Dr. Liuchen Chang Dr. Haibo Xu

Transcription

1 Economic Analysis and Optimal Design on Microgrids with SS-PVs for Industrial Applications Dr. Liuchen Chang Dr. Haibo Xu EAST Power Hefei University of Technology 1/ Tianjin Symposium on Microgrids, Nov , 214

2 1. Introduction Outline 2. Structure of microgrid with SS-PV PVs 3. Evaluation indices for the microgrid with SS-PVs 4. Optimal design of PV microgrid for industrial applications 5. Case studies 6. Conclusions 2/ Tianjin Symposium on Microgrids, Nov , 214

3 1. Introduction 1.1 Background MW $/Wp Time global cumulative installed PV capacity global average PV module price The developing trend of PV systems is in two directions : 1. Large-scale grid-connected PV systems(ls-pv) 2. Small-scale PV systems(ss-pv) integrated with other distributed generators in microgrids Fig.1 Global PV cumulative installed capacity / Tianjin Symposium on Microgrids, Nov , 214

4 1.2 Development of SS-PVs 1. Used in remote communities 2. Used as distributed generators, including building integrated photovoltaic systems (BIPV) 3. Based on the microgrid concept 1. Facilitating the integration of renewable energy systems 2. Increasing the reliability and power quality 1. Low economy efficiency in general 4/ Tianjin Symposium on Microgrids, Nov , 214

5 1.3 Some research on microgrids with PVs On the economic evaluation Less focus on the economic evaluation of the emission reduction benefits, especially for the non-back-feeding systems. On optimal design Mostly for the island system, but rarely for grid-connected system 5/ Tianjin Symposium on Microgrids, Nov , 214

6 2. Structure of Microgrid with SS-PVs 2.1 2MW industrial photovoltaic microgrid installed at EAST Total installed capacity:2mw (5KW completed) 6/ Tianjin Symposium on Microgrids, Nov , 214

7 Configuration of Microgrids with SS-PVs installed at EAST 7/ Tianjin Symposium on Microgrids, Nov , 214

8 Normal PV output power characteristic in coastal areas: fluctuate frequently and drastically 8/ Tianjin Symposium on Microgrids, Nov , 214

9 Load The PV provides almost 5% total power consumption at EAST PV output power Power from utility The profiles of the utility, PV and load 9/ Tianjin Symposium on Microgrids, Nov , 214

10 2.2 Operation strategies of the microgrid with SS-PVs kw : 3: 6: 9: 12: 15: 18: 21: Time Pload Insolation Fig.3 Typical daily load curve of the factory kw/m In order to reduce the cost of electricty, an effective way is needed to minimize the difference of the electricity demand between the peak and valley in different periods every day. Calculating the evaluation indices of the system Economic analysis based on an optimized design model Energy management strategy for the PV system Sensitivity analysis of the impact of different installation sites on the system 1/ Tianjin Symposium on Microgrids, Nov , 214

11 3. Evaluation indices for the microgrid with SS-PVs 3.1 Levelized Energy Cost (LEC) C LEC N r(1 r) C C C C C N ( 1 r) 1 E tot rep om buy ERB C tot C rep C om C buy C ERB E r N the total initial investment of the system the annual replacement cost the operation and maintenance cost the annual cost of electricity purchase the benefits of emission reduction the annual energy output of the system the interest rate the life circle of the system 11/ Tianjin Symposium on Microgrids, Nov , 214

12 3.2 Emission Reduction Benefit (ERB) 4 C ( E * Emi * Env ) ERB PV i i i 1 E PV Emi i Env i the annual power output of PV in the microgrid the emission of four different pollutants in producing 1 kwh of electricity the corresponding environment cost 3.3 Payback Period (PBP) PBP C tot p E C C Q Q= rep om Q annual cash flow of the system p E the electricity price the annual energy output of the system 12/ Tianjin Symposium on Microgrids, Nov , 214

13 4. Optimal design of PV microgrid for industry 4.1 Energy Scheduling Strategy 1) If it is allowable to sell the electricity to the utility: (a) During the peak period If the solar energy is sufficient If the solar energy is insufficient 13/ Tianjin Symposium on Microgrids, Nov , 214

14 (b) During the flat period (c) During the valley period 2) If it is not allowable to sell the electricity to the utility If the solar energy is sufficient If the solar energy is insufficient 14/ Tianjin Symposium on Microgrids, Nov , 214

15 4.2 Optimal design model 1) The objective function N r(1 r) fmin C C C C C N ( 1 r) 1 C tot r N C rep C buy C ERB tot rep om buy ERB The total initial investment of the system The bank interest rate The life circle of the system The replacement cost The electricity purchasing cost The benefits of emission reduction 2) Constraints PPV PBat Pbuy Pload PPV PMPP I I I d,max Bat c,max SOCmin SOC SOCmax during peak and vallay period SOClow SOC SOCmax during flat period P PV P Bat P buy P load I Bat SOC SOC min SOC low η Desired the output power of photovoltaic array charge or discharge power of the battery the purchased electricity of the system the load power charge or discharge current of the battery the state of the charge of the battery the minimum SOC of the battery a set value which avoids that the battery is over discharged during the flat period the self-sufficiency ratio during the peak period 15/ Tianjin Symposium on Microgrids, Nov , 214

16 Fig.4 The studied system at EAST, China 5. Case studies case Table 2. Optimization result of the 5kW PV microgrid for industries Units Capacity Ctot($) Crep($/year) PV 5kW 5 Capacity of Batteries for the non-back feeding system Table1.Time-of-use electricity price policy Load period peak period valley period flat period Hour(h) 115kWh Electricity price ($/kwh) 9:-12:, 19:-22:.13 :-8:.3 8:-9:,12:-19:, 22:-24:.8 Capacity of Batteries for the back-feeding system 143kWh / Tianjin Symposium on Microgrids, Nov , 214

17 5.1 The simulation results in four scenarios 1) Non-Back-Feeding System Without Batteries kw : 3: 6: 9: 12: 15: 18: 21: Time Ppv Ppcc Pload Fig.5 Output power of the units kw ) Non-Back-Feeding System With Batteries : -2 3: 6: 9: 12: 15: 18: 21: Time Ppv Pbat Ppcc Pload Fig.6 Output power of the units SOC : 3: 6: 9: 12: 15: 18: 21: Time SOC Voltage Fig.7 SOC and voltage of the battery V / Tianjin Symposium on Microgrids, Nov , 214

18 3) Back-Feeding System Without Batteries kw : -2 3: 6: 9: 12: 15: 18: 21: -4 Time Ppv Ppcc Pload Fig.8 Output power of the units 4) Back-Feeding System With Batteries kw : -2 3: 6: 9: 12: 15: 18: 21: -4 Time Ppvm Pbat Pbuy Pload Fig.9 SOC and voltage of the battery SOC : 3: 6: 9: 12: 15: 18: 21: Time SOC Voltage Fig.1 Output power of the units 18/ Tianjin Symposium on Microgrids, Nov , 214 V

19 5.2 Three evaluation indexes 1) LEC kg $/kwh )ERB Scene Scenario 1 1 Scene Scenario 2 2 Scene Scenario 3 3 Scenario 4 Scene Years SO2 NOx CO CO2 Reduction of pollutants Fig.12 Reduction of pollutant emission of the system before and after the introduction of the battery Fig.11 LEC of the system at different scenarios Scenario Scene 11 Scenario 2 Scene 2 Scenario 3 Scene 3 Scenario 4 Scene 4 3)PBP 19/ Tianjin Symposium on Microgrids, Nov , scenario 1 scenario 2 scenario 3 scenario 4 Fig.13 PBP of the system at different scenarios

20 5.3 Sensitivity analysis Table 3. Summary of the sensitivity analysis Parameter Base value Changed to change in LEC (%) change in PBP (%) Initial investment cost 5 $ Operation and maintenance cost Battery cost.8 $/kw $/kwh 475$(-5%) $(-1%) $/kW(-1%) $/kW(+1%) (-5%) (-1%) Table II. The summary of the sensitivity analysis Cycle efficiency 8% FiT Allowable level of reverse power (% of the installed system capacity).19 $/kwh 2% 7% % (+1%) (+2%) % % / Tianjin Symposium on Microgrids, Nov , 214

21 5.4 Calculation results for microgrids installed at different sites Table 4. Region classification by distribution of solar energy resource in china Class of Regions Total annual insolation (MJ/m 2 ) Daily solar insolation (kwh/m 2 ) Regions First level 668 ~ ~6.4 Ningxia, Gansu, northern Xinjiang, western Tibet Second level 585 ~ ~5.1 Hebei, Shanxi, northern, central Gansu Third level 5 ~ ~4.5 Guangdong, Shandong, Liaoning, Jiangsu, northern Anhui Forth level 42 ~5 3.2 ~3.8 Hunan, Hubei, Zhejiang, southern Anhui Fifth level 335 ~ ~3.2 Sichuan, Guizhou Non-Back-Feeding system with batteries Back-Feeding system with batteries Non-Back-Feeding system with batteries Back-Feeding system with batteries Fig.14 The LEC of microgrids installed at different sites Fig.15 The PBP of microgrids installed at different sites 21/ Tianjin Symposium on Microgrids, Nov , 214

22 6. Conclusion The optimized back-feeding microgrid with SS-PVs and batteries can bring the most economic and emission reduction benefits to the customers and society. The sensitivity analysis of the impact of various parameters and different installed sites for the microgrid system has also been performed in this study. The economic analysis and optimal design of the PV microgrid for industrial applications provided a reference for the application of similar projects. 22/ Tianjin Symposium on Microgrids, Nov , 214