Comparative and Cost Analysis of a Novel Predictive Power Ramp Rate Control Method: A Case Study in a PV Power Plant in Puerto Rico
Abstract
:1. Introduction
2. Overview of the Power Ramp-Rate Control Methods
2.1. Ramp Saturation (RS) Method
2.2. Simple Moving Average (SMA) Method
2.3. Exponential Moving Average (EMA) Method
2.4. First Order Low-Pass Filter (FOLPF) Method
2.5. Second Order Low-Pass Filter (SOLPF) Method
2.6. Enhanced Linear Exponential Smoothing (ELES)
3. Proposed Predictive Dynamic Smoothing PRRC Method
4. Methodology for the Levelized Cost of Storage Estimation
4.1. Battery Degradation Estimation for PRRC
4.2. Levelized Cost of Storage (LCOS) Estimation
4.3. Ramp Violations
5. Coto Laurel Case Study
5.1. General Description of Coto Laurel Solar Power Plant
5.2. Environmental Characteristics of Coto Laurel Solar Power Plant
5.3. Proposed Model
5.4. Model Validation
6. Simulation Results
6.1. First Stage: One Day Evaluation
6.1.1. Ramp Saturation Method
6.1.2. Simple Moving Average (SMA) Method
6.1.3. Exponential Moving Average (EMA) Method
6.1.4. First Order Low-Pass Filter (FOLPF) Method
6.1.5. Second Order Low-Pass Filter (SOLPF) Method
6.1.6. Enhanced Linear Exponential Smoothing (ELES) Method
6.1.7. Proposed Predictive Dynamic Smoothing (PDS)
6.2. Economic Analysis through One Year
- RS with a PRRmax of 10%.
- SMA with a window size W = 10.
- EMA with a window size W = 30 and a smoothing factor α = 0.123.
- FOLPF with a sampling period Ts = 60 s and a Tf = 500 s.
- SOLPF with a sampling period of Ts = 60 s, a damping ratio ζ = 0.707, and a natural frequency ωn = 1/25 rad/s.
- ELES with a smoothing factor α = 0.06.
- Proposed PDS with a window size W = 5 and a disturbance coefficient µ = 10%. This coefficient was selected since it represented errors in estimations of about 1 MW, which is reasonable according to the literature presented in Section 3.
6.2.1. Battery Degradation
6.2.2. LCOS
6.2.3. Violations
7. Discussion
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Battery | Output | DC Power [MW] | Inverter Capacity [kWac] | Feeder | Transf. Capacity [kVA] | Primary-Delta [kV] | Secondary-Yn [V] |
---|---|---|---|---|---|---|---|
1 | 1 | 1 | 880 | 3 | 1800 | 13.2 | 360 |
2 | 880 | ||||||
2 | 1 | 1 | 880 | 3 | 1800 | 13.2 | 360 |
2 | 880 | ||||||
3 | 1 | 1 | 880 | 3 | 1800 | 13.2 | 360 |
2 | 880 |
Group | PV Capacity [W] | PV Quantity | DC Power [kW] | PowerLimit [kW] | Feeder ID | Transf. Capacity [kVA] | Primary-Delta [kV] | Secondary-Yn [V] |
---|---|---|---|---|---|---|---|---|
A1 | 235 | 3408 | 800.88 | 575 | 1 | 1800 | 13.2 | 360 |
A2 | 235 | 3312 | 778.32 | 555 | 1 | |||
B1 | 235 | 3480 | 817.8 | 585 | 1 | 1800 | 13.2 | 360 |
B2 | 235 | 3240 | 761.4 | 545 | 1 | |||
D | 275 | 3744 | 1029.6 | 695 | 2 | 1800 | 13.2 | 360 |
G | 275 | 3744 | 1029.6 | 695 | 2 | |||
E | 275 | 3720 | 1023 | 705 | 2 | 1800 | 13.2 | 360 |
H | 275 | 3744 | 1029.6 | 705 | 2 | |||
D-G | 275 | 3864 | 1062.6 | 710 | 2 | 1800 | 13.2 | 360 |
E-H | 275 | 3864 | 1062.6 | 735 | 2 | |||
F | 260 | 3720 | 967.2 | 695 | 1 | 800 | 13.2 | 360 |
J | 260 | 3744 | 973.44 | 695 | 1 | 1800 | 13.2 | 360 |
F-J | 260 | 3864 | 1004.64 | 710 | 1 | |||
K | 280 | 3984 | 1115.52 | 790 | 2 | 1800 | 13.2 | 360 |
L | 280 | 3984 | 1115.52 | 790 | 2 | |||
= | 55,416 | 14,571.72 | 10,185 |
Measurement | PRRmax = 8% | PRRmax = 10% | PRRmax = 12% |
---|---|---|---|
(%) | 0.0023 | 0.0021 | 0.0014 |
0.2349 | 0.2097 | 0.1405 | |
Violations (mins) | 0 | 0 | 161 |
SOC (end of the day)-SOC(ref) | −4.5307 | −9.0051 | −3.5554 |
22.7312 | 31.9882 | 41.9434 |
Measurement | W = 5 | W = 10 | W = 20 |
---|---|---|---|
(%) | 0.0019 | 0.0052 | 0.0107 |
0.1864 | 0.5201 | 1.0685 | |
Violations (mins) | 64 | 0 | 0 |
SOC (end of the day) -SOC(ref) | −13.6058 | −27.1991 | −24.6659 |
25.3416 | 7.7530 | 2.6601 |
Measurement | |||
---|---|---|---|
(%) | 0.0048 | 0.0053 | 0.0049 |
0.4823 | 0.5315 | 0.4927 | |
Violations (mins) | 13 | 0 | 1 |
SOC (end of the day) -SOC(ref) | 28.215 | 15.3441 | 6.2242 |
25.9067 | 5.3813 | 6.1433 |
Measurement | |||
---|---|---|---|
(%) | 0.0071 | 0.0081 | 0.0085 |
0.7117 | 0.8127 | 0.8485 | |
Violations (mins) | 1 | 0 | 0 |
SOC (end of the day) -SOC(ref) | −21.6426 | −22.8112 | −21.7886 |
6.1622 | 5.1486 | 4.3769 |
Measurement | |||
---|---|---|---|
(%) | 0.0063 | 0.0101 | 0.0136 |
0.6286 | 1.0117 | 1.3634 | |
Violations (mins) | 18 | 0 | 0 |
SOC (end of the day) -SOC(ref) | −29.9978 | −34.8233 | −32.3034 |
14.4757 | 4.6293 | 2.4287 |
Measurement | |||
---|---|---|---|
(%) | 0.0072 | 0.0057 | 0.0046 |
0.7206 | 0.5709 | 0.4599 | |
Violations (mins) | 0 | 0 | 1 |
SOC (end of the day) -SOC(ref) | −31.949 | −22.593 | −20.975 |
3.9163 | 5.3242 | 6.8792 |
Measurement | |||
---|---|---|---|
(%) | 0.0016 | 0.0020 | 0.0026 |
0.1591 | 0.1990 | 0.2621 | |
Violations (mins) | 0 | 0 | 0 |
SOC (end of the day) -SOC(ref) | −1.5788 | 14.4696 | 29.9847 |
14.2955 | 14.1632 | 15.9081 |
Measurement | |||
---|---|---|---|
(%) | 0.0043 | 0.0041 | 0.0042 |
0.4340 | 0.4115 | 0.4245 | |
Violations (mins) | 0 | 0 | 0 |
SOC (end of the day) -SOC(ref) | −18.594 | 3.8675 | −10.287 |
5.1573 | 4.7417 | 6.1070 |
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Patarroyo-Montenegro, J.F.; Vasquez-Plaza, J.D.; Rodriguez-Martinez, O.F.; Garcia, Y.V.; Andrade, F. Comparative and Cost Analysis of a Novel Predictive Power Ramp Rate Control Method: A Case Study in a PV Power Plant in Puerto Rico. Appl. Sci. 2021, 11, 5766. https://doi.org/10.3390/app11135766
Patarroyo-Montenegro JF, Vasquez-Plaza JD, Rodriguez-Martinez OF, Garcia YV, Andrade F. Comparative and Cost Analysis of a Novel Predictive Power Ramp Rate Control Method: A Case Study in a PV Power Plant in Puerto Rico. Applied Sciences. 2021; 11(13):5766. https://doi.org/10.3390/app11135766
Chicago/Turabian StylePatarroyo-Montenegro, Juan F., Jesus D. Vasquez-Plaza, Omar F. Rodriguez-Martinez, Yuly V. Garcia, and Fabio Andrade. 2021. "Comparative and Cost Analysis of a Novel Predictive Power Ramp Rate Control Method: A Case Study in a PV Power Plant in Puerto Rico" Applied Sciences 11, no. 13: 5766. https://doi.org/10.3390/app11135766