability assessment of offshore oil platform power system based on state enumeration method

Based on the state enumeration method, a reliability evaluation method for offshore platform power system is proposed in this paper. Firstly, the reliability model of land-based components and the modelling method of the system are introduced. In reliability evaluation, all fault states are generated based on state enumeration method, power supply circuit sets are identified based on depth-first algorithm. The effects and losses of multiple faults are calculated based on platform maintenance capability, and fault time and load-loss time are separated and counted. Finally, taking an offshore oil platform as an example, the outage table of the system is generated, and the reliability index of the system is obtained, which verifies the effectiveness and accuracy of the method proposed in this paper.

Reliability Assessment of Distribution Power System When Considering Energy Storage Configuration Technique

The main task of distribution systems is to provide acceptable reliability, economic and quality service of electrical power according to the demanded load value. To fulfill this task more accurately, the reliability performance of the distribution system can be performed and measured using a wide variety of indices, which are divided into energy indices and frequency/expectation indices. This study evaluates the reliability indices of a part of the distribution network selected as a model and deals with the selection of the most suitable feeder by connecting energy storage units to the busbars. Using IEEE Standard 1366 reliability indices, historical data from Prosperous Electricity Distribution Company (PEDC), which is used to evaluate reliability based on the 5-year past reliability assessment of the power system (RAPS), was selected. In addition, as an innovation in this application process, energy storage systems (ESS) have been evaluated according to four different network configurations (A-B-C-D) to increase RAPS and achieve more realistic results. Using DigSILENT, ESS-based configurations are designed, comparisons are made, and configuration B is the best result to increase system reliability and the 80E6 feeder is optimal. In addition, reliability changes achieved by network configuration have demonstrated the importance of optimal configuration planning to improve the uninterrupted and sustainable energy quality of the system based on storage technology.

An Overview on the Reliability of Modern Power Electronic Based Power Systems

Renewable energy resources are becoming the dominating element in power systems. Along with de-carbonization, they transform power systems into a more distributed, autonomous, bottom-up style one. We speak of Smart Grid and Microgrid when distributed energy resources take over. While being a means to improve technical and financial efficiency, planning, operations, and carbon footprint, it is these new technologies that also introduce new challenges. Reliability is one of them, deserving a new way of describing and assessing system and component reliability. This paper introduces a new reliability framework that covers these new elements in modern power systems. It can be seen that reliability assessment of modern power systems also requires introducing local reliability concepts as well as incorporating different electro-magnetic/mechanical stability issues.

Risk-Oriented Renewable Energy Scenario Clustering for Power System Reliability Assessment and Tracing

The integration of large-scale renewable energy significantly increases the computation time of reliability assessment and tracing. To solve this problem, the traditional methods cluster the scenarios directly based on renewable energy data. However, it could lead to errors in reliability assessment due to scenarios with similar risks. In this paper, a multi-scenario risk-oriented clustering algorithm considering renewable energy is proposed. The enumeration method is used to calculate the risk for different scenarios. According to the risk of each scenario, the Fuzzy C-means clustering method is adopted to cluster the scenarios, which maximizes the similarity of scenarios in the same cluster. The high-risk scenarios that contribute more to the reliability index are retained. The system reliability assessment and tracing are conducted based on the clustered scenarios. Case studies on the IEEE RBTS-6 and RTS-79 systems verify the accuracy and efficiency of the proposed method.

Reliability analysis for electric power systems of more-electric aircraft based on the minimal path set

With the raise of aircraft performance and the increasing electrical applications, the more-electrical or all-electric aircraft will become the main aircraft model in future. The reliability assessment of aircraft electric power system is critical to guarantee the reliable operation of the aircraft . A reliability assessment method for complex power system of large aircraft such as Boeing 787 has been described in this paper. First the aircraft power distribution system is abstracted as a topology diagram based on the graph theory. Then the minimal path sets are searching from the source node to the load nodes by the depth-first search. These path sets can represent the normal power supply path of the electric power system. Finally, using the raw reliability data of components, the reliability function of various important buses is established and the reliability index of large aircraft power distribution system is calculated. This assessment method can be used to analyze and assess the reliability of power supply and distribution system of different models and to provide a reference for the design and analysis of complex electric power system of civil aircraft.

Power System Reliability Assessment in a Complex Restructured Power System

The basic purpose of an electric power system is to supply its consumers with electric energy as parsimoniously as possible and with a sensible degree of continuity and quality. It is expected that the solicitation of power system reliability assessment in bulk power systems will continue to increase in the future especially in the newly deregulated power diligence. This paper presents the research conducted on the three areas of incorporating multi-state generating unit models, evaluating system performance indices and identifying transmission paucities in complex system adequacy assessment. The incentives for electricity market participants to endow in new generation and transmission facilities are highly influenced by the market risk in a complex restructured environment. This paper also presents a procedure to identify transmission deficiencies and remedial modification in the composite generation and transmission system and focused on the application of probabilistic techniques in composite system adequacy assessment

A novel importance sampling method of power system reliability assessment considering multi-state units and correlation between wind speed and load

With the rapid integration of wind energy, the increasing uncertainty and high reliable property of power systems have resulted in great difficulties in reliability assessment. To solve the problem, traditional cross entropy based importance sampling (CE-IS) methods are improved in this paper. The improved method is capable of efficiently assessing the reliability of composite power systems with wind energy integrated. First, we introduce the differences between the improved CE-IS (ICE-IS) and traditional CE-IS. Particularly, ICE-IS takes the correlation of random variables (RVs) into account and models multi-state RVs with multinomial distribution. Therefore, ICE-IS can obtain much better suboptimal distributions for the RVs than CE-IS, which accelerates the reliability assessment. Then the procedures of ICE-IS are detailed by two parts, which are a pre-simulation stage and a main simulation stage, respectively. Finally, we modify IEEE-RTS 79 and IEEE-RTS 96 test systems based on wind speed data observed in northwest China. Several case studies are designed and carried out on the modified systems to validate the proposed method.

Capacity Credit Evaluation of Correlated Wind Resources Using Vine Copula and Improved Importance Sampling

This paper concentrates on the capacity credit (CC) evaluation of wind energy, where a new method for constructing the joint distribution of wind speed and load is proposed. The method is based on the skew-normal mixture model (SNMM) and D-vine copulas, which is used to model the marginal distribution and the correlation structure, respectively. Then a cross entropy based importance sampling (CE-IS) is improved to enhance the efficiency of the power system reliability assessment, which is a crucial part of the CC evaluation. After that, the proposed methods are adopted to combine with the secant method to develop a complete algorithm to calculate the CC of wind energy. Numerical tests are designed and carried out based on the IEEE-RTS 79 system and wind speed data obtained from four wind farms in Northwest China. In order to show the superiority of SNMM and D-vine copula, the goodness-of-fit is quantified by different statistics. Besides, the improved CE-IS method is validated by comparison with Monte Carlo sampling (MCS) and traditional CE-IS in the efficiency of reliability assessment. Finally, the proved methods are combined with the secant method to calculate the CC of four wind farms, which can provide information for wind farm planning.

Operational Reliability Assessment of an Interconnected Power System Based on an Online Updating External Network Equivalent Model with Boundary PMU

Information between interconnected power systems is difficult to share in real time, due to trade secrets and technical limitations. The regional power grid cannot timely detect the impact of changes in the operation mode of the external power grid on the regional reliability, due to faults, load fluctuations, power generation plan adjustments, and other reasons. How to evaluate the reliability of a regional power system under the conditions of information isolation is a difficult problem for the security of interconnected power systems. Aiming at this problem, an operational reliability evaluation method for an interconnected power system is proposed herein, which does not depend on external network information directly, but only uses boundary phasor measurement unit (PMU) measurement data and internal network information. A static equivalent model with sensitivity consistency was used to simplify the external network to ensure the accuracy of the reliability calculation of interconnected power systems. The boundary PMU measurement data were used to update the external network equivalent model online. The algorithm flow of the operation reliability assessment for the interconnected power grid is given. The results of an example based on the IEEE-RTS-96 test system show that the proposed method can track the equivalent parameters of the external network without depending on the actual topological information, and calculate the reliability index of the internal network accurately.