Distribution System Planning: Evolution of Methodologies and Digital Tools for Energy Transition

Description

Distribution systems drive energy and societal transition. System planning enables investments to be made in the right place, at the right time and with the right technology. Distribution System Planning is centered on the evolution of planning methods that will best support this transition, and describes the historical context and concepts that enable planning, its challenges and key influencing factors to be grasped. It also analyzes the impact of the development of renewable and decentralized energy resources, government recommendations and distributor initiatives to promote their integration. Through the use of case studies, this book provides examples of how planning methodologies have evolved, as well as an overview of new and emerging solutions. Cover Title Page Copyright Page Contents Foreword List of Notations List of Acronyms Introduction Chapter 1. Power Systems 1.1. Electricity: an essential and complex product 1.2. History of industrial power systems 1.2.1. Discovery of direct current and the design of the first generators 1.2.2. Birth of the first power systems: public lighting systems 1.2.3. The expansion of AC 1.2.4. The revival of DC 1.2.5. Development of power systems 1.2.6. The frequency choice for power systems 1.2.7. Choosing voltage levels for power systems 1.2.8. Structuring the power system 1.3. Technical description of the power system 1.3.1. The three-phase system 1.3.2. Connection mode for components of the power system 1.3.3. Electrotechnical imperfections of power systems 1.4. Distribution systems 1.4.1. HV/MV primary substations 1.4.2. MV/LV distribution substations 1.5. Opening of the energy markets: appearance of new players 1.5.1. Market deregulation versus technical regulation 1.5.2. Historical players in the power system 1.5.3. Market models around the world 1.5.4. Additional players in deregulated systems 1.5.5. Example of the European model 1.6. Roles of consumers and producers 1.6.1. Development of distributed energy resources based on renewable energies 1.6.2. Change in the status of the consumer: the “prosumer” 1.6.3. Distributed energy resources 1.7. Conclusion 1.8. References Chapter 2. Principles of Power Distribution System Planning 2.1. Methods of power distribution system planning 2.1.1. Definition 2.1.2. The different time scales in planning 2.1.3. France’s power distribution system planning 2.1.4. Indicators used in planning and the solutions commonly employed to meet them 2.1.5. Planning options 2.1.6. Application of techno-economic formulas on simple examples 2.2. Typical architectures of non-distributed neutral distribution systems (European system) 2.2.1. MV system architectures 2.2.2. LV system architectures 2.3. Typical architectures of distributed neutral systems (North American system) 2.3.1. MV system architectures 2.3.2. LV system architectures 2.3.3. Comparison of architectures 2.4. Other architectures encountered in the world 2.4.1. Multi-divided and multi-connected structure (Japan and China) 2.4.2. Loop and sub-loop system (Madrid, Berlin and China) 2.4.3. Two voltage levels, two types of distribution systems (Singapore) 2.4.4. Secured feeder and spot network (Indonesia, Malaysia) 2.4.5. United Arab Emirates 2.5. Conclusion 2.6. References Chapter 3. Integration of Distributed Energy Resources in Distribution System Planning 3.1. Introduction 3.2. Impact of distributed energy resources on the planning methods of distribution power systems 3.2.1. Problems brought about by the appearance of DERs 3.2.2. A need for an advanced planning tool that integrates DERs 3.2.3. Government policy recommendations on the evolution of distribution system planning methods 3.2.4. Transitioning to planning with DERs 3.3. Phase 1: traditional “fit and forget” planning 3.3.1. Allocation of DER connection costs 3.3.2. Estimated hosting capacity of the distribution system 3.3.3. Locational Net Benefit Analysis 3.3.4. Distribution Investment Deferral Framework 3.4. Phase 2: planning with DERs 3.4.1. List of possible insertion solutions 3.4.2. Planning without flexibility markets 3.4.3. Planning with flexibility markets 3.5. Conclusion 3.6. References Chapter 4. Planning Case Studies 4.1. Introduction 4.2. State of the art of distribution systems with DERs 4.2.1. New diagnostic criteria for distribution systems 4.2.2. General principle for estimating the maximum DER power without imposing constraints on the system 4.2.3. Decision support tools under uncertainty based on the Monte Carlo method 4.3. Dense urban interconnected systems 4.3.1. Structural solution: topological optimization of electrical distribution systems 4.3.2. Case study 3: non-wire alternatives 4.4. Rural interconnected systems 4.4.1. Case study 4: NWA to integrate DERs into LV rural distribution systems 4.4.2. Case study 5: using storage to defer investments in LV systems 4.5. Off-grid systems 4.5.1. Case study 6: rural electrification – Cambodia 4.5.2. Case study 7: high cost, difficult access areas – Australia 4.6. Conclusion 4.7. References Chapter 5. Mathematical Tools for Planning 5.1. Introduction 5.2. Inputting data for the planning problem 5.2.1. Preliminary definitions 5.2.2. Technical and economic data 5.2.3. Structure of the initial electrical system 5.2.4. Topological data 5.2.5. Definition of sizing situations 5.3. Planning: a multi-objective optimization problem under constraints 5.3.1. Decision-making variables 5.3.2. Definition of the multi-objective function to be optimized 5.3.3. Defining constraints 5.3.4. Load distribution calculation 5.4. Algorithms for optimizing the planning of distribution systems 5.4.1. Analysis of the optimization problem 5.4.2. Breakdown of sub-problems to be optimized 5.4.3. Summary of optimization methods used in planning 5.4.4. Integration of uncertainties in planning 5.5. Conclusion 5.6. References Chapter 6. Mathematical Tools for Planning: Application to Case Studies 6.1. Introduction 6.2. Master-slave decomposition method with a feedback loop and use of metaheuristics: case study no. 1 6.3. Greedy decomposition method 6.3.1. Heuristics: case study no. 2a 6.3.2. Brute-force search: case study no. 2b 6.4. Linear programming 6.4.1. Consumption curtailment (demand response): case study no. 3a 6.4.2. Phase balancing problem – integer linear programming: case study no. 6 6.5. Nonlinear programming 6.5.1. Storage to remove system constraints: case study no. 5 6.5.2. Placement and sizing of storage and production units: case study no. 6 6.6. Integration of uncertainties 6.6.1. Monte Carlo method applied to the calculation of the DER HC and the technical and economic interest of flexibilities 6.6.2. Probabilistic method applied to the technical and economic interests of flexibilities: case study no. 3b 6.7. Conclusion 6.8. References Chapter 7. New Trends and Challenges 7.1. Introduction 7.2. New architectures and new products 7.2.1. A new set of values 7.2.2. New objects: virtualization of assets, case of the virtual lines of the Ringo Project 7.2.3. Renewed interest for direct current 7.2.4. New multi-objective systemic approaches 7.3. Integrated planning tools 7.3.1. Why integrate? 7.3.2. The challenges of data 7.3.3. Including control in planning models 7.3.4. The challenge of skills 7.4. New economic actors and new business models 7.4.1. Diversity of actors 7.4.2. Diversity of topics 7.4.3. Diversity of business models 7.5. Conclusion 7.6. References Conclusion Index EULA