Sketch of Renewable Energy Production Simulation Platform ()
Jing Wang1,
Yunfeng Gao1,
Yuehui Huang1,
Yuefeng Wang1,
Jietan Zhang2
1Renewable Energy Department, China Electric Power Research Institute, Beijing, China.
2Renewable Energy Department, Qinghai Power Grid Corporation, Xining, China.
DOI: 10.4236/wjet.2015.33C010
PDF HTML XML
3,205
Downloads
3,890
Views
Citations
Abstract
Renewable Energy Production Simulation
Platform (REPS) is developed by China Electric Power Research Institute (CEPRI)
to simulate the operation of renewable energy in the power system. REPS takes
into account the characteristics of China’s electric power system, it can
assess the accommodation of renewable energy power and simulate the impact of
different renewable energy capacity on the operation of power system. Assessment
model and calculation process of REPS V1.3 is introduced in this article, and
annual consumptive capacity in one provincial power grid of China is evaluated
with the platform. REPS is of great guiding significance to electrical source planning.
With the sustained and rapid growth of renewable energy in China, power system
will be more and more dependent on REPS.
Share and Cite:
Wang, J. , Gao, Y. , Huang, Y. , Wang, Y. and Zhang, J. (2015) Sketch of Renewable Energy Production Simulation Platform.
World Journal of Engineering and Technology,
3, 65-71. doi:
10.4236/wjet.2015.33C010.
Conflicts of Interest
The authors declare no conflicts of interest.
References
[1]
|
Chen, C.L. (2008) Optimal Wind-Thermal Generating Unit Commitment. IEEE Transactions on Energy Conversion, 23, 273-280. http://dx.doi.org/10.1109/TEC.2007.914188
|
[2]
|
Marwali, M.K.C. and Shahidehpour, S.M. (2000) Coordination between Long-Term and Short-Term Generation Scheduling with Network Constraints. IEEE Transactions on Power Systems, 15, 1161-1167.
http://dx.doi.org/10.1109/59.871749
|
[3]
|
Handke, J., Handschin, E., Linke, K. and Sanders, H.-H. (1995) Coordination of Long- and Short-Term Generation Planning in Thermal Power Systems. IEEE Transactions on Power Systems, 10, 803-809.
http://dx.doi.org/10.1109/59.387920
|
[4]
|
Chen, C.L. (2007) Simulated Annealing-Based Optimal Wind-Thermal Coordination Scheduling. IET Generation, Transmission & Distribution, 1, 447-455. http://dx.doi.org/10.1049/iet-gtd:20060208
|
[5]
|
Handschin, E. and Slomski, H. (1990) Unit Commitment in Thermal Power Systems with Long-Term Energy Constraints. IEEE Transactions on Power Systems, 5, 1470-1477. http://dx.doi.org/10.1109/59.99401
|
[6]
|
Grothe, O. and Schnieders, J. (2011) Spatial Dependence in Wind and Optimal Wind Power Allocation: A Copula-Based Analysis. Energy Policy, 39, 4742-4754. http://dx.doi.org/10.1016/j.enpol.2011.06.052
|
[7]
|
Decarolis, J.F. and Keith, D.W. (2007) The Economics of Large-Scale Wind Power in a Carbon Constrained World. Energy Policy, 35, 3999-4008.
|
[8]
|
Liang, R.H. and Liao, J.H. (2007) A Fuzzy-Optimization Approach for Generation Scheduling with Wind and Solar Energy Systems. IEEE Transactions on Power Systems, 22, 1665-1674.
http://dx.doi.org/10.1109/TPWRS.2007.907527
|
[9]
|
Lee, T.Y. (2007) Optimal Spinning Reserve for a Wind-Thermal Power System Using EIPSO. IEEE Transactions on Power Systems, 22, 1612-1621. http://dx.doi.org/10.1109/TPWRS.2007.907519
|