9,488 research outputs found
PHASOR MEASUREMENT UNIT DEPLOYMENT APPROACH FOR MAXIMUM OBSERVABILITY CONSIDERING VULNERABILITY ANALYSIS
In recent years, there has been growing interest of synchrophasor measurements like Phasor Measurement Units (PMUs) Power systems are now being gradually populated by PMU since they provide significant phasor information for the protection and control of power systems during normal and abnormal situations. There are several applications of PMUs, out of which state estimation is a widely used. To improve the robustness of state estimation, different approaches for placement of PMUs have been studied. This thesis introduces an approach for deployment the PMUs considering its vulnerability. Two different analysis have been considered to solve the problem of locating PMUs in the systems. The first analysis shows that using a very limited number of PMUs, maximum bus observability can be obtained when considering the potential loss of PMUs. This analysis have been done considering with and without conventional measurements like zero injections and branch flow measurements. The second analysis is based on selection of critical buses with PMUs. The algorithm in latter is specifically used for the system which has existing PMUs and the scenario where new locations for new PMUs has to be planned. The need for implementing this study is highlighted based on attack threads on PMUs to minimize the system observability. Both the analysis are carried out using Binary Integer Programming (BIP). Detail procedure has been explained using flow charts and effectiveness of the proposed method is testified on several IEEE test systems
Optimal Placement of Phasor Measurement Units for Power Systems Using Genetic Algorithm
Power grids require monitoring to operate with high efficiency while minimizing the chances of having a failure. However, current monitoring scheme which consists of SCADA (Supervisory Control and Data Acquisition), accompanied with conventional meters distributed throughout the grid, is no longer sufficient to maintain an acceptable operation of the grid. This is evident from the multiple failures and blackouts that happened and are still happening in grids worldwide. This issue became more severe due to systems being operated near their limits (to reduce costs and due to the increase in electricity demands), as well as, the addition of renewable energy sources, which usually have abrupt changes. Smart grids were introduced as a solution to this issue by the inclusion of Wide Area Monitoring System (WAMS), which is mainly based on Phasor Measurement Units (PMU), which are measurement devices that provides synchronized time stamped measurements with high sending rate which significantly improves the monitoring of the grid. However, PMUs are relatively expensive (considering both direct and indirect costs incurred). Thus, it is desired to know the minimum number of PMUs required for achieving certain monitoring criteria. Thus, Optimal PMU Placement (OPP) formulates an optimization problem to solve this issue. In the literature of OPP, multiple objectives and constraints are considered, based on desired criteria. In this thesis, a review of OPP is made, followed by the application of selected algorithms (Integer Linear Programming and Genetic Algorithm) on various test systems as a verification and then applying it to Qatar Grid, to compare between different considerations as well as gain insight about the possible PMU placements for Qatar Grid. The contribution of this thesis is introducing a modified fitness function for the Genetic Algorithm that provides more diverse results than previous papers, while incorporating for various considerations like Zero Injection Buses, Conventional Measurements and current branch limit. It also analyzes the results of current branch limit and provides new plots describing their effects
An efficient genetic algorithm for large-scale transmit power control of dense and robust wireless networks in harsh industrial environments
The industrial wireless local area network (IWLAN) is increasingly dense, due to not only the penetration of wireless applications to shop floors and warehouses, but also the rising need of redundancy for robust wireless coverage. Instead of simply powering on all access points (APs), there is an unavoidable need to dynamically control the transmit power of APs on a large scale, in order to minimize interference and adapt the coverage to the latest shadowing effects of dominant obstacles in an industrial indoor environment. To fulfill this need, this paper formulates a transmit power control (TPC) model that enables both powering on/off APs and transmit power calibration of each AP that is powered on. This TPC model uses an empirical one-slope path loss model considering three-dimensional obstacle shadowing effects, to enable accurate yet simple coverage prediction. An efficient genetic algorithm (GA), named GATPC, is designed to solve this TPC model even on a large scale. To this end, it leverages repair mechanism-based population initialization, crossover and mutation, parallelism as well as dedicated speedup measures. The GATPC was experimentally validated in a small-scale IWLAN that is deployed a real industrial indoor environment. It was further numerically demonstrated and benchmarked on both small- and large-scales, regarding the effectiveness and the scalability of TPC. Moreover, sensitivity analysis was performed to reveal the produced interference and the qualification rate of GATPC in function of varying target coverage percentage as well as number and placement direction of dominant obstacles. (C) 2018 Elsevier B.V. All rights reserved
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Development of novel electrical power distribution system state estimation and meter placement algorithms suitable for parallel processing
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe increasing penetration of distributed generation, responsive loads and emerging smart metering technologies will continue the transformation of distribution systems from passive to active network conditions. In such active networks, State Estimation (SE) tools will be essential in order to enable extensive monitoring and enhanced control technologies. In future distribution management systems, the novel electrical power distribution system SE requires development in a scalable manner in order to accommodate small to massive size networks, be operable with limited real time measurements and a restricted time frame. Furthermore, a significant phase of new sensor deployment is inevitable to enable distribution system SE, since present-day distribution networks lack the required level of measurement and instrumentation. In the above context, the research presented in this thesis investigates five SE optimization solution methods with various case studies related to expected scenarios of future distribution networks to determine their suitability. Hachtel's Augmented Matrix method is proposed and developed as potential SE optimizer for distribution systems due to its potential performance characteristics with regard to accuracy and convergence. Differential Evolution Algorithm (DEA) and Overlapping Zone Approach (OZA) are investigated to achieve scalability of SE tools; followed by which the network division based OZA is proposed and developed. An OZA requiring additional measurements is also proposed to provide a feasible solution for voltage estimation at a reduced computation cost. Realising the requirement of additional measurements deployment to enable distribution system SE, the development of a novel meter placement algorithm that provides economical and feasible solutions is demonstrated. The algorithm is strongly focused on reducing the voltage estimation errors and is capable of reducing the error below desired threshold with limited measurements. The scalable SE solution and meter placement algorithm are applied on a multi-processor system in order to examine effective reduction of computation time. Significant improvement in computation time is observed in both cases by dividing the problem into smaller segments. However, it is important to note that enhanced network division reduces computation time further at the cost of accuracy of estimation. Different networks including both idealised (16, 77, 356 and 711 node UKGDS) and real (40 and 43 node EG) distribution network data are used as appropriate to the requirement of the applications throughout this thesis.‘High Performance Computing Technologies for Smart Distribution Network Operation' (HiPerDNO) project under Grant FP7 - 248135/2007-2013 (European Community's Seventh Framework Programme)
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Optimal allocation of phasor measurement units using practical constraints in power systems
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.The purpose of the research is to find a strategic placement of phasor measurement
units (PMUs) that can maintain the observability of the power system using a binary
variant of particle swarm optimisation method (BPSO). In recent years, integer linear
programming (ILP) is the common optimisation method used to solve this problem.
However, recent studies have shown that deterministic methods such as ILP are still
unable to find the most optimal placement of PMUs. Therefore, there is still room for
further investigation using heuristic algorithm due to its search-based nature. It is
important to determine the most strategic placement of PMUs to ensure that the PMUs are
fully utilised due to their expensive price tag. The challenge in using heuristic algorithm
lies in its weakness when involving large-sized problem since it is prone to stuck in local
optima as shown in earlier studies where most of them applied their proposed approach to
small bus systems. To prevent the BPSO method from being stuck in local optima, a
mutation strategy is proposed in addition to the V-shaped sigmoid function replacing the
S-shaped sigmoid function. The proposed method is designed to intensify the local search
of the algorithm around the current best solution to help instigate the particles from being
stuck in local optima and consequently finding a better solution. This is shown to be a
crucial factor based on the numerical results obtained where it outperforms all methods
for all bus systems tested including the IEEE 300-bus system in terms of measurement
redundancy and the number of PMUs. This study also considers other problem constraints
such as zero-injection bus, single PMU loss and also PMU’s channels limit. Most of the
existing studies considered PMU to have an unlimited number of channels whereas in
practical, PMU does have a finite number of channels that it can use.Majlis Amanah Rakyat (MARA) and University Kuala Lumpur (UniKL
Heuristic Method for Optimal Placement of Phasor Measurement Units (PMUs)
The phasor measurement units (PMUs) are very important tool for monitoring and control the power system. PMUs give real time, synchronized measurements of voltages at the buses and also current phasors which are incident to those buses where these PMUs are located. It is unnecessary and impossible to place PMU at each bus to estimate the states because high cost of PMUs and also the cost of communication facilities. It is necessary to find out the minimum number of PMUs to entire power system observable. The optimal placement of PMUs (OPP) problem solved by various techniques such as mathematical programming, metaheuristic techniques. The recently some heuristic optimization technique proposed to determine the minimum number of PMUs for various systems should be completely observable. This optimal PMUs placement (OPP) problem is pure binary optimization problem. A topological observability based three stages optimal PMU placement technique is proposed for solving this problem. For topological observability a set of minimum PMUs is required to make the system completely observable. It is assumed that there are strategic buses in every system using that the PMU placement becomes an easy task. The proposed method tested on standard IEEE bus systems and compared the results of the proposed method to the previously methods
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