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| Content Provider | IET Digital Library |
|---|---|
| Author | Gouin, Victor Herault, Marie Cecile Alvarez Raison, Bertrand |
| Abstract | Planning the distribution network of the future involves forecasting the most likely scenario to make appropriate investment decisions. Many uncertainties concerning, e.g. the evolution of conventional loads, renewable production and electric vehicles (EVs) make it difficult to predict the location of the distribution network's weaknesses (overvoltages, undervoltages and overcurrents) and their occurrence. In some cases, alternative solutions such as demand response (DR) and reconfiguration can remove the constraints and prevent expensive network investment. This study proposes a two-stage algorithm that is able to give the probability that no technical constraints will appear as a function of the reinforcement cost with and without using DR and/or reconfiguration. The first stage of the algorithm consists in running Monte Carlo simulations based on realistic scenarios for loads, EVs and renewable production development provided by French governmental roadmaps. The cost of reinforcement per line and per hour of constraints enables selection of the feeders, where DR (solved with linear programming) and/or reconfiguration (exhaustive research) will be implemented in the second stage of the algorithm to remove these constraints. The methodology is applied to a real part of a French distribution network. |
| Starting Page | 4536 |
| Ending Page | 4545 |
| Page Count | 10 |
| ISSN | 17518687 |
| Volume Number | 12 |
| e-ISSN | 17518695 |
| Issue Number | Issue 20, Nov (2018) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-gtd/12/20 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2018.5833 |
| Journal | IET Generation, Transmission & Distribution |
| Publisher Date | 2018-08-29 |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Alternative Solutions Appropriate Investment Decisions Conventional Loads Demand Response Distribution Network Distribution Network Expansion Planning Electric Vehicle EVs Expensive Network Investment French Distribution Network Investment Linear Programming Monte Carlo Method Monte Carlo Simulation Method Optimisation Technique OverCurrent Power Distribution Economics Power Distribution Planning Power Generation Planning Power System Economics Power System Managemen Power System Operation Power System Planning And Layout Power Transmission Planning Realistic Scenario Reconfiguration Reinforcement Cost Renewable Production Development Stochastic Integration Technical Constraint Two-stage Algorithm Undervoltages |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering |
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