Abstract
This paper proposes a chance constrained formulation to tackle the uncertainties of the load and wind turbine generator in transmission network expansion planning. The Monte Carlo simulation and analytical probabilistic power flow analysis are combined by simulating the probability density function of wind farm output and applying it in analytical probabilistic load flow calculation. A chance constrained transmission network expansion planning formulation considering the uncertainties of both the load and wind turbine generator is worked out. The optimization problem is solved with a two-step genetic algorithm. The formulation proposed is more computationally efficient and can deal with uncertainties in transmission network expansion planning, the efficiency shown through a test example. This work is supported by National Natural Science Foundation of China (No. 50677019) and Research Grants Council of Hong Kong (No. PolyU G-YF26).
| Original language | English |
|---|---|
| Pages (from-to) | 20-24 |
| Number of pages | 5 |
| Journal | Dianli Xitong Zidonghua/Automation of Electric Power Systems |
| Volume | 33 |
| Issue number | 2 |
| Publication status | Published - 25 Jan 2009 |
Keywords
- Chance constrained programming
- Load uncertainty
- Probabilistic load flow calculation
- Transmission network planning
- Wind farm
ASJC Scopus subject areas
- Control and Systems Engineering
- Energy Engineering and Power Technology
- Computer Science Applications
- Electrical and Electronic Engineering