Dynamic Modeling and Optimal Design for Net Zero Energy Houses Including Hybrid Electric and Thermal Energy Storage

Gong, Huangjie; Rallabandi, Vandana; Ionel, Dan M.; Colliver, D. G.; Duerr, Shaun; Ababei, Cristinel

doi:10.1109/tia.2020.2986325

Cited by 27 publications

(15 citation statements)

References 43 publications

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“…3. INSPIRE+D incorporates freeware such as Energy-Plus, BEopt, OpenDSS, and Python, and is capable of both power flow analysis at the system level, and house energy modeling along with HEM at the single house level [29]. Its scalability allows the simulation of thousands of different house models in parallel, utilizing a high-performance computing (HPC) system with thousands of cores.…”

Section: Technology Demonstrator and Analysis Frameworkmentioning

confidence: 99%

“…Most EWH manufacturers provide the CTA-2045 modules in their new products or offer refurbishments to enable real-time communication and control [27], [28]. Previous research published by the extended group of authors showed that a smart home may achieve comparable functionality with a smaller battery energy capacity, provided that special EWH and associated controls are incorporated in a hybrid energy storage system [29]. The paper included a systematic sizing procedure for such a home-based hybrid energy storage system and modeled it with a co-simulation framework for building energy use and electric power flow in distribution systems.…”

Section: Introductionmentioning

confidence: 99%

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Peak Reduction and Long Term Load Forecasting for Large Residential Communities Including Smart Homes With Energy Storage

et al. 2021

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Domestic load profiles in the residential sectors are being modified with the adoption of smart home management systems and solar generation. In addition, houses with rooftop PV behave like local generators, contributing to the growth of the penetration of PV energy. Hence, the demand for power is declining day by day. However, the increasing PV penetration causes technical challenges for the power system, such as the "duck curve". This can be addressed through home energy management (HEM) techniques including peak shaving, load shifting with smart home devices. In this regard, electric water heaters (EWH), with high thermal mass and being ubiquitous, are attractive and low-cost energy storage systems. In this paper, a case study for one of the largest rural field smart energy technology demonstrators involving business, industries, and more than 5,000 residences, located in Glasgow, KY, US, is presented. Furthermore, a HEM system, which aims to minimize the total energy usage and peak demand by regulating the heating, ventilation, and airconditioning (HVAC) systems, water heaters, and batteries, thereby benefiting both the utility and the consumer is proposed. This work also demonstrates the ability of EWH to provide ancillary services while maintaining customer comfort. The minimum participation rates for EWH and batteries are calculated and compared with respect to different peak reduction targets. Long term load prediction by considering different fractions of smart homes for the utility is also provided.

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Section: Technology Demonstrator and Analysis Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Peak Reduction and Long Term Load Forecasting for Large Residential Communities Including Smart Homes With Energy Storage

et al. 2021

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“…The technical and economic constraints of different energy services, which might serve for net-zero emissions energy systems have been presented in [11]. On a smaller scale, the concept of net-zero energy buildings has been analyzed [12]. The technologies, construction design, and their operation have been presented in [13] and [14].…”

Section: Introductionmentioning

confidence: 99%

A Vision for Energy Decarbonization: Planning Sustainable Tertiary Sites as Net-Zero Energy Systems

et al. 2021

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The power system is changing towards a decarbonized one. The Kyoto protocol and the Paris climate agreement have prompted many nations to approve energy policies based on volatile renewable energy sources (RESs). However, the integration into the grid of the power generated by RESs as well as the electrification of the heating, gas and transportation sectors is becoming a huge challenge. Planning industrial and tertiary sites as net-zero energy systems (NZESs) might contribute to advance the solutions of fully integrating volatile RESs into the power system. This study aims to point out the importance of planning large energy consumer sites such as NZESs, and to depict a holistic modeling approach for this. The methodology is based on a multi-layer approach, which focuses on on-site power generation by RESs, on the improvement of energy efficiency, and on the increase of system flexibility. A qualitative case study has been conducted. It considers the planning of a Net-Zero Energy Data Center located in Germany. Results point out that new interdisciplinary and in particular social analysis methods are necessary. They might be used for accelerating the decision making process during the planning of RES-based on-site power generation systems. Besides, for computation and cooling systems, new technologies that are continuously emerging in the market should be taken into account. If well designed, they contribute to significantly decrease the whole energy demand of data center. Finally, optimal sizing of energy storage systems (electric and thermal) as well as an expedient choice of performance indicators to evaluate technology options are identified as the key factor for decreasing the external energy demand of tertiary sites, such as data center.

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“…As PV penetration keeps rising, there are multiple benefits of incorporating EWHs into home energy management. Recent research indicates that battery capacity may be reduced by up to 30% when batteries are coordinated with EHW, which were regarded as "uni-directional" energy storage [2].…”

Section: Introductionmentioning

confidence: 99%

Equivalent Electric and Heat-Pump Water Heater Models for Aggregated Community-Level Demand Response Virtual Power Plant Controls

Gong¹,

Rooney²,

Akeyo

et al. 2021

IEEE Access

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Advanced control techniques may be used to establish a virtual power plant to regulate the operation of electric water heaters, which may be regarded as a "uni-directional battery" and a major component of a hybrid residential energy storage system. In order to estimate the potential of regulating water heaters at the aggregated level, factors including user behavior, number of water heaters, and types of water heaters must be considered. This study develops generic water heater load curves based on the data retrieved from large experimental projects for resistive electric water heaters (EWHs) and heat pump water heaters (HPWHs). A community-level digital twin with scalability has been developed to capture the aggregated hot water flow and average hot temperature in the tank. The results in this paper also include the "energy take" in line with the CTA-2045 standard and Energy Star specification. The data from the experiments demonstrated that changing from an EWH to an HPWH reduces electricity usage by approximately 70%. The case study showed that daily electricity usage could be shifted by approximately 14% and 17% by EWH and HPWHs, respectively, compared to their corresponding average power. Another case study showed that both EHWs and HPWHs, coordinated with PV to reduce morning and evening peaks, could shift approximately 22% of the daily electricity.

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Dynamic Modeling and Optimal Design for Net Zero Energy Houses Including Hybrid Electric and Thermal Energy Storage

Cited by 27 publications

References 43 publications

Peak Reduction and Long Term Load Forecasting for Large Residential Communities Including Smart Homes With Energy Storage

Peak Reduction and Long Term Load Forecasting for Large Residential Communities Including Smart Homes With Energy Storage

A Vision for Energy Decarbonization: Planning Sustainable Tertiary Sites as Net-Zero Energy Systems

Equivalent Electric and Heat-Pump Water Heater Models for Aggregated Community-Level Demand Response Virtual Power Plant Controls

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