Residential Energy Performance Metrics

Wright, C. David; Baur, Stuart Werner; Grantham, Katie; Stone, Robert B.; Grasman, Scott E.

doi:10.3390/en3061194

Cited by 10 publications

(7 citation statements)

References 3 publications

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“…The utility costs for residential consumers can be saved by the support of RESs and ESS [14] in smart grid architecture. The work presented in [15] outlined a detailed review of the current progression in the HEM system, challenges in appliance scheduling, and energy optimization in the smart grid community. In addition, the incorporation of RESs into households and their effects on utility tariffs have not been addressed properly.…”

Section: Introductionmentioning

confidence: 99%

“…However, this work did not take into account the cluster-based energy management and energy allocation algorithm (EAA) in the smart grid framework. The authors in [15,16] demonstrated a household energy supervising system interfaced with a data logger unit to measure and record the electricity generation and demand patterns. In addition, RESs, ESS, and self-satisfied power demand were not considered to generate an alternative source of energy and storage facilities while peak demand appears.…”

Section: Introductionmentioning

confidence: 99%

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Development of Cluster-Based Energy Management Scheme for Residential Usages in the Smart Grid Community

Rashid

Granelli

et al. 2020

Electronics

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Several efforts have been taken to promote clean energy towards a sustainable and green economy. Existing sources of electricity present some complications concerning consumers, utility owners, and the environment. Utility operators encourage household applicants to employ residential energy management (REM) systems. Renewable energy sources (RESs), energy storage systems (ESS), and optimal energy allocation strategies are used to resolve these difficulties. In this paper, the development of a cluster-based energy management scheme for residential consumers of a smart grid community is proposed to reduce energy use and monetary cost. Normally, residential consumers deal with household appliances with various operating time slots depending on consumer preferences. A simulator is designed and developed using C++ software to resolve the residential consumer’s REM problem. The benefits of the RESs, ESS, and optimal energy allocation techniques are analyzed by taking in account three different scenarios. Extensive case studies are carried out to validate the effectiveness of the proposed cluster-based energy management scheme. It is demonstrated that the proposed method can save energy and costs up to 45% and 56% compared to the existing methods.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development of Cluster-Based Energy Management Scheme for Residential Usages in the Smart Grid Community

Rashid

Granelli

et al. 2020

Electronics

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“…Numerous factors are involved when considering energy-saving designs, particularly for large-scale carbon-neutral community building developments; examples include the use of renewable energies [31], eco-designs [32], solar energy [33][34][35], lighting [36], compressed shopper waste (CSW) blocks [37], waste disposal [8], air-conditioning facilities [38], ventilation designs [39,40], shading designs [41], heating systems [42,43], green roofs [44], building envelopes [45], and wall insulation for buildings and double-skin facades [46][47][48]. Therefore, comprehensive preparation in integration and design is required to demonstrate effectiveness.…”

Section: Introductionmentioning

confidence: 99%

A DFuzzy-DAHP Decision-Making Model for Evaluating Energy-Saving Design Strategies for Residential Buildings

Liu

Hsueh

et al. 2012

Energies

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Abstract:The construction industry is a high-pollution and high-energy-consumption industry. Energy-saving designs for residential buildings not only reduce the energy consumed during construction, but also reduce long-term energy consumption in completed residential buildings. Because building design affects investment costs, designs are often influenced by investors' decisions. A set of appropriate decision-support tools for residential buildings are required to examine how building design influences corporations externally and internally. From the perspective of energy savings and environmental protection, we combined three methods to develop a unique model for evaluating the energy-saving design of residential buildings. Among these methods, the Delphi group decision-making method provides a co-design feature, the analytical hierarchy process (AHP) includes multi-criteria decision-making techniques, and fuzzy logic theory can simplify complex internal and external factors into easy-to-understand numbers or ratios that facilitate decisions. The results of this study show that incorporating solar building materials, double-skin facades, and green roof designs can effectively provide high energy-saving building designs.

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“…Moreover, the barriers, challenges, benefits, and future trends regarding the communication technologies and their role in the SG and SHs are also discussed. The authors in [14], demonstrate a residential energy monitoring system (REMS). Three SHs powered by an in-house RES (i.e., PV system) are considered for demonstration.…”

Section: Related Workmentioning

confidence: 99%

An Optimized Home Energy Management System with Integrated Renewable Energy and Storage Resources

et al. 2017

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Traditional power grid and its demand-side management (DSM) techniques are centralized and mainly focus on industrial consumers. The ignorance of residential and commercial sectors in DSM activities degrades the overall performance of a conventional grid. Therefore, the concept of DSM and demand response (DR) via residential sector makes the smart grid (SG) superior over the traditional grid. In this context, this paper proposes an optimized home energy management system (OHEMS) that not only facilitates the integration of renewable energy source (RES) and energy storage system (ESS) but also incorporates the residential sector into DSM activities. The proposed OHEMS minimizes the electricity bill by scheduling the household appliances and ESS in response to the dynamic pricing of electricity market. First, the constrained optimization problem is mathematically formulated by using multiple knapsack problems, and then solved by using the heuristic algorithms; genetic algorithm (GA), binary particle swarm optimization (BPSO), wind driven optimization (WDO), bacterial foraging optimization (BFO) and hybrid GA-PSO (HGPO) algorithms. The performance of the proposed scheme and heuristic algorithms is evaluated via MATLAB simulations. Results illustrate that the integration of RES and ESS reduces the electricity bill and peak-to-average ratio (PAR) by 19.94% and 21.55% respectively. Moreover, the HGPO algorithm based home energy management system outperforms the other heuristic algorithms, and further reduces the bill by 25.12% and PAR by 24.88%.

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Residential Energy Performance Metrics

Cited by 10 publications

References 3 publications

Development of Cluster-Based Energy Management Scheme for Residential Usages in the Smart Grid Community

Development of Cluster-Based Energy Management Scheme for Residential Usages in the Smart Grid Community

A DFuzzy-DAHP Decision-Making Model for Evaluating Energy-Saving Design Strategies for Residential Buildings

An Optimized Home Energy Management System with Integrated Renewable Energy and Storage Resources

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