Improving the Power Outage Resilience of Buildings with Solar PV through the Use of Battery Systems and EV Energy Storage
<p>Illustrations for the example reference home: location in California zone climate 9 (<b>left</b>); home energy management, PV, battery, EV, and appliances diagram including major energy users HVAC system and EWH (<b>center</b>); and new power flow during a year (<b>right</b>). The negative power flow during daytime is due to surplus solar PV generation. The very high power draw marked with red dots and occurring mostly in the evening and at night is due to the EWH.</p> "> Figure 2
<p>Example of a residential power and energy management system, based on the concept described in a US patent [<a href="#B36-energies-14-05749" class="html-bibr">36</a>]. Such a multifunctional system can ensure V2H operation, providing support during grid power outages and increased resilience.</p> "> Figure 3
<p>Systematic procedure for the evaluation of building resilience. Simulation is performed for each time step, corresponding to instances for which power outage occurs. The self-sustainment duration is calculated for each instance.</p> "> Figure 4
<p>An example of the daily self-sustain case for the reference house when the power outage occurs at (<b>a</b>) midnight and (<b>b</b>) 3 p.m. The BESS covers the residential load in the morning and was charged by surplus solar PV generation throughout the day. As PV power rapidly declined and no longer met the residential load, the BESS discharged until falling to the minimum SOC of 20%. The reference house tends to self-sustain longer when the power outage occurs in the early morning because the BESS could be charged by PV generation during the daytime hours.</p> "> Figure 5
<p>Self-sustained operation duration of the reference house for power outages occurring at different times. All 105,120 instances of varying days and times for power outages were calculated throughout the year. The self-sustained operation duration is longer if the power outage occurs in the morning because the BESS could be charged during the day with surplus solar PV generation.</p> "> Figure 6
<p>The distribution of residence self-sustained operation duration for all 105,120 instances. All instances were binned into duration categories with a time interval of 1-h.</p> "> Figure 7
<p>The cumulative probability curve for self-sustained operation duration of the reference house. Regardless of when a power outage occurs, the reference house is highly likely to completely self-sustain at 100% load for up to 3 h. If the power outage occurs at any point in time there is a 50% likelihood the residence will self-sustain for up to 10 h.</p> "> Figure 8
<p>An example of aself-sustained case with residential load, except for the electric water heater, curtailed to 50% of the reference value. The self-sustainment duration was 21 h, 4 h longer than the reference house because of the lower electricity usage.</p> "> Figure 9
<p>Self-sustained operation duration of the house with 50% of the reference residential load presented as a (<b>a</b>) heat map and (<b>b</b>) distribution. The likelihood of the house self-sustaining for more than 24 h is approximately 31%.</p> "> Figure 10
<p>An example of self-sustained operation for a house with an increased BESS rating of 27 kWh. In this case, the self-sustained operation of approximately 22 h was 5 h longer than the reference case.</p> "> Figure 11
<p>Self-sustained operation duration of the house with a BESS rating of 27 kWh is presentedas a (<b>a</b>) heatmap, and (<b>b</b>) distribution. The probability that the house can self-sustain for more than 24 h is approximately 72%.</p> "> Figure 12
<p>Results of a case study examining varying combinations of BESS capacities and home load percentages in self-sustainment duration of 24 h or greater.</p> "> Figure 13
<p>An example of a self-sustained case for the reference house with EV contributing to (<b>a</b>) supply the residential load only, (<b>b</b>) supply the residential load and charge the BESS. Assuming that the EV arrived home every day at 6 p.m. with a SOC of 90% and left home at 6 a.m. the next day.</p> "> Figure 14
<p>Case study for combinations of different load percentage and BESS capacities with an EV participating to (<b>a</b>) supply the residential load only, (<b>b</b>) supply the residential load and charge the BESS.</p> "> Figure 15
<p>An example self-sustain case for the house with the EV staying at home. Shown is the case with an EV battery rated at 20 kWh. The capacity of the energy storage system (ESS) was expanded dramatically by incorporating the EV battery.</p> "> Figure 16
<p>The self-sustained operation duration of the house with an EV at home for the duration of 72 h presentedas a (<b>a</b>) heatmap, and (<b>b</b>) distribution. The EV battery was rated 20 kWh in this case. The probability that house can self-sustain for at least 72 h is approximately 10%.</p> "> Figure 17
<p>The cumulative distribution for the self-sustained operation duration of the house withan EV at home rated for 20 kWh. Building resilience was analyzed over a duration of 72 h.</p> "> Figure 18
<p>Building resilience heatmap for the house with an EV staying at homeand providing additional energy storage. The effect of different EV capacities on building resilience was evaluated.</p> ">
Abstract
:1. Introduction
- Quantification of building resilience considering all possible power outage occurrence times;
- Analysis of building resilience for different factors including user behavior, the impact of renewable energy generation, and the energy capacity of the residential ESS;
- Exploration of the possibility of EV battery incorporation into the residential ESS;
- Evaluation of the impact of EV battery capacity on building resilience.
2. Energy Model for the Reference House
3. Method for Calculating the Self-Sustainment Duration for a Reference House
4. Study for Different Home Load and BESS Energy Capacities
5. EV Participation
6. Discussion
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Acknowledgments
Conflicts of Interest
References
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Parameters | Value |
---|---|
Conditioned area | 223 m (2401 ft) |
House type | 4-bedroom, 3.5-bathroom |
Location | Burbank, CA, Zone 9 |
PV rating/annual generation | 7.2 kW/11,316 kWh |
Annual electricity usage w/o EWH | 13,628 kWh |
Annual electricity usage of EWH | 4233 kWh |
EWH rated electric power | 5 kW |
BESS energy capacity/maximum power | 11 kWh/5 kW |
Initial BESS SOC | 100% |
Minimum BESS SOC | 20% |
EV battery energy capacity/maximum power | 90 kWh/10 kW |
EV battery SOC when EV arrives home | 90% |
Minimum EV battery SOC | 20% |
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Gong, H.; Ionel, D.M. Improving the Power Outage Resilience of Buildings with Solar PV through the Use of Battery Systems and EV Energy Storage. Energies 2021, 14, 5749. https://doi.org/10.3390/en14185749
Gong H, Ionel DM. Improving the Power Outage Resilience of Buildings with Solar PV through the Use of Battery Systems and EV Energy Storage. Energies. 2021; 14(18):5749. https://doi.org/10.3390/en14185749
Chicago/Turabian StyleGong, Huangjie, and Dan M. Ionel. 2021. "Improving the Power Outage Resilience of Buildings with Solar PV through the Use of Battery Systems and EV Energy Storage" Energies 14, no. 18: 5749. https://doi.org/10.3390/en14185749