Optimal Configuration of Hybrid Energy Storage Capacity in a Grid-Connected Microgrid Considering Laddering Carbon Trading and Demand Response
Abstract
:1. Introduction
2. System Composition and Control
2.1. System Structure and Mathematical Models
2.2. Energy Scheduling Strategy
2.3. Demand Response
3. Optimal Configuration Model
3.1. Objective Function
3.1.1. Economy Model
3.1.2. Reliability Model
3.2. Constraints
3.2.1. Power Balance Constraints
3.2.2. Storage Operational Constraints
3.2.3. System Operational Constraints
3.3. Optimization Method of the Configuration Model
4. Case Study
4.1. Different Scenario Setting and Result Analysis
4.1.1. Impact of Different Carbon-Trading Calculation Models on Capacity Configuration
4.1.2. Impact of Demand Response on Capacity Configuration
4.2. Analysis of Load Characteristics with Demand Response
4.3. Sensitivity Analysis of Demand Response
4.4. Sensitivity Analysis of Other Parameters
5. Conclusions and Discussion
- There is a contradiction between the economy and reliability of power supply in the microgrid, and they cannot be optimized at the same time. When the overall profit rises, the reliability of the power supply decreases; when the overall profit decreases, the reliability of the power supply increases.
- When the model for calculating the cost of carbon trading changes from conventional to laddering, the penalties for carbon trading increase, and the overall profit of the microgrid decreases. The increased cost of power purchases by microgrids from the grid leads to a decrease in the amount of purchased power, which favors new energy generation for the grid, resulting in an increase in the capacity configuration of PV and BAT, as well as a rise in the reliability of the supply.
- Demand response makes the peak-to-valley difference in daily loads smaller and reduces the supply–demand power differential, thereby reducing the pressure on renewable energy generation and energy storage systems to store energy. This means that demand response allows microgrids to achieve greater economic efficiency with less configured capacity but with lower supply reliability.
- Different load shares in demand response can affect capacity configuration and system operation results. As the share of shiftable loads increases, the PV configuration capacity decreases, but the BAT configuration capacity increases; as the share of the served or substituted loads increases, the configuration capacity of both PV and BAT decreases. Both the increase in the share of shiftable and the served or substituted loads can contribute to the economics of microgrids but can lead to a decrease in the reliability of the supply.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Equipment | Investment Cost | O&M Cost | Lifespan/Year |
---|---|---|---|
PV | 6195 RMB/kW | 0.15 RMB/kW | 20 |
BAT | 1070 RMB/kW h | 5 RMB/kW h | 10 |
EL | 7615 RMB/kW | 120 RMB/kW | 10 |
HST | 2600 RMB/kg | 19 RMB/kg | 20 |
Time Period | Purchasing Price | Selling Price |
---|---|---|
0:00–8:00 | 0.37 RMB/kW h | 0.28 RMB/kW h |
12:00–17:00, 21:00–24:00 | 0.69 RMB/kW h | 0.53 RMB/kW h |
8:00–12:00, 17:00–21:00 | 0.87 RMB/kW h | 0.72 RMB/kW h |
Scenarios | PV/kW | BAT/kW h | EL/kW | HST/kg | Profit/104 RMB | LSR/% |
---|---|---|---|---|---|---|
I | 2762 | 6271 | 357 | 237 | 29.13 | 0.98 |
II | 2810 | 6448 | 379 | 181 | 25.75 | 0.91 |
III | 2693 | 6154 | 353 | 114 | 31.65 | 0.99 |
IV | 2731 | 6382 | 357 | 153 | 27.88 | 0.92 |
Scenarios | RE/104 RMB | RH2/104 RMB | CInv/104 RMB | CRun/104 RMB | CCO2/104 RMB | Load Shortage /104 kW h |
---|---|---|---|---|---|---|
I | 260.64 | 68.81 | 223.92 | 84.47 | 1.13 | 3.37 |
II | 261.33 | 70.41 | 228.22 | 86.05 | 1.88 | 3.11 |
III | 255.90 | 67.27 | 216.57 | 82.22 | 1.20 | 3.44 |
IV | 256.39 | 68.58 | 221.65 | 83.51 | 1.97 | 3.19 |
Parameter | Base Value | Changed to | Change in Profit (%) | Change in LSR (%) |
---|---|---|---|---|
Hydrogen price | 55 RMB/kg | 44 RMB/kg (−20%) | −18.80 | −5.17 |
66 RMB/kg (+20%) | 16.78 | 5.30 | ||
Carbon trading price (regular) | 247.33 RMB/t | 197.86 RMB/t (−20%) | 12.02 | 6.69 |
296.80 RMB/t (+20%) | −15.23 | −7.43 | ||
Growth rate of carbon trading prices | 25% | 20% (−20%) | 10.16 | 3.39 |
30% (+20%) | −9.82 | −4.18 |
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Xu, Z.; Chen, F.; Yang, X.; Lu, Q. Optimal Configuration of Hybrid Energy Storage Capacity in a Grid-Connected Microgrid Considering Laddering Carbon Trading and Demand Response. Energies 2024, 17, 139. https://doi.org/10.3390/en17010139
Xu Z, Chen F, Yang X, Lu Q. Optimal Configuration of Hybrid Energy Storage Capacity in a Grid-Connected Microgrid Considering Laddering Carbon Trading and Demand Response. Energies. 2024; 17(1):139. https://doi.org/10.3390/en17010139
Chicago/Turabian StyleXu, Zhanpeng, Fuxin Chen, Xuefan Yang, and Qinfen Lu. 2024. "Optimal Configuration of Hybrid Energy Storage Capacity in a Grid-Connected Microgrid Considering Laddering Carbon Trading and Demand Response" Energies 17, no. 1: 139. https://doi.org/10.3390/en17010139
APA StyleXu, Z., Chen, F., Yang, X., & Lu, Q. (2024). Optimal Configuration of Hybrid Energy Storage Capacity in a Grid-Connected Microgrid Considering Laddering Carbon Trading and Demand Response. Energies, 17(1), 139. https://doi.org/10.3390/en17010139