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Unformatted text preview: Green Energy and Technology Jahangir Hossain Apel Mahmud Editors Renewable Energy Integration Challenges and Solutions Green Energy and Technology For further volumes: Jahangir Hossain Apel Mahmud • Editors Renewable Energy Integration Challenges and Solutions 123 Editors Jahangir Hossain Griffith School of Engineering Griffith University Gold Coast, QLD Australia Apel Mahmud Electrical and Electronics Engineering Swinburne University of Technology Hawthorn, VIC Australia ISSN 1865-3529 ISSN 1865-3537 (electronic) ISBN 978-981-4585-26-2 ISBN 978-981-4585-27-9 (eBook) DOI 10.1007/978-981-4585-27-9 Springer Singapore Heidelberg New York Dordrecht London Library of Congress Control Number: 2014931209  Springer Science+Business Media Singapore 2014 This work is subject to copyright. 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Printed on acid-free paper Springer is part of Springer Science+Business Media ( ) Editorial Advisory Board A/Prof. Hemanshu Roy Pota, The University of New South Wales, Australia Dr. Nadarajah Mithulananthan, The University of Queensland, Australia Dr. Nirmal Nair, University of Auckland, New Zealand Dr. S. M. Muyeen, The Petroleum Institute, UAE Dr. Mohd. Hasan Ali, Asst. Prof., The University of Memphis, USA Reviewers Nigel Hargreaves, Brunel University, UK Naruttam Kumar Roy, The University of New South Wales, Australia Francisco Gonzalez-Longatt, Loughborough University, UK Tareq Aziz, Ahsanullah University of Science and Technology, Bangladesh Tahsin Fahima Orchi, The University of New South Wales, Australia Raymundo Enrique Torres Olguin, Sintef Energy Research, Trondheim, Norway Md. Abdul Barik, The University of New South Wales, Australia Ramesh Rayudu, Victoria University of Wellington, New Zealand Ramesh Bansal, The University of Pretoria, South Africa Md. Shihanur Rahman, The University of New South Wales, Australia Ahmed Fathi Abdou, The University of New South Wales, Australia Henry Louie, Seattle University, USA A. B. M. Nasiruzzaman, The University of New South Wales, Australia Jayashri Ravishankar, The University of New South Wales, Australia Md. Masud Rana, The University of Sydney, Australia Elyas Rakhshani, Campus Palmas Altas, Spain Sajeeb Saha, The University of Melbourne, Australia Rajeev Chauhan, Indian Institute of Technology Mandi, India Mithulan Nadarajah, The University of Queensland, Australia Md. Rakibuzzaman Shah, The University of Queensland, Australia Geev Mokryani, Imperial College London, UK Abdun Naser Mahmood, The University of New South Wales, Australia Bharat Singh Rajpurohit, Indian Institute of Technology Mandi, India Md. Rabiul Islam, University of Technology Sydney, Australia vi Editorial Advisory Board B. Azzopardi, Kaunas University of Technology, Lithuania Ayaz Chowdhury, Swinburne University of Technology, Australia Farhad Shahania, Curtin University, Australia G. A. Taylor, Brunel University, UK F. M. Rabiul Islam, The University of New South Wales, Australia Jin Yang, Aston University, UK Hemanshu Roy Pota, The University of New South Wales, Australia Alireza Soroudi, University of Tehran, Iran Adnan Anwar, The University of New South Wales, Australia Asheesh K. Singh, Motilal Nehru National Institute of Technology Allahabad, India Preface Recent concerns regarding the environmental protection and sustainable development have resulted in there being a critical need for cleaner energy technologies. Some potential solutions have evolved including energy conservation through improved energy efficiency, reductions in the use of fossil fuels, and increases in the supply of environmental-friendly energy sources which has led to the use of intermittent renewable energy sources (RESs). These RESs are connected close to loads in the distribution network to reduce transmission losses and delay in the upgrade of transmission systems. The inclusion of renewable sources gives rise to a new set of problems which are due to the intermittency of the sources and the dynamics of interfacing equipments. Therefore, it is essential to investigate the potential challenges of renewable energy integration and to find out the effective and innovative solutions. This book includes different aspects of renewable energy integration—from the current trends of renewable energy integration to the current development of smart grids. Chapter 1 of this book discusses the importance of green energy which is structured into two parts: (i) the available knowledge with regard to the general decision-making processes is described, followed by a critical perspective about today’s decision making and (ii) a review of three enhanced approaches using Real Options Theory, Multi-Criteria Decision Analysis, and Multi-Criteria Cost Benefit Analysis, which are applied to RES decision making from the personal or investment point of view as well to the policy and the latter pan-European point of view. Various aspects, such as classification and specifications of the grid codes, the anomalies that exist between the grid codes developed and standards used in conventional power plants are discussed in Chap. 2 and a fault-ride-through criteria by satisfying these grid codes are developed in Chap. 3 where the criteria is tested on New Zealand power systems. Chapter 4 presents a voltage imbalance sensitivity analysis and stochastic evaluation based on Monte Carlo method carried out based on the ratings and locations of single-phase grid-connected rooftop PVs in a residential low voltage distribution network. On the other hand Chap. 5 includes comparative studies on the performance evaluation of grid-connected photovoltaic systems with different maximum power point tracking techniques. vii viii Preface One of the most important tasks in renewable energy integration is to determine optimal size and location of renewable energy sources which is discussed in Chap. 6 in which wind energy is considered as a renewable energy sources (RESs). After determining the optimal size and location, it is essential to investigate the characteristics of RESs and the steady state characteristics of wind energy conversion systems (WECSs) is presented in Chap. 7 from where it can be seen that WECSs affect the performance of power systems. A detailed study in which the effects of variable-speed wind generators to frequency regulation and oscillation damping is discussed elaborately in Chap. 8. The behaviors of power systems change with the penetration of RESs and Chap. 9 discusses some power management approaches for low and medium voltage distribution networks. The negative impacts of RESs need to be minimized for stable and reliable system operation. Keeping this in mind, a new control methodology is proposed in Chaps. 10 and 11 which incorporates a review study on a new load, plug-in hybrid electric vehicles in power distribution networks. The coordination and aggregation of RESs during emergency conditions are discussed in Chaps. 12 and 13, respectively. Since the cost is an important issue for power system operation, this aspect of study for a residential application is presented in Chap. 14. The latest trend in the area of renewable energy integration is the operation of power system in a smarter way. The operation of interconnected smart grids with self-healing capability is addressed in Chap. 15 and an agent-based scheme for smart-grid protection and security is presented in Chap. 16. In the last two chapters (Chaps. 15 and 17), the vulnerability analysis of complex smart grids is discussed from the cyber attacks and renewable energy integration points of view. Contents 1 Green Energy and Technology: Choosing Among Alternatives . . . Brian Azzopardi 1 2 Grid Codes: Goals and Challenges . . . . . . . . . . . . . . . . . . . . . . . Pradeep Kumar and Asheesh K. Singh 17 3 Fault Ride-Through Criteria Development . . . . . . . . . . . . . . . . . Nirmal-Kumar C. Nair and Waqar A. Qureshi 41 4 High Penetration of Rooftop Photovoltaic Cells in Low Voltage Distribution Networks: Voltage Imbalance and Improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Farhad Shahnia and Arindam Ghosh 5 6 7 8 9 69 Performance Evaluation of Grid-Connected Solar Photovoltaic (SPV) System with Different MPPT Controllers . . . . R. Singh and B. S. Rajpurohit 97 Optimal Siting and Sizing of Wind Turbines Based on Genetic Algorithm and Optimal Power Flow . . . . . . . . . . . . . Geev Mokryani and Pierluigi Siano 125 Power Flow Analysis and Reactive Power Compensation of Grid Connected Wind Energy Conversion Systems . . . . . . . . . J. Ravishankar 145 Contribution of Variable-Speed Wind Generators to Frequency Regulation and Oscillation Damping in the United States Eastern Interconnection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yong Liu, J. R. Gracia, T. J. King and Yilu Liu Power Management of Low and Medium Voltage Networks with High Density of Renewable Generation . . . . . . . . . . . . . . . . M. A. Barik, H. R. Pota and J. Ravishankar 169 189 ix x 10 Contents Integration of Green Energy into Power Distribution Systems: Study of Impacts and Development of Control Methodology . . . . N. K. Roy and H. R. Pota 209 11 Integrating Smart PHEVs in Future Smart Grid . . . . . . . . . . . . . F. R. Islam and H. R. Pota 12 Coordinating Distributed Energy Resources During Microgrid Emergency Operation. . . . . . . . . . . . . . . . . . . . . . . . . C. Gouveia, D. Rua, C. L. Moreira and J. A. Peças Lopes 259 A Novel Aggregation Technique Using Mechanical Torque Compensating Factor for DFIG Wind Farms . . . . . . . . . M. A. Chowdhury 305 13 14 15 DC Grid Interconnection for Conversion Losses and Cost Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. K. Chauhan, B. S. Rajpurohit, S. N. Singh and F. M. Gonzalez-Longatt Interconnected Autonomous Microgrids in Smart Grids with Self-Healing Capability . . . . . . . . . . . . . . . . . . . . . . . . . . . . Farhad Shahnia, Ruwan P. S. Chandrasena, Sumedha Rajakaruna and Arindam Ghosh 239 327 347 16 Agent-Based Smart Grid Protection and Security . . . . . . . . . . . . Md Shihanur Rahman and H. R. Pota 17 Vulnerabilities of Smart Grid State Estimation Against False Data Injection Attack . . . . . . . . . . . . . . . . . . . . . . . . . . . . Adnan Anwar and Abdun Naser Mahmood 411 Impediments and Model for Network Centrality Analysis of a Renewable Integrated Electricity Grid . . . . . . . . . . . . . . . . . A. B. M. Nasiruzzaman, Most. Nahida Akter and H. R. Pota 429 18 383 Chapter 1 Green Energy and Technology: Choosing Among Alternatives Brian Azzopardi Abstract The primary renewable energy system (RES) investment decisionmaking criteria are economics. These criteria are focused on the RES and its support ancillary infrastructure technical superiorities, such as efficiency and cost, which is reasonable in the context of generous financial support schemes. However, when financial supports are phased out the energy market becomes technologically diversified environmental, political and social concerns, which include both quantitative as well as qualitative criteria, become significant. The technical superiorities may fail to describe RES or the relevant technology properly. This chapter is structured in two parts. Firstly, the available knowledge with regards to the general decision making processes is described, followed by a critical perspective about today’s decision making. The second part presents a review of three enhanced approaches using Real Options Theory, Multi-Criteria Decision Analysis and Multi-Criteria Cost Benefit Analysis which are applied to RES decision making both from the personal or investment point of view as well to the policy and the latter pan-European point of view. Finally, the society challenges are discussed within this context.  Keywords Decision making Renewable energy system (RES) (RO) theory Multi-criteria analysis (MCA)   Real options B. Azzopardi (&) Faculty of Electrical and Electronics, Department of Electrical Energy Systems and Renewable Energy Centre, Kaunas University of Technology (KTU), Studentu˛ g. 48, LT-51367 Kaunas, Lithuania e-mail: [email protected] J. Hossain and A. Mahmud (eds.), Renewable Energy Integration, Green Energy and Technology, DOI: 10.1007/978-981-4585-27-9_1,  Springer Science+Business Media Singapore 2014 1 2 B. Azzopardi 1.1 Introduction Historically, the choice of energy has been economics and local conditions. Our society has been driven to choose inexpensive energy. However nowadays, the technical superiorities of energy systems may fail to describe for instance renewable energy systems (RESs) or its technology properly. In this chapter, the RESs decision making process is examined with a number of analytical lenses that may not give priority to their technological superiorities. Although the real life decision-making process is far from the aspired process in this chapter, this chapter will provide the understanding of the complex multidisciplinary decision making approach that today’s experts and policy makers are faced to address the challenges that society will dictate in the future. The large scale definition in this chapter is not limited to large system size magnitudes such as in Mega Watt equivalent but also considers the high deployment rates of micro-generation which when collected together may provide a large scale renewable power generation potential. 1.2 The Decision-Process Complexity The decision process starts when there is more than one alternative to a solution. As will be described later on in the second part of the chapter, with the use of Real Options (RO) Theory decision-process kicks-off even between two simple alternatives do nothing or do something. There is no fixed framework or a single sequential approach how to achieve to the best decision. Figure 1.1 tries to depict the complexity of choosing among alternatives.The first phase is the Problem Definition which is the crucial stage in decision-making. It is usually difficult or impossible to fully complete one component in the process without reflecting on the other components within a decision making process. This first phase groups the components into more malleable and therefore more realistic manner. This phase involve data processing that filters the relevant data and the feasible alternatives by their attributes leading to objective mapping. The criteria description helps the evaluation which is subjectively mapped to quantitative of qualitative attributes. While several components of the decision making process may be considered in parallel, there is no dictated or standardised procedure of what component comes before the other. Hence, Fig. 1.1 to some difficulty tries to draw the interrelationships between all components. It also includes a very important component in today’s world, the perspective of the decision maker. Information and data can be gathered to understand more holistically the perspective of the decision maker being at political level, business level or individual customer level. Perspective change depending on the decision maker position and during the next phase due importance may be provided. This will lead to the most 1 Green Energy and Technology: Choosing Among Alternatives 3 Fig. 1.1 The complexity of choosing among alternatives missing aspect in decision making which is usually referred to ‘feedback’ and will help finding the trade-off between different decision makers’ perspectives. The objective of a decision making process is the focus of the problem definition. The objective may have a multi-dimension perspective and several impacts. This is illustrated by the following example for decision making: • To integrate nationwide renewable energy systems, an example using multicriteria decision making technique is further illustrated in second part of this chapter. • To inform stakeholders including policy, business and end-user on diversified renewable energy technology for example in case of photovoltaic (PV) technologies. An example is also illustrated in second part of the chapter. 4 B. Azzopardi • To evaluate production high throughput practices in producing renewable energy systems or components. The second phase is the modelling and decision analysis. Figure 1.1 shows a wide range of techniques that may be used, while the importance of results can differ for decision makers. The decision analytics methods may be undertaken combined such as with simulation models which are fed to multi-attribute utility analysis. There is an extensive classic works on decision making techniques [1, 2] which goes beyond the scope for this chapter, including aspects related to the behavioural viewpoint in Kahneman et al. [3] which aspect has already been highlighted above. In the next subsections, a brief description is given to all the named techniques. 1.2.1 Voting In voting methods, the stakeholders that have the right to vote can voice up and choose democratically an alternative over another. However this allows for the possibility of political interference and may not result in complete unbiased solution to be the right choice. Voting can take many forms such as using simple voting system or preferential voting system. Voting technique may also inform decision makers to form the ‘‘big picture’’ that is the holistic approach and fed back to the decision support system. 1.2.2 Cost-Benefit Cost-Benefit Analysis (CBA) computes the ‘‘net present value’’ (NPV) which is usually monetary value based on one time snap-shot all the benefits and costs of a project, decision or policy. CBA has been widely used in RES projects to justify investment or compare projects and sometimes even coupled by other economic theories such as the RO Theory which will be further described in the second part of this chapter. Related formal techniques include cost-effectiveness analysis, cost–utility analysis, economic impact analysis, fiscal impact analysis, and social return on investment (SROI) analysis. When Life Cycle Costing (LCC) is incorporated within CBA, the technique finds out the total cost of ownership. It is a structured methodology which deals with all the elements of this total cost of ownership. Hence an expenditure profile of a system ov...
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