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| 【獎(jiǎng)勵(lì)】 本帖被評(píng)價(jià)9次，作者danielxu1983增加金幣 7.2 個(gè) | ||
[資源]
Modelling Distributed Energy Resources in Energy Service Networks
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1 Challenges in effectively managing energy resources, infrastructures and conversion technologies 1 1.1 Global urbanisation and efficiency of energy systems 1 1.2 Evolution of urban energy systems 5 1.3 Integrated management of energy systems 8 2 Integrated modelling review 13 2.1 Modelling issues concerning DERs 13 2.1.1 Meeting the challenges of decentralised power generation 13 2.1.2 Impacts of cogeneration technology on electric networks 15 2.1.3 Impacts of PHEV technology on electric networks 19 2.2 Approaches on modelling multiple energy networks 24 2.2.1 Multi-generation analysis 24 2.2.2 Integrated energy transportation systems 25 2.2.3 Modelling of energy hubs 26 2.2.4 Integrated natural gas and electricity studies 27 3 Modelling of energy service networks 29 3.1 Modelling electrical networks 29 3.1.1 Fundamentals of electrical systems 29 3.1.2 Defining the electrical load flow problem 31 3.1.3 Nodal formulation and the admittance matrix 32 3.2 Modelling natural gas networks 35 3.2.1 Fundamentals of natural gas systems 35 3.2.2 Defining the natural gas load flow problem 37 3.2.3 Nodal formulation and the incidence matrix 38 3.3 Analogies in energy service networks 42 3.3.1 Modelling components and variables 42 3.3.2 The Newton–Raphson algorithm 43 3.3.2.1 The electrical system Jacobian matrix 44 3.3.2.2 The natural gas system Jacobian matrix 46 3.3.2.3 Load flow conclusions 48 4 Modelling embedded technologies in energy service networks 51 4.1 Modelling on-load tap-changer transformers 51 4.1.1 Fundamentals of OLTC transformers 51 4.1.2 OLTC modelling equations 53 4.2 Modelling compressor stations 56 4.2.1 Fundamentals of compressor stations 56 4.2.2 Compressor modelling equations 58 4.3 Modelling CHP technologies 59 4.3.1 Fundamentals of combined heat and power units 59 4.3.2 Nodal formulation of natural gas networks with CHPs 65 4.3.3 Thermal energy storage management equations 68 4.4 Modelling PHEV technologies 71 4.4.1 Fundamentals of plug-in hybrid electric vehicles 71 4.4.2 Nodal formulation of electrical networks with PHEVs 81 4.4.3 Electrochemical energy storage management equations 84 5 Time-coordinated optimal power flow for energy service networks 89 5.1 TCOPF problem outline 89 5.1.1 Problem description 89 5.1.2 Optimisation solver 93 5.1.3 Input data and assumptions of the TCOPF tool 94 5.2 TCOPF objective functions 96 5.2.1 Plug and forget 96 5.2.2 Fuel cost 96 5.2.3 Energy loss 97 5.2.4 Energy cost 97 5.2.5 Composite objectives 97 5.3 Mathematical TCOPF formulation 98 5.3.1 Objective function formulations 98 5.3.1.1 For plug-and-forget scenario 98 5.3.1.2 For fuel cost minimisation 99 5.3.1.3 For energy loss minimisation 99 5.3.1.4 For energy cost minimisation 100 5.3.1.5 For composite objective minimisation (e.g. cost of spot prices vs. cost of emissions) 100 5.3.2 Constraints 101 5.3.2.1 Concerning electrical networks 102 5.3.2.2 Concerning natural gas networks 102 5.3.2.3 Concerning PHEV devices embedded in electrical networks 103 5.3.2.4 Concerning CHP devices embedded in natural gas networks 103 5.3.3 TCOPF problem and solution characteristics 104 6 Optimising DERs in energy service networks: a case study 107 6.1 TCOPF energy service network case studies 107 6.1.1 Input data and assumptions 107 6.1.2 Description of case studies and energy system parameters 110 6.2 Techno-economical results 116 6.2.1 Overview 116 6.2.2 Integrated versus non-integrated systems 117 6.2.3 Natural gas network 120 6.2.4 CHP technology 123 6.2.5 Electrical network 130 6.2.6 PHEV technology 135 6.3 Summary of results 142 7 Modelling electric vehicle mobility in energy service networks 145 7.1 Modelling PHEV mobility 146 7.1.1 Modelling methods 146 7.2 Combining agent-based and load flow models 147 7.2.1 Agent-based model for vehicles 148 7.2.2 PHEV optimal power flow formulation 149 7.2.2.1 For PHEV charging cost minimisation scenario 150 7.3 ABM–TCOPF case study for charging of PHEVs 151 7.3.1 Input data and assumptions 151 7.3.1.1 Driver profiles 151 7.3.1.2 PHEV features 152 7.3.1.3 City layout 152 7.3.1.4 Electricity load profiles and network characteristics 153 7.3.2 Case studies and energy system parameters 153 7.4 Techno-economical results 154 7.4.1 Agent-based model results 154 7.4.2 Optimal power flow model results 159 8 Concluding remarks 163 8.1 Summary and contributions 163 8.2 Research beneficiaries 166 8.3 Future work suggestions 166 |
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