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2014 | Book

Reliability-Centric Studies in Smart Grids: Adequacy and Vulnerability Considerations Read chapter Read first chapter

Reliability Modeling and Analysis of Smart Power Systems

Editors: Rajesh Karki, Roy Billinton, Ajit Kumar Verma

Publisher: Springer India

Book Series : Reliable and Sustainable Electric Power and Energy Systems Management

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik"

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About this book

The volume presents the research work in understanding, modeling and quantifying the risks associated with different ways of implementing smart grid technology in power systems in order to plan and operate a modern power system with an acceptable level of reliability. Power systems throughout the world are undergoing significant changes creating new challenges to system planning and operation in order to provide reliable and efficient use of electrical energy. The appropriate use of smart grid technology is an important drive in mitigating these problems and requires considerable research activities, some of which (by researchers from academia and industry) are included in this volume: the reliability appraisal of smart grid technologies and their applications, micro-grids, assessment of plug-in hybrid vehicles and the system effects, smart system protection and reliability evaluation, demand response and smart maintenance of power system equipment.

Table of Contents

Frontmatter
Reliability-Centric Studies in Smart Grids: Adequacy and Vulnerability Considerations
Abstract
There are diverse visions on how to go about achieving reliability, energy conservation, and efficiency with environmental compliance through the inter-disciplinary integration of information and communication technologies (ICT) and power system technologies to facilitate the modernization of grids. The paradigm of smart grid has been brought forward and is being continually improvised to cater to the energy demands of the twenty-first century. However, the term “reliability” used in invariably defining and outlining the characteristic features of smart grids seems to be in a generic context, and more often than not qualitative. The aim of this chapter is to appraise the challenges presented by the envisioned transformation towards Smart grids in terms of capturing the anticipated quantitative reliability benefits and the growing need for allied reliability-related studies.
Vijay Venu Vadlamudi, Rajesh Karki, Gerd H. Kjølle, Kjell Sand
Security of Supply in Active Distribution Networks with PHEV-Based Strategic Microgrids
Abstract
With the increased integration of intermittent distributed generation (DG) into active distribution networks the security of power supply to consumers is challenging. Plug-in hybrid electric vehicles (PHEVs) can be used as standing reserve units that can mitigate intermittency of power. They can also provide strategic supports in the form of microgrids. Taking into account merits of PHEVs, the chapter proposes a methodology to mobilize the strategic microgrids for the improved security of supply in an active distribution network. It also quantifies the feasible improvement in security of supply with PHEV-based strategic microgrids. The Monte Carlo simulation is the core engine of the approach and it captures many uncertainties that can be embedded in an active distribution network. A case study is performed and the results suggest that PHEV-based strategic microgrids can improve the security of power supply to consumers. The PHEV-based strategic microgrids would not always be the same strategic microgrids with increased penetration of intermittent DG. Strategic ability of PHEV-based microgrids dynamically change with increased penetration of DG.
Dilan Jayaweera, Syed Islam
Operational Characteristics of Microgrids with Electric Vehicles
Abstract
Microgrids are the basic building cells of a smart grid. They are assumed to be established at the low voltage distribution level, where distributed energy sources, storage devices, controllable loads, and electric vehicles are integrated and need to be properly managed. The microgrid cell is a very flexible system that can be operated connected to the main power network or autonomously, in a controlled and coordinated way. When operating in islanded mode, the MG relies on local energy storage to ensure the balance between generations and loads. However, when operating isolated from the main grid, the MG is more sensitive to power quality issues such as voltage unbalance, caused by the connection of single-phase loads and sources. In order to improve the MG emergency operation conditions, the EV should be envisaged as an active and flexible entity, providing to the MG additional distributed load or storage capacity under the vehicle-to-grid (V2G) concept. This chapter reviews the MG architecture considering EV and focuses on the impact of their active participation on the MG frequency regulation in emergency conditions (namely in islanding operating mode). Voltage unbalance issues during MG autonomous operation and the need for adopting voltage balancing mechanisms in specific power electronic interfaces are also discussed.
Clara Sofia Gouveia, Paulo Ribeiro, Carlos L. Moreira, João Peças Lopes
An Optimized Adaptive Protection Scheme for Distribution Systems Penetrated with Distributed Generators
Abstract
An intelligent adaptive protection scheme for distribution systems penetrated with distributed generators is proposed in this chapter. The scheme utilizes digital directional overcurrent relays connected with a communication network to a central relaying unit. A linear optimization technique is used to coordinate the overcurrent relays whenever a change in the system topology is detected. The scheme can also identify the faulty section of the feeder and update the settings of the primary and backup relays to speed up the fault clearance. The obtained results show that the scheme is successfully able to update the settings of the relays based on the current system topology and when a faulted section is identified.
Ahmed H. Osman, Mohamed S. Hassan, Mohamad Sulaiman
Protection System Reliability Assessment Considering Smart Grid Technologies
Abstract
Advanced protection systems and peer-to-peer communications are major assets in a smart grid platform. Failures of protection system components play a significant role in the outage events of breaker oriented power systems and protected components. The recent developments in nonconventional protection systems and the widespread use of intelligent electronic devices (IED) supported by advanced peer-to-peer communication systems could lead to unexpected protection system failures, which can result in circuit breakers not opening when required. A protection system is a completely integrated system of its own which can be analyzed independently of the power system network or component that it is intended to protect. An independent analysis enables sensitivity and comparative studies to be made of alternative technologies and protection schemes. This paper presents and discusses different alternative digitized protection schemes supported by an IED and a communication system. The reliability of each scheme is assessed using event tree analysis (ETA). An application to a breaker oriented system is illustrated. Sensitivity analysis is conducted to assess the effect of the protection system component. Evaluation results show that an IED supported by a robust communication system can improve the protection system reliability, especially for highly redundant protection systems. The paper illustrates that high penetration of advanced technologies in protection systems must also be associated with highly reliable components for enhanced system performance.
Ahmed Saleh AlAbdulwahab, Roy Billinton
Smart Charging of Plug-in Electric Vehicles Under Driving Behavior Uncertainty
Abstract
An upcoming introduction of plug-in hybrid electric vehicles and electric vehicles could put power systems’ infrastructure under strain in the absence of charging control. The charging of electric vehicles could be managed centrally by a so-called aggregator, which would take advantage of the flexibility of these loads. To determine optimal charging profiles day-ahead, the aggregator needs information on vehicles’ driving behavior, such as departure and arrival time, parking location, and energy consumption, none of which can be perfectly forecasted. In this chapter, we introduce an approach to derive day-ahead charging profiles that minimize generation costs while respecting network and drivers’ end-use constraints, as well as taking into account the uncertainty in driving patterns. The charging profiles are derived by aggregating vehicles at each network node into virtual battery resources and dispatching them with a multiperiod optimal power flow (OPF). To take driving pattern uncertainty into consideration, different possible realizations of individual driving patterns are generated with a Monte Carlo simulation, modeling individual driving behavior with non-Markov chains. This information is integrated into the OPF, where constraints concerning the virtual batteries are modeled as chance constraints, i.e., as constraints that may be violated with a certain probability. Compared with a deterministic approach, this framework increases the chances of not violating the constraints subject to uncertainty.
Marina González Vayá, Göran Andersson
Multivariate Stochastic Modeling of Plug-in Electric Vehicles Demand Profile Within Domestic Grid
Abstract
A copula-based stochastic approach is proposed to derive the load demand of a fleet of domestic commuter plug-in electric vehicles (PEVs). Employing a copula, a multivariate distribution can be constructed by specifying marginal univariate distributions, and afterwards choosing a copula to provide a dependence structure among variables. The copula function does not constrain the choice of the marginal distribution. At first, appropriate non-Gaussian probability density functions are fitted to the gathered datasets. The datasets include home arrival time, daily travelled distance, and home departure time of randomly selected private internal combustion engines (ICE) vehicles. Then, the dependence structure is modeled using a student’s t copula distribution to generate random samples required in the Monte Carlo simulation. In each iteration, extraction of the charging profile is carried out for the individual PEVs in order to derive the hourly aggregated load profile of the fleet. Afterwards, probability density function of the aggregated load of the PEVs within each hour is estimated by applying the Monte Carlo simulation. Eventually, the expected value of the hourly load demand can be calculated regarding the achieved power distributions. The PEVs are supposed to be charged through a distribution transformer. Consequently, the profile of the power delivered through the transformer to the PEVs is attained, which in turn can be useful for various distribution system applications such as network planning, load management, and probabilistic load flow as well as sitting and sizing issues.
Ehsan Pashajavid, Masoud Aliakbar Golkar
Probabilistic Home Load Controlling Considering Plug-in Hybrid Electric Vehicle Uncertainties
Abstract
Home automation is evolving with the objective of upgrading the living convenience. The load control is, however, conceived as its subsidiary function for economic benefits. In this chapter, the problem of home load controlling (HLC) is widely investigated through deterministic and probabilistic analysis. The behavior of plug-in hybrid electric vehicles (PHEVs) consumer, i.e., departure time, traveling time, and energy consumption, are assumed to be stochastic variables. Incorporation of these inherent uncertainties offers a solution with robust optimality in real world applications. More benefits are accordingly achievable compared with deterministic solutions. The optimization problem is formulated based on the mixed-integer programming (MIP) fashion since present commercial high-performance solvers guarantee the optimality of solutions. Numerical studies are conducted in order to illustrate the effectiveness of the model which clarifies the practicality of the proposed approach. A variety of sensitivity analyses are performed to demonstrate the effectiveness of the method in different conditions.
Mahmud Fotuhi-Firuzabad, Mohammad Rastegar, Amir Safdarian, Farrokh Aminifar
A Load Management Perspective of the Smart Grid: Simple and Effective Tools to Enhance Reliability
Abstract
This chapter reviews the effects of advanced load management on smart grid reliability. Emerging smart grid and development of advanced technologies such as AMI, smart monitors, smart appliances, and smart controllers, will facilitate the load management activities. This improved load management can be employed for increasing the power system reliability. Also, due to significant changes in load management methods in the future smart grids, it seems that the existing reliability indices should be modified for this new environment. This chapter discusses the changes in reliability indices of distribution systems and proposes some modifications for these indices.
Amir Moshari, Akbar Ebrahimi
Evaluating the Performance of Small Autonomous Power Systems Using Reliability Worth Analysis
Abstract
The analysis and design of a small autonomous power system (SAPS) that contains renewable energy sources (RES) technologies can be challenging, due to the large number of design options and the uncertainty in key parameters. Renewable power sources add further complexity because their power output may be intermittent, seasonal, and nondispatchable. Due to this characteristic, reliability evaluation of a RES based SAPS cannot be implemented using the traditional deterministic and analytical methods. Moreover, in order to be complete, this evaluation has to be done within a cost-benefit framework. This chapter investigates the effect of reliability worth in the optimal economic operation of SAPS that is based on RES technologies, considering different scenarios. The optimization procedure is implemented with a combined genetic algorithm (GA) and local search procedure. In addition, this chapter examines the effect of considering SAPS components forced outage rate in the obtained optimal solutions via Monte Carlo simulation (MCS). The performance of the proposed optimization methodology is studied for a large number of alternative scenarios via sensitivity analysis, which study the effect on the results due to the uncertainty on weather data and cost data. The results show that the optimal operation of a RES based SAPS depends largely on the consideration of reliability worth as well as the inclusion of components forced outage rate.
Yiannis A. Katsigiannis, Pavlos S. Georgilakis, Marios N. Moschakis
Condition Monitoring Benefit for Operation Support of Offshore Wind Turbines
Abstract
As more offshore wind parks are commissioned, the focus will inevitably shift from a planning, construction, and warranty focus to an operation, maintenance, and investment payback focus. In this latter case, both short-term risks associated with wind turbine component assemblies, and long-term risks related to integrity of the support structure, are highly important. This research focuses on the role of condition monitoring to lower costs and risks associated with short-term reliability and long-term asset integrity. This enables comparative estimates of the life cycle costs and reduction in uncertainty, both of which are of value to investors.
Sebastian Thöns, David McMillan
Towards Reliability Centred Maintenance of Wind Turbines
Abstract
Reliability centred maintenance applied to a fleet of wind turbines is presented in this paper. The key components and failure modes are identified via analysis of maintenance records. Corrective actions which an operator can take to mitigate such failures are discussed, together with implementation issues. By developing a robust set of RCM tools, wind farm operators can better quantify and minimise operational expenditure of wind farm fleets.
David McMillan, Graham W. Ault
Cable Segment Replacement Optimization
Abstract
This chapter presents an opportunistic maintenance optimization approach for cable segment replacement in a population with degraded cables. The optimization is based on diagnostic measurements, which typically could be made online with temperature sensors and/or partial discharge detection. System perspective in the optimization is achieved by the use of component reliability importance indices. The method identifies interesting cable segments for replacement under a budget constraint and encourages replacement of continuous segments of cable. The strength of the method is an optimization that incorporates diagnostics, economy, and power system structure in one model.
Patrik Hilber
Metadata
Title
Reliability Modeling and Analysis of Smart Power Systems
Editors
Rajesh Karki
Roy Billinton
Ajit Kumar Verma
Copyright Year
2014
Publisher
Springer India
Electronic ISBN
978-81-322-1798-5
Print ISBN
978-81-322-1797-8
DOI
https://doi.org/10.1007/978-81-322-1798-5