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Content Provider | IET Digital Library |
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Author | Jiang, Xin Chen, Hongkun Xiang, Tieyuan |
Abstract | A probabilistic approach with considering the peaking characteristics of wind power is proposed to determine the maximum wind power penetration level (WPPL). To evaluate the effect wind peaking characteristics brought to the hosting capacity of systems, a detailed simulation of wind speed/load distributions over a long period is required. Thus, taking an hour as the time scale, the time-sharing peaking characteristics of wind power are discussed by describing the hourly distribution of wind output and load. Based on the chance constrained programming, a WPPL model is established in this study. The optimisation process is achieved using the improved particle swarm optimisation algorithm based on Monte–Carlo simulation. This proposed approach has been applied to an actual power system in central China. Simulation results show that the WPPL would be too optimistic without considering the anti-peaking characteristics of wind power. Besides various sensitivity analyses are performed to assess the effect of other parameters on the maximum penetration level. |
Starting Page | 2466 |
Ending Page | 2473 |
Page Count | 8 |
ISSN | 17518687 |
Volume Number | 9 |
e-ISSN | 17518695 |
Issue Number | Issue 16, Dec (2015) |
Journal | IET Generation, Transmission & Distribution |
Publisher Date | 2015-12-03 |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Chance Constrained Programming Energy ReSource Improved Particle Swarm Optimisation Algorithm Load Distribution Maximum Wind Power Penetration Level Monte Carlo Method Monte Carlo Simulation Optimisation Technique Particle Swarm Optimisation Power System Power System Economics Power System Managemen Power System Operation Time Scale Wind Power Wind Power Peaking Characteristic Effect Wind Power Plant Wind Speed WPPL |
Content Type | Text |
Resource Type | Article |
Subject | Energy Engineering and Power Technology Control and Systems Engineering Electrical and Electronic Engineering |
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