Abstract

With the increased adoption of distributed energy resources (DERs) and renewables, such as solar panels at the building level, consumers turn into prosumers with generation capability to supply their on-site demand. The temporal complementarity between supply and demand at the building level provides opportunities for energy exchange between prosumers and consumers towards community-level self-sufficiency. Investigating different aspects of community-level energy exchange in cyber and physical layers has received attention in recent years with the increase in renewables adoption. In this study, we have presented an in-depth investigation into the impact of energy exchange through the quantification of temporal energy deficit–surplus complementarity and its associated self-sufficiency capacities by considering the impact of variations in community infrastructure configurations, variations in household energy use patterns, and the potential for user adaptation for load flexibility. To this end, we have adopted a data-driven simulation using real-world data from a case-study neighborhood consisting of ~250 residential buildings in Austin, TX with a mix of prosumers and consumers and detailed data on decentralized DERs. By accounting for the uncertainties in energy consumption patterns across households, different levels of PV and energy storage integration, and different modalities of user adaptation, various scenarios of operations were simulated. The analysis showed that with PV integration of more than 75%, energy exchange could result in self-sufficiency for the entire community during peak generation hours from 11 a.m. to 3 p.m. However, there are limited opportunities for energy exchange during later times with PV-standalone systems. As a potential solution, leveraging building-level storage or user adaptation for load shedding/shifting during the 2-h low-generation timeframe (i.e., 5–7 p.m.) was shown to increase community self-sufficiency during generation hours by 17% and 5–10%, respectively, to 83% and 71–76%.

Highlights

  • Managing distributed energy resources (DERs) in microgrids draws on opportunities that are provided by elements such as communication technologies, metering devices, controllable loads, renewable energy sources, storage systems, and human–building interaction for the improved operation of a power system

  • We quantified the temporal variation of surplus–deficit complementarity capacity by considering varied infrastructure configurations—i.e., the ratio of prosumers to consumers

  • Improved complementarity led to increased community-level self-sufficiency, which was quantified by considering the impact of varying levels of energy storage integrations compared to user adaptation for load flexibility

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Summary

Introduction

Managing distributed energy resources (DERs) in microgrids draws on opportunities that are provided by elements such as communication technologies, metering devices, controllable loads, renewable energy sources (e.g., solar panels), storage systems, and human–building interaction for the improved operation of a power system. We have investigated how these human factors could affect the temporal complementarity under the constraints of infrastructure configurations, the penetration level of small-scale DER assets—i.e., solar panels and storage systems at the prosumer level. To this end, we have examined how the reshaping of energy profiles through load flexibility/user adaptation impacts load-balancing capacities. We have investigated how diverse and realistic household load profiles (representing energy use behaviors) affect the temporal complementarity for self-sufficiency in communities with different mixes of prosumers and consumers These investigations have been guided by defining varying levels of solar panels and energy storage penetration as distributed. The findings could help infrastructure planners evaluate the required share of DERs and the impact of consumer-focused programs in future networks that rely on energy trading for decentralized energy management

Research Background
Methodology
Basic Definitions
Dynamic Energy Use Behavior at the Household Level
Dynamic Energy Use Behavior and Load Profile Change at the Household Level
Battery Modeling
Case-Study CommunityCharacteristics
Solarand generation in the during case-study community:
Baseline Surplus–Deficit Temporal Complementarity Quantification
Energy Storage Integration
User Adaptation and Load Profile Change as Complementarity Capacity
Market Design and User Behavior Dimensions’ Impact on Self-Sufficiency
Limitations
Conclusions

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