Evaluating the Effect of Distributed Generation on Power Supply Capacity in Active Distribution System Based on Sensitivity Analysis
Abstract
:1. Introduction
2. SA of PSC Evaluation Indexes to DG
2.1. Selection of PSC Evaluation Indexes for SA
2.2. Deduction of Sensitivity Formulas of PSC Evaluation Indexes to DG
2.2.1. Sensitivity of the Expectation of PSC to DG output
2.2.2. Sensitivity of Other Evaluation Indexes of PSC to DG output
2.2.3. Sensitivity of Evaluation Indexes of PSC to DG type
3. PSC Evaluation Model Based on the SA of DG
3.1. Calculation Model of PSC
3.2. The Non-Parametric Kernel Density Probability Model of DG
3.3. PSC Reckoning Based on SA
4. Steps of PSC Evaluation Based on SA
- (1)
- Base on the demands of PSC evaluation from various aspects, multiple PSC evaluation indexes are selected according to the consideration of numerical size, adequacy, and contribution degree of DG.
- (2)
- Based on the generalized sensitivity formulas, the sensitivity formulas of position, output and type of accessed DG are defined and deduced.
- (3)
- Taking constraint conditions into consideration, including the active and reactive power flow, branch capacity and node voltage, the basic model of PSC evaluation is established.
- (4)
- On the basis of the non-parametric kernel density estimation theory, the uncertainty of DG output is simulated and the probability model is established. The output samples are extracted from the model by Latin hyper-cube sampling technique to form multiple scenarios with different probabilities.
- (5)
- Due to the traditional PSC evaluation methods, the PSC values are calculated when the type and capacity of the connected DG differs.
- (6)
- Calculate the sensitivity value corresponding to the PSC and its evaluation indexes.
- (7)
- Based on the SA results of step 6, the PSC evaluation results in ADS can be reckoned when the accessed DG are of the same type.
- (8)
- Based on the SA results of step 6, the PSC evaluation results in ADS can be reckoned and compared when the types of the accessed DG are different.
- (9)
- Comparing with the PSC evaluation results in step 5, and the PSC reckoning results based on SA in steps 7 and 8, the feasibility and effectiveness of the PSC evaluation based upon the SA can be verified.
5. Case Study
5.1. General Situation of the System
5.2. General Situation of the Distribution System
5.3. PSC Evaluation Based on SA
5.3.1. Sensitivity Calculation of PSC Evaluation
5.3.2. Reckoning of the PSC Evaluation Indexes Based on SA
6. Conclusions
- (1)
- On the foundation of the generalized sensitivity, the sensitivity formulas applicable to PSC evaluation are deduced and calculated, the analysis results of which are capable of providing the sensitivity of PSC evaluation indexes to the type, output and capacity of DG at specific node directly and effectively.
- (2)
- In view of the sensitivity results obtained above, the fluctuation of PSC and its evaluation indexes are supposed to be reckoned at specific node when the type and capacity of added DG varied, offering vigorous evidence for the PSC evaluation of multiple perspectives.
- (3)
- Considering the connection of various types of DG at the same node, the optimal DG proportion of type and capacity can be presented, as well as its corresponding PSC numerical result, which contributes to lowering the investigation costs and optimizing the PSC.
- (4)
- The application of the PSC evaluation based on SA is limited by the DG, the capacity of which is supposed to be within a certain small boundary. Furthermore, the calculation precision is in inverse proportion to the distance between reference point and reckoning point. On one hand, the PSC evaluation based on SA is supposed to meet the demand of the operation and scheduling of ADS basically; on the other hand, starting from the point of view of upgrading and planning, it may be necessary to build up a new sensitivity criteria to provide guidance for the component renewal and the further expansion of the power grid.
Acknowledgments
Author Contributions
Conflicts of Interest
Abbreviations
PSC | Power supply capacity |
ADS | Active distribution system |
DG | Distributed generation |
SA | Sensitivity analysis |
PV | Photovoltaic |
WG | Wind generation |
EPSC | Expectation of PSC |
DAPSC | Dissatisfied Amount of PSC |
CRDTE | Contribution Rate of DG to Expectation of PSC |
CRDTDA | Contribution Rate of DG to Dissatisfied Amount of PSC |
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Number | PV | WG | ||
---|---|---|---|---|
Sampling Power/MW | Probability | Sampling Power/MW | Probability | |
1 | 0.0385 | 0.0905 | 0.0550 | 0.0682 |
2 | 0.0955 | 0.1377 | 0.1554 | 0.1393 |
3 | 0.1568 | 0.1271 | 0.1997 | 0.1428 |
4 | 0.2922 | 0.0890 | 0.2486 | 0.1378 |
5 | 0.3924 | 0.0828 | 0.3039 | 0.1285 |
6 | 0.5458 | 0.0946 | 0.3242 | 0.1261 |
7 | 0.6238 | 0.1051 | 0.4320 | 0.0837 |
8 | 0.7073 | 0.1072 | 0.4412 | 0.0799 |
9 | 0.7888 | 0.0791 | 0.5830 | 0.0367 |
10 | 0.8525 | 0.0869 | 0.7700 | 0.0570 |
Calculation Results | PSC Evaluation Indexes | |||
---|---|---|---|---|
EPSC | DAPSC | CRDTE | CRDTDA | |
PSC evaluation indexes | 42.5819/MW | 17.4181/MW | 0/MW | 0/MW |
Sensitivity of DG output | 1.5384 | −1.5384 | 0.03613 | 0.08832 |
Sensitivity of PV capacity | 0.6532 | −0.6532 | 0.01534 | 0.03750 |
Sensitivity of WG capacity | 0.4689 | −0.4689 | 0.01101 | 0.02692 |
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Gao, Y.; Yang, W.; Zhu, J.; Ren, J.; Li, P. Evaluating the Effect of Distributed Generation on Power Supply Capacity in Active Distribution System Based on Sensitivity Analysis. Energies 2017, 10, 1473. https://doi.org/10.3390/en10101473
Gao Y, Yang W, Zhu J, Ren J, Li P. Evaluating the Effect of Distributed Generation on Power Supply Capacity in Active Distribution System Based on Sensitivity Analysis. Energies. 2017; 10(10):1473. https://doi.org/10.3390/en10101473
Chicago/Turabian StyleGao, Yajing, Wenhai Yang, Jing Zhu, Jiafeng Ren, and Peng Li. 2017. "Evaluating the Effect of Distributed Generation on Power Supply Capacity in Active Distribution System Based on Sensitivity Analysis" Energies 10, no. 10: 1473. https://doi.org/10.3390/en10101473