Motivation
The state of California aims to achieve Zero Net Energy (ZNE) in new buildings with photovoltaic (PV) installation, for residential buildings by 2020, Government buildings by 2025, and commercial buildings by 2030. ZNE in residential homes is accomplished by increasing the energy efficiency of appliances and offsetting the remaining energy use with PV energy generation. Consequently, high PV energy penetration in geographically concentrated areas will result in duck curves with substantially lower energy usage during morning times and increase backflow of energy significantly. Furthermore, the evening load demands, caused by ZNE homes, will lead to steep energy usage ramps during evenings. In addition, the appliances in these ZNE homes will be predominantly electric, as gas driven loads are electrified to utilize PV energy generation, which further stress the distribution systems during peak times. ZNE homes are often equipped with battery energy storage systems to reduce the peaks and valleys in their load profiles.
In the state of Arizona, utility grid planners are not yet familiar with the impacts of ZNE communities on the local distribution transformers, load blocks, and feeders. No studies are available if Arizona is to follow California’s bold plan of ZNE homes. In addition, it has not yet been studied how optimized energy storage could benefit both ZNE home consumers and utility operators.
Our work focuses on modeling, analysis, and optimization of the interaction and integration between ZNE buildings and distribution grids in Arizona. Firstly, we present the expected load profiles of ZNE homes during different time frames (hourly, weekly, monthly, yearly, and seasonally) and their impact on distribution grids in Arizona, especially in the Phoenix metro area. In this study, the load profiles of ZNE homes are characterized based on current customer load profiles of the distribution system. Mathematical and simulation models are developed to analyze the negative effects of ZNE homes with all electrical loads. Our study focuses on the distribution transformers and feeders overloading with respect to different photovoltaic generation capacities. Secondly, this research will develop optimization algorithms for sizing and operating energy storage systems to prevent distribution transformers from being overloaded during the backflow of energy in mornings and peak loads in evenings. The developed optimization algorithms will help reduce operational costs of ZNE homes by shifting energy consumption from high to low price periods. In order to support the analysis in this research, simulation studies are conducted with proprietary software consisting of a substation and 4 residential feeders. The simulation results will be presented during different time frames (hourly, weekly, monthly, yearly, and seasonally) with various scenarios, such as different combinations of ZNE homes and normal homes in the community, and ZNE home-level and community-level energy storage.
In order to understand the effects of a zero net energy profile, this team must research the load and generation profiles.
The data from the profiles will be inputted into simulation software to further analyze the effects on the distribution grid.
In other words, we looked up some stuff! Fig. 1: Traditional Home Load Profile The load curve above depicts the average power demands of a traditional house without PV generation. Fig. 2: ZNE Home Load Profile The ZNE Home profile above, depicts the average daily demand with PV generation. Our path to progress Fig.3: PV generation profile PV generation curves for an individual ZNE home for different months in a year. Fig. 4: Total demand of typical ZNE home Total demand curve of a typical ZNE home in May with minimum load curves based on the standard residential service of SRP. Key tasks and Activities • Determine software to use for this project (first began with MatPower, resulted to Synergi in order to better provide results to SRP) • Gain access to software, familiarize ourselves with software by using the demo and manuals provided • Sort out load data needed and import into Synergi, then run SRP Warehouse data • Develop load model for the specified rate (give each section [of the grid] the specified load profile) • Develop a generation model for specified PV generation (give each section specified PV generation) • Research and import PV data into Synergi, incorporate ZNE Profile and Energy Storage • Run Simulation for Entire System (run the simulation with all 4 feeders and see the effect on the transformer, consumption and generation amounts) Fig. 5: Methods Using the Engineering Design Process, we followed those steps and related our project to them in order to complete our project. Challenges, Risks and Resolutions • Due to only having one license, we were only able to download the software onto one computer. This lead to the challenge of encountering a virus or other
technical difficulty on this computer. We encountered the computer having trouble turning on, however, we were able to get in contact with IT and
have a quick solution.
• The maintanence of having to get a new license each month was a risk of having to wait an extended time to gain access to the software once the previous license
experience. Towards the end of the project the license was delayed, resulting in our team not being able to work for those days without the license.
After simulation on all four feeders Fig. 6: Total demand of one feeder without energy storage Total demand in the feeder without energy storage applying peak load curves based on the standard residential service of SRP with 300 ZNE homes. Fig. 7: Total demand profile with different ZNE home penetration levels Total demand in the feeder at different rates of ZNE home penetration levels, for May, with minimum load curves based on the standard residential service of SRP. Impacts of implementing ZNE Homes Penetration of ZNE homes on distribution grid: • 20% ZNE penetration: 0.35 MW peak reverse flow • 30% ZNE penetration: 1.28 MW peak reverse flow • 40% ZNE penetration: 2.52 MW peak reverse flow • 50% ZNE penetration: 4.24 MW peak reverse flow The steep rates of increase (late afternoon) and decrease (morning) on the demand curve is of primary concern. Addition of energy storage, at single ZNE home, will reduce strain on distribution grid. Future implementation of ZNE homes will require energy storage systems to be grid optimized, charge during the mid-morning hours and discharge during the evening hours, for optimization. Fig.8: UGrads Poster Our final UGrads poster which contains: Motivation, Problem Statements, Methods, Results, Conclusion and Acknowledgements. Team Picture at UGrads with Our Client, Dr. YaramasuBackground Research
Analysis
Design Process
Challenges
Results
Conclusion
