A real industrial building: Modeling, calibration and Pareto optimization of energy retrofit

Ascione, Fabrizio; Bianco, Nicola; Iovane, Teresa; Mauro, Gerardo Maria; Napolitano, Davide Ferdinando; Ruggiano, Antonio; Viscido, Lucio

doi:10.1016/j.jobe.2020.101186

Cited by 52 publications

(23 citation statements)

References 42 publications

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“…Mainly, a calibration process describes by the literature of use energy consumption as the analysis variable [14,[21][22][23][24][25][26][27][28][29][30][31], although the inner temperature can also be used [21,22,24].…”

Section: Energy Modeling Of the Buildings Belonging To The Samplementioning

confidence: 99%

“…The energy consumption data of buildings can be obtained from databases (local or national), bills, or a set of energy meters for monitoring specific areas or services (e.g., HVAC, lighting, appliances, etc.). In general, the calibration process of the energy models of single dwellings uses databases [13,14,18] or bills [24,31], while this process can be supported by bills [21][22][23]25,[28][29][30] or a set of energy meters [21,23,24,28,30] for commercial or school buildings.…”

Section: Energy Modeling Of the Buildings Belonging To The Samplementioning

confidence: 99%

“…Although the calibration process could be done using energy consumption data for the whole building, this work proposes to conduct the calibration of energy models in two The validity of the energy models can be reached through a calibration process, which consists of mainly three steps: comparison between the comparison of simulated data and measured data, identification of the error causes, and adjustment of input data (e.g., the physical parameter of the buildings, occupancy behavior, or schedule and rated power of equipment) [21].…”

Section: Energy Modeling Of the Buildings Belonging To The Samplementioning

confidence: 99%

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Improvement Proposal of Bottom-Up Approach for the Energy Characterization of Buildings in the Tropical Climate

2021

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The energy characterization of buildings can be done by bottom-up methods such as energy simulation models (samples or archetypes). A sample consists of the selection of real buildings and an archetype is a theoretical building that represents them. Nevertheless, both approaches have shortcomings for the creation of energy models. This work proposes to improve the sampling approach from the validation of input data, and calibration of models by individual adjustment processes. The studied category corresponds to multi-family buildings of median incomes from the Metropolitan Area of Bucaramanga (Colombia). This study presents the energy model of five existing buildings and an archetype, calibration results, energy characterization, and comparative analysis between both approaches. The sampling approach indicates that housing units and general services demand an average of 76.9% and 23.1% of consumed energy, respectively. The average energy consumption by housing units is 22.38 kWh/m2·year caused by appliances (85.3%), lighting (11.2%), and air conditioning (3.5%). The archetype presents similar results for the energy consumption of housing units (kWh/m2·year), but notable differences concerning a specific behavior of inner spaces, being the sampling approach more accurate to characterize to a building category.

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Section: Energy Modeling Of the Buildings Belonging To The Samplementioning

confidence: 99%

Section: Energy Modeling Of the Buildings Belonging To The Samplementioning

confidence: 99%

Section: Energy Modeling Of the Buildings Belonging To The Samplementioning

confidence: 99%

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Improvement Proposal of Bottom-Up Approach for the Energy Characterization of Buildings in the Tropical Climate

2021

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“…For this reason, many optimizations were performed using different algorithms and related parameters, finding that Omni-Optimizer genetic algorithm [66] with 40 individuals and 200 generations was the most adequate to the problem assessed in this study, providing many solutions in the Pareto Front that satisfied the constraints. The resulting Pareto Front was investigated to understand which kind of renovation solutions should be preferred, after the removal of non-feasible solutions, and the utopia point criterion was adopted to identify the best compromise solution [67]. This criterion is based on the evidence that, in the multi-dimensional space of the objective functions, the origin of axes would represent a building with null values of each objective function, and thus an ideal solution.…”

Section: Case Study: the Renovation Of An Apartment Buildingmentioning

confidence: 99%

Multi-Objective Optimization of Building Life Cycle Performance. A Housing Renovation Case Study in Northern Europe

Montana¹,

Kanafani

Wittchen

et al. 2020

Sustainability

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While the operational energy use of buildings is often regulated in current energy saving policies, their embodied greenhouse gas emissions still have a considerable mitigation potential. The study aims at developing a multi-objective optimization method for design and renovation of buildings incorporating the operational and embodied energy demands, global warming potential, and costs as objective functions. The optimization method was tested on the renovation of an apartment building in Denmark, mainly focusing envelope improvements as roof and exterior wall insulation and windows. Cellulose insulation has been the predominant result, together with fiber cement or aluminum-based cladding and 2-layered glazing. The annual energy demand has been reduced from 166.4 to a range between 76.5 and 83.7 kWh/(m2 y) in the optimal solutions. The fact that the legal requirements of 70 kWh/(m2 y) are nearly met without building service improvements indicates that energy requirements can be fulfilled without compromising greenhouse gas emissions and cost. Since the method relies on standard national performance reporting tools, the authors believe that this study is a preliminary step towards more cost-efficient and low-carbon building renovations by utilizing multi-optimization techniques.

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“…Nowadays, the issue of energy consumption has attracted much attention regarding its relations with environmental problems, economic developments, and sustainability of life [1]. However, generation and demand should be balanced to maintain the sustainability and reliability of the energy system.…”

Section: Introductionmentioning

confidence: 99%

Sequential Tasks Shifting for Participation in Demand Response Programs

et al. 2020

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In this paper, the proposed methodology minimizes the electricity cost of a laundry room by means of load shifting. The laundry room is equipped with washing machines, dryers, and irons. Additionally, the optimization model handles demand response signals, respecting user preferences while providing the required demand reduction. The sequence of devices operation is also modeled, ensuring correct operation cycles of different types of devices which are not allowed to overlap or have sequence rules. The implemented demand response program specifies a power consumption limit in each period and offers discounts for energy prices as incentives. In addition, users can define the required number of operations for each device in specific periods, and the preferences regarding the operation of consecutive days. In the case study, results have been obtained regarding six scenarios that have been defined to survey about effects of different energy tariffs, power limitations, and incentives, in a laundry room equipped with three washing machines, two dryers, and one iron. A sensitivity analysis of the power consumption limit is presented. The results show that the proposed methodology is able to accommodate the implemented scenario, respecting user preferences and demand response program, minimizing energy costs. The final electricity price has been calculated for all scenarios to discuss the more effective schedule in each scenario.

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A real industrial building: Modeling, calibration and Pareto optimization of energy retrofit

Cited by 52 publications

References 42 publications

Improvement Proposal of Bottom-Up Approach for the Energy Characterization of Buildings in the Tropical Climate

Improvement Proposal of Bottom-Up Approach for the Energy Characterization of Buildings in the Tropical Climate

Multi-Objective Optimization of Building Life Cycle Performance. A Housing Renovation Case Study in Northern Europe

Sequential Tasks Shifting for Participation in Demand Response Programs

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