Includes bibliographical references and index.

Machine generated contents note: ch. 1 Introduction to Renewable Energy Systems / Joao P.S. Catalao -- 1.1. An Overview of Renewable Energy Systems -- 1.1.1. Climate Change -- 1.1.2. Renewable Energy Trend -- 1.2. Types of Renewable Energy Systems -- 1.2.1. Introduction -- 1.2.2. Wind Power -- 1.2.3. Solar Energy -- 1.2.4. Geothermal Power -- 1.2.5. Hydro Power -- 1.2.6. Bioenergy -- 1.2.7. Ocean Power -- 1.3. Economic Aspects of Renewable Energy Systems -- 1.3.1. Introduction -- 1.3.2. Affecting Factors -- 1.3.3. Life-Cycle Costs -- 1.3.4. Economic Trend of Renewable Energy Systems -- 1.4. Opportunities and Challenges of Renewable Energy Systems Integration -- 1.4.1. Renewable Energy Systems Integration Opportunities -- 1.4.2. Renewable Energy Systems Integration Challenges and Barriers -- 1.4.3. Alleviating the Challenges and Barriers -- 1.4.4. Current Trends and Future Prospects -- 1.5. The Need for Optimization Tools to Solve Problems Related to Renewable Energy Systems -- 1.6. Conclusions -- Acknowledgments -- References -- ch. 2 Introduction to Optimization / Ilker Ustoglu -- 2.1. Introduction -- 2.2. Formulation of Optimization Problem -- 2.2.1. General Models of Optimization Problems -- 2.2.2. Convex Optimization -- 2.2.3. Basic Concepts and Models of Linear Optimization -- 2.3. Solution Techniques for Unconstrained Optimization -- 2.3.1. Nelder -- Mead Method -- 2.3.2. Golden Section Search -- 2.3.3. Fibonacci Search -- 2.3.4. Hooke and Jeeves' Method -- 2.3.5. Gradient Descent Method -- 2.3.6. Coordinate Descent Method -- 2.4. Solution Techniques for Constrained Optimization and Relevant Applications to Renewable Energy Systems -- 2.4.1. Genetic Algorithm -- 2.4.2. Particle Swarm Optimization -- 2.4.3. Simulating Annealing -- 2.4.4. Ant Colony Optimization -- 2.4.5. Tabu Search -- 2.4.6. Firefly Algorithm -- 2.4.7. Artificial Bee Colony Algorithm -- 2.4.8. Artificial Immune System -- 2.4.9. Game Theory -- 2.4.10. Simplex Technique Specifically for Mixed Integer Linear Programming Concept -- 2.4.11. Optimal Control Technique -- 2.5. Conclusion and Discussion -- References -- ch. 3 Optimal Procurement of Contingency and Load Following Reserves by Demand Side Resources Under Wind-Power Generation Uncertainty / Nikolaos G. Paterakis -- 3.1. Introduction -- 3.2. Mathematical Model -- 3.2.1. Overview and Modeling Assumptions -- 3.2.2. Objective Function -- 3.2.3. Constraints -- 3.3. Case Studies -- 3.3.1. Wind-Power Production Scenario Generation -- 3.3.2. Illustrative Example -- 3.3.3. Application on a 24-Bus System -- 3.3.4. Computational Statistics -- 3.4. Conclusions -- Appendix A: 24-Bus System Test System Data -- Nomenclature -- Sets and Indices -- Parameters -- Variables -- References -- ch. 4 Optimum Bidding of Renewable Energy System Owners in Electricity Markets / Ting Dai -- 4.1. Renewable Energy System Owners in Electricity Markets -- 4.1.1. Electricity Market Overview -- 4.1.2. Importance of Integrating Renewables into the Electricity Market -- 4.1.3. Current Market Rules for Renewable Energy System Owners in North America -- 4.2. Price-Taker Models -- Multistage Stochastic Programming Approach -- 4.2.1. Multistage Stochastic Programming Approach -- 4.2.2. Scenario Generation and Reduction Method -- 4.2.3. Risk Management -- 4.2.4. Bidding Strategy Models for Price-Taker Renewable Energy Owner -- 4.2.5. Mitigating the Trading Risk by Purchasing Additional Power from Conventional Energy Owner -- 4.3. Price-Maker Models -- MPEC Approach -- 4.3.1. Why Consider Wind Power Energy Owners as Price-Makers? -- 4.3.2. Price-Maker Models -- MPEC Approach -- 4.3.3. Mathematical Formulation and Conversion -- 4.3.4. Case Study -- 4.4. Summary and Conclusion -- 4.5. Appendix: IEEE Reliability Test System -- References -- ch. 5 Impacts of Accurate Renewable Power Forecasting on Optimum Operation of Power System / Akin Tascikaraoglu -- 5.1. Introduction -- 5.2. Fundamentals of Renewable Power Forecasting Techniques -- 5.2.1. Wind Speed and Power Forecasts -- 5.2.2. PV Irradiance and Power Forecasts -- 5.3. State-of-the-Art in Renewable Power Forecasting -- 5.3.1. Combined Renewable Power Forecasting Methods -- 5.3.2. Spatiotemporal Renewable Power Forecasting Methods -- 5.3.3. Probabilistic Renewable Power Forecasting Methods -- 5.4. The Literature on the Contribution of High-Accuracy Renewable Power Forecasts in Optimum Power System Operation -- 5.5. Discussion and Conclusion -- References -- ch. 6 Optimum Transmission System Expansion Offshore Considering Renewable Energy Sources / Madeleine Gibescu -- 6.1. Introduction -- 6.2. Classification of TEP Formulations -- 6.2.1. Regulated Versus Deregulated -- 6.2.2. Centralized Versus Decentralized Decision-Making Process -- 6.2.3. Deterministic versus Nondeterministic Methods -- 6.2.4. Static versus Dynamic Methods -- 6.3. Transmission Expansion Planning in Europe -- 6.4. Review of TEP Formulations -- 6.4.1. Formulation of Transmission Expansion Planning Problem -- 6.4.2. Simplifying the Problem Formulation -- 6.4.3. Static Transmission Expansion Planning -- 6.4.4. Dynamic Transmission Expansion Planning -- 6.5. Algorithms and Models for Solving TEP -- 6.5.1. Exact Algorithms -- 6.5.2. Heuristic & MetaHeuristic Algorithms -- 6.6. Numerical Simulation -- 6.6.1. Assumptions -- 6.6.2. Defining Development Stages -- 6.6.3. Data Clustering -- 6.6.4. Numerical Results -- 6.6.5. Comparison -- 6.6.6. Discussion -- 6.7. Conclusions and Future Research -- 6.7.1. Conclusions -- 6.7.2. Reflection -- References -- ch. 7 Optimum Sizing and Siting of Renewable-Energy-based DG Units in Distribution Systems / Moein Moeini-Aghtaei -- 7.1. Introduction -- 7.2. Renewable-Energy-Based DG Models -- 7.2.1. Deterministic Models -- 7.2.2. Stochastic Models -- 7.3. Effects of DGs on Distribution Networks -- 7.3.1. Voltage Profile -- 7.3.2. Power Losses -- 7.3.3. Power Distribution System Reliability -- 7.3.4. Costs and Benefits -- 7.3.5. Voltage Stability -- 7.3.6. Fault Current -- 7.3.7. Harmonic Distortion -- 7.3.8. Reactive Power Supply -- 7.4. Optimal Placement -- 7.4.1. Problem Definition -- 7.4.2. Solution Methodology -- 7.4.3. Linearized DG Placement Problem -- 7.4.4. Stochastic Assessment of DG Placement Problem -- 7.5. Case Study -- 7.5.1. Case Under Study and Assumptions -- 7.5.2. Simulation Results -- 7.6. Conclusions -- References -- ch. 8 Optimum Design of Small-Scale Stand-Alone Hybrid Renewable Energy Systems / Joao P.S. Catalao -- 8.1. Introduction -- 8.2. Hybrid Energy Systems Modeling -- 8.2.1. Photovoltaic Panel Modeling -- 8.2.2. Wind Turbine Modeling -- 8.2.3. Battery Energy Storage System Modeling -- 8.2.4. Charge Controller -- 8.2.5. Power Converter -- 8.3. Hybrid Energy Systems Sizing and Optimization -- 8.4. Rural Electrification in a Remote Community -- 8.5. Conclusions -- List of Symbols -- Acknowledgments -- References.

"Optimization in Renewable Energy Systems covers all major areas where optimization techniques have been applied to reduce uncertainty or improve results in renewable energy systems (RES) and related power system fields. The power production of RES is highly volatile and unpredictable, leading to the need for optimization-based planning and operation in order to maximize economy while sustaining performance. Written by an international group of experts, the book begins with an introduction to RES and optimization, then covers a wide range of applications in both large and small scale operations, including optimum operation of electric power systems with large penetration of RES, power forecasting, transmission system planning, and DG sizing and siting for distribution systems and end-user premises."--Page [4] of cover.