Optimal Coordination of Aggregated Hydro-Storage with Residential Demand Response in Highly Renewable Generation Power System: The Case Study of Finland
Abstract
:1. Introduction
2. Modeling Methodology
2.1. Base-Load Generation Modeling
2.2. Hydro-Generation Modeling
2.3. Renewable Generation Modeling
2.4. Two-Capacity Building Model for HVAC Loads
2.5. Electric Vehicle
3. Mathematical Formulation
4. Case Study
4.1. Input Data
- Case I
- The hydro storage was optimized to accommodate for RESs variability without activating DR through residential flexible loads of detached houses. The charging of EV was also uncontrolled.
- Case II
- The hydro storage was optimized while coordinating with DR through direct control of HVAC, EWH, and EV charging loads. DR enrollment was assumed 100%.
4.2. Simulation Results
4.3. Sensitivity Analyses
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
Nomenclature
Indices and sets | |
t, T | Index and set of time slot |
t1m, t2m | Time step when EV m leaves and arrives home respectively on daily basis |
Difference between two time slots | |
n, N | Index and set of household |
m, M | Index and set of Electric Vehicle |
Parameters | |
Specific heat capacity of water (J/kg/K) | |
Indoor air heat capacity (J/°C) | |
Building fabric capacity (J/°C) | |
Distance travelled by EV m at time t (mile) | |
Total critical demand in the system at time t (Wh) | |
Heat conductance between external air and indoor air node points (W/°C) | |
Heat conductance between indoor air and ground node points (W/°C) | |
Heat conductance between indoor air and building mass node points (W/°C) | |
Heat conductance between external air and building mass node points (W/°C) | |
Heat conductance between HVAC air and indoor air node points (W/°C) | |
Hydro-inflows at time t (Wh) | |
Nuclear power production at time t (W) | |
CHP-city power production at time t (W) | |
CHP-industry power production at time t (W) | |
RES production at time t (W) | |
Maximum and minimum limits for hydro-power generation (W) | |
Rated maximum charging power of EV m (W) | |
Rated maximum power of EWH of household n (W) | |
Rated maximum charging power of thermal storage of household n (W) | |
Rated maximum power of HVAC unit of household n (W) | |
Maximum and minimum limits for SOC of aggregated hydro storage (Wh) | |
Maximum and minimum limits for SOC of thermal storage of household n(Wh) | |
Maximum and minimum limits for SOC of EV m (Wh) | |
Maximum and minimum limits for ambient temperature of household n (°C) | |
External temperature at time t (°C) | |
Temperature of the ventilation air of household n at time t(°C) | |
Temperature of inlet cold water in the hot water tank (°C) | |
Ground node temperature of household n at time t (°C) | |
Maximum and minimum limits for DHW temperature of household n (°C) | |
Volume of hot water tank of household n (L) | |
Volume of hot water used by household n at time t (L) | |
Charging efficiency of EV storage | |
Travel efficiency of EV (Wh/mile) | |
Total thermal charging demand of household n over the period T (Wh) | |
Total EWH demand of household n over the scheduling period T (Wh) | |
Total EV charging demand of EV m over the scheduling period T (Wh) | |
Variables | |
Total flexible demand at time t (W) | |
Total HVAC demand at time t (W) | |
Total EWH demand at time t (W) | |
Total EV charging demand at time t (W) | |
Hydro power production at time t (W) | |
EWH power of household n at time t (W) | |
Thermal storage charging power of household n at time t (W) | |
Charging power of EV m at time t (W) | |
HVAC power consumption of household n at time t (W) | |
SOC of EV m at time t (Wh) | |
SOC of aggregated hydro-storage at time t (Wh) | |
SOC of thermal storage of household n at time t (Wh) | |
Ambient temperature of household n at time t (°C) | |
DHW temperature of household n at time t (°C) | |
Building mass temperature of household n at time t (°C) | |
Thermal storage loss coefficient of household n at time t (Wh) |
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Case Study | Load Curtailment (TWh) | RES Curtailment (TWh) |
---|---|---|
Case I | 4.13 | 5.84 |
Case II | 0.98 | 1.65 |
Case Study | Curtailment | Mean Value (TWh) | Standard Deviation (TWh) | Lower 95% Confidence Bound (TWh) | Upper 95% Confidence Bound (TWh) |
---|---|---|---|---|---|
Case I | Load | 3.748 | 0.267 | 3.695 | 3.8 |
Generation | 5.168 | 0.277 | 5.113 | 5.222 | |
Case II | Load | 0.653 | 0.19 | 0.6078 | 0.698 |
Generation | 1.112 | 0.274 | 1.047 | 1.177 |
RES Penetration (%) | Aggregated Generation as % of Total Demand | Case I | Case II | ||
---|---|---|---|---|---|
Load Curtailment (TWh) | RES Curtailment (TWh) | Load Curtailment (TWh) | RES Curtailment (TWh) | ||
35 | 102.1 | 4.130 | 5.84 | 0.982 | 1.65 |
40 | 107.23 | 3.215 | 9.339 | 0.484 | 4.921 |
45 | 112.41 | 2.586 | 13.128 | 0.320 | 8.456 |
50 | 117.6 | 2.248 | 17.207 | 0.227 | 12.538 |
55 | 122.8 | 1.974 | 21.351 | 0.176 | 16.790 |
60 | 127.98 | 1.752 | 25.546 | 0.143 | 21.082 |
65 | 133.15 | 1.566 | 29.777 | 0.117 | 25.419 |
70 | 138.34 | 1.409 | 34.038 | 0.095 | 29.781 |
RES Penetration (%) | RES Curtailment (TWh) | Reduction in Curtailment (%) | CHP-city Electricity Production (TWh) | CHP-city Heating Production (TWh) | CHP-city Total Production (TWh) |
---|---|---|---|---|---|
35 | 0.174 | 89.45 | 11.628 | 37.51 | 49.14 |
40 | 0.67 | 86.38 | 10.970 | 35.39 | 46.36 |
45 | 1.424 | 83.16 | 10.313 | 33.27 | 43.58 |
50 | 2.510 | 79.98 | 9.603 | 30.98 | 40.58 |
55 | 3.885 | 76.86 | 8.923 | 28.785 | 37.71 |
60 | 5.617 | 73.35 | 8.318 | 26.832 | 35.15 |
65 | 7.445 | 70.71 | 7.724 | 24.916 | 32.64 |
70 | 9.644 | 67.62 | 7.212 | 23.265 | 30.48 |
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Bashir, A.A.; Lehtonen, M. Optimal Coordination of Aggregated Hydro-Storage with Residential Demand Response in Highly Renewable Generation Power System: The Case Study of Finland. Energies 2019, 12, 1037. https://doi.org/10.3390/en12061037
Bashir AA, Lehtonen M. Optimal Coordination of Aggregated Hydro-Storage with Residential Demand Response in Highly Renewable Generation Power System: The Case Study of Finland. Energies. 2019; 12(6):1037. https://doi.org/10.3390/en12061037
Chicago/Turabian StyleBashir, Arslan Ahmad, and Matti Lehtonen. 2019. "Optimal Coordination of Aggregated Hydro-Storage with Residential Demand Response in Highly Renewable Generation Power System: The Case Study of Finland" Energies 12, no. 6: 1037. https://doi.org/10.3390/en12061037