Distribution System Planning

Marie-Cécile Alvarez-Herault is an associate professor at Grenoble INP, France, and holds the Enedis chair in Smart Grids.Victor Gouin is an engineer and researcher in electrical engineering at Roseau Technologies, France, which he co-founded.Trinidad Chardin-Segui is technical director at Schneider Electric, France.Alain Malot is portfolio strategy manager at Schneider Electric, France.Jonathan Coignard is a PhD student at Lancey Energy Storage, G2Elab, France, and an LBNL affiliate in the USA.Bertrand Raison is a professor at University Grenoble Alpes, France.Jérôme Coulet is a member of the Alps regional management of Enedis and a teacher at Ense3, Grenoble INP, France.

• Foreword xiNouredine HADJSAID and Pierre MALLETList of Notations xvList of Acronyms xxiiiIntroduction xxxvChapter 1 Power Systems 11.1 Electricity: an essential and complex product 11.2 History of industrial power systems 41.2.1 Discovery of direct current and the design of the first generators 41.2.2 Birth of the first power systems: public lighting systems 51.2.3 The expansion of AC 61.2.4 The revival of DC 71.2.5 Development of power systems 81.2.6 The frequency choice for power systems 111.2.7 Choosing voltage levels for power systems 141.2.8 Structuring the power system 161.3 Technical description of the power system 201.3.1 The three-phase system 201.3.2 Connection mode for components of the power system 271.3.3 Electrotechnical imperfections of power systems 291.4 Distribution systems 371.4.1 HV/MV primary substations 371.4.2 MV/LV distribution substations 411.5 Opening of the energy markets: appearance of new players 491.5.1 Market deregulation versus technical regulation 491.5.2 Historical players in the power system 491.5.3 Market models around the world 521.5.4 Additional players in deregulated systems 571.5.5 Example of the European model 581.6 Roles of consumers and producers 641.6.1 Development of distributed energy resources based on renewable energies 641.6.2 Change in the status of the consumer: the “prosumer” 701.6.3 Distributed energy resources 721.7 Conclusion 731.8 References 73Chapter 2 Principles of Power Distribution System Planning 812.1 Methods of power distribution system planning 812.1.1 Definition 812.1.2 The different time scales in planning 842.1.3 France’s power distribution system planning 862.1.4 Indicators used in planning and the solutions commonly employed to meet them 922.1.5 Planning options 1082.1.6 Application of techno-economic formulas on simple examples 1092.2 Typical architectures of non-distributed neutral distribution systems (European system) 1192.2.1 MV system architectures 1202.2.2 LV system architectures 1342.3 Typical architectures of distributed neutral systems (North American system) 1352.3.1 MV system architectures 1362.3.2 LV system architectures 1402.3.3 Comparison of architectures 1442.4 Other architectures encountered in the world 1442.4.1. Multi-divided and multi-connected structure (Japan and China) 1442.4.2 Loop and sub-loop system (Madrid, Berlin and China) 1452.4.3 Two voltage levels, two types of distribution systems (Singapore) 1462.4.4 Secured feeder and spot network (Indonesia, Malaysia) 1472.4.5 United Arab Emirates 1482.5 Conclusion 1492.6 References 150Chapter 3 Integration of Distributed Energy Resources in Distribution System Planning 1553.1 Introduction 1553.2 Impact of distributed energy resources on the planning methods of distribution power systems 1563.2.1 Problems brought about by the appearance of DERs 1563.2.2 A need for an advanced planning tool that integrates DERs 1603.2.3 Government policy recommendations on the evolution of distribution system planning methods 1623.2.4 Transitioning to planning with DERs 1653.3 Phase 1: traditional “fit and forget” planning 1683.3.1 Allocation of DER connection costs 1693.3.2 Estimated hosting capacity of the distribution system 1713.3.3 Locational Net Benefit Analysis 1733.3.4 Distribution Investment Deferral Framework 1753.4 Phase 2: planning with DERs 1813.4.1 List of possible insertion solutions 1813.4.2 Planning without flexibility markets 1833.4.3 Planning with flexibility markets 1893.5 Conclusion 1953.6 References 196Chapter 4 Planning Case Studies 2014.1 Introduction 2014.2 State of the art of distribution systems with DERs 2054.2.1 New diagnostic criteria for distribution systems 2054.2.2 General principle for estimating the maximum DER power without imposing constraints on the system 2064.2.3 Decision support tools under uncertainty based on the Monte Carlo method 2094.3 Dense urban interconnected systems 2174.3.1 Structural solution: topological optimization of electrical distribution systems 2174.3.2 Case study 3: non-wire alternatives 2434.4 Rural interconnected systems 2624.4.1 Case study 4: NWA to integrate DERs into LV rural distribution systems 2624.4.2. Case study 5: using storage to defer investments in LV systems 2754.5 Off-grid systems 2804.5.1 Case study 6: rural electrification – Cambodia 2804.5.2 Case study 7: high cost, difficult access areas – Australia 2904.6 Conclusion 2924.7 References 293Chapter 5 Mathematical Tools for Planning 2955.1 Introduction 2955.2 Inputting data for the planning problem 2955.2.1 Preliminary definitions 2955.2.2 Technical and economic data 3005.2.3 Structure of the initial electrical system 3025.2.4 Topological data 3055.2.5 Definition of sizing situations 3105.3. Planning: a multi-objective optimization problem under constraints 3125.3.1 Decision-making variables 3125.3.2 Definition of the multi-objective function to be optimized 3195.3.3 Defining constraints 3225.3.4 Load distribution calculation 3295.4 Algorithms for optimizing the planning of distribution systems 3405.4.1 Analysis of the optimization problem 3405.4.2 Breakdown of sub-problems to be optimized 3445.4.3 Summary of optimization methods used in planning 3465.4.4 Integration of uncertainties in planning 3515.5 Conclusion 3545.6 References 354Chapter 6 Mathematical Tools for Planning: Application to Case Studies 3576.1 Introduction 3576.2 Master-slave decomposition method with a feedback loop and use of metaheuristics: case study no 1 3606.3 Greedy decomposition method 3656.3.1 Heuristics: case study no 2a 3656.3.2 Brute-force search: case study no 2b 3716.4 Linear programming 3736.4.1. Consumption curtailment (demand response): case study no. 3a 3736.4.2 Phase balancing problem – integer linear programming: case study no 6 3786.5 Nonlinear programming 3796.5.1 Storage to remove system constraints: case study no 5 3796.5.2 Placement and sizing of storage and production units: case study no 6 3826.6 Integration of uncertainties 3836.6.1 Monte Carlo method applied to the calculation of the DER HC and the technical and economic interest of flexibilities 3836.6.2 Probabilistic method applied to the technical and economic interests of flexibilities: case study no 3b 3916.7 Conclusion 3986.8 References 399Chapter 7 New Trends and Challenges 4017.1 Introduction 4017.2 New architectures and new products 4027.2.1 A new set of values 4027.2.2 New objects: virtualization of assets, case of the virtual lines of the Ringo Project 4077.2.3 Renewed interest for direct current 4087.2.4 New multi-objective systemic approaches 4177.3 Integrated planning tools 4187.3.1 Why integrate? 4187.3.2 The challenges of data 4207.3.3 Including control in planning models 4227.3.4 The challenge of skills 4237.4 New economic actors and new business models 4247.4.1 Diversity of actors 4247.4.2 Diversity of topics 4257.4.3 Diversity of business models 4267.5 Conclusion 4277.6 References 427Conclusion 433Index 437