Application of multi-objective optimization model to assess the energy efficiency measures for the cases of Spain

2021 ◽  
Vol 38 ◽  
pp. 102144
Author(s):  
Bo Liu ◽  
Dragan Rodriguez
2021 ◽  
Vol 13 (20) ◽  
pp. 11554
Author(s):  
Fahad Haneef ◽  
Giovanni Pernigotto ◽  
Andrea Gasparella ◽  
Jérôme Henri Kämpf

Nearly-zero energy buildings are now a standard for new constructions. However, the real challenge for a decarbonized society relies in the renovation of the existing building stock, selecting energy efficiency measures considering not only the energy performance but also the economic and sustainability ones. Even if the literature is full of examples coupling building energy simulation with multi-objective optimization for the identification of the best measures, the adoption of such approaches is still limited for district and urban scale simulation, often because of lack of complete data inputs and high computational requirements. In this research, a new methodology is proposed, combining the detailed geometric characterization of urban simulation tools with the simplification provided by “building archetype” modeling, in order to ensure the development of robust models for the multi-objective optimization of retrofit interventions at district scale. Using CitySim as an urban scale energy modeling tool, a residential district built in the 1990s in Bolzano, Italy, was studied. Different sets of renovation measures for the building envelope and three objectives —i.e., energy, economic and sustainability performances, were compared. Despite energy savings from 29 to 46%, energy efficiency measures applied just to the building envelope were found insufficient to meet the carbon neutrality goals without interventions to the system, in particular considering mechanical ventilation with heat recovery. Furthermore, public subsidization has been revealed to be necessary, since none of the proposed measures is able to pay back the initial investment for this case study.


Author(s):  
A. Kamenders ◽  
A. Blumberga

Multi-Objective Optimization Approach for Improving Performance of Building Energy efficiency measures are different from energy efficiency and cost effectiveness perspective. For decision maker it is hard to make right decision about different energy efficiency measure combinations in building. It is a complex problem to choose the best energy efficiency measure combination as decision involves many different factors that should be taken in account. Decision on implementation of energy efficiency measure implementation usually depends on investment costs and pay back time. Standards like Latvian Building Code LBN 002-01 can't be used to achieve reasonable expenses in renovation of buildings. Therefore, in order to find the optimal energy-efficiency measures, it is necessary to carry out optimization taking all the variable parameters into account. In the paper target function was presented that gives ability of the multi-objective optimization approach to handle the problem of improving energy efficiency in buildings. Case study is used to demonstrate the feasibility of the approach. 104. series soviet type dwellings was analysed to optimized insulation thickness for external walls. Even if accord with the LBN 002-01 it is enough to use 7 cm thick isolation (λ-0,039 W/(m2K)) layers optimal insulation layer is 12 cm (λ-0,039 W/(m2K)).


2017 ◽  
Vol 35 ◽  
pp. 764-773 ◽  
Author(s):  
Monica M. Eskander ◽  
M. Sandoval-Reyes ◽  
Carlos A. Silva ◽  
S.M. Vieira ◽  
João M.C. Sousa

Author(s):  
Baoxue Bai ◽  
Zhuang Xiao ◽  
Qingyuan Wang ◽  
Pengfei Sun ◽  
Xiaoyun Feng

The overspeed protection, smooth driving, punctuality, and energy efficiency of freight trains largely depend on their trajectory optimization. This paper proposes a multi-objective optimization model, which maximizes the weighted sum of energy efficiency, punctuality, and driving smoothness. Model constraints systematically cover many practical conditions, including varying line resistance, overspeed protection, discrete neutral zones, and nonlinear traction and electric braking characteristics. Electric braking and pneumatic braking are distinguished in the freight train model, and the utilization of feedback braking energy is also considered. By nonlinear approximation, the proposed multi-objective optimization model is solved by the quadratic programming (QP) algorithm, and optimized trajectories are obtained. Numerical simulation demonstrates the correctness and effectiveness of the proposed method. Comparisons with two actual trials show that the energy efficiency and driving smoothness of the proposed method are better than that of the drivers’ operation with the same journey time. In addition, the algorithm has a short computation time, which has the potential to be integrated for on-board devices such as the driver advisory system (DAS).


2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Bruno Ramos Zemero ◽  
Maria Emília de Lima Tostes ◽  
Ubiratan Holanda Bezerra ◽  
Vitor dos Santos Batista ◽  
Carminda Célia M. M. Carvalho

Buildings' energy consumption has a great energetic and environmental impact worldwide. The architectural design has great potential to solve this problem because the building envelope exerts influence on the overall system performance, but this is a task that involves many objectives and constraints. In the last two decades, optimization studies applied to energy efficiency of buildings have helped specialists to choose the best design options. However, there is still a lack of optimization approaches applied to the design stage, which is the most influential stage for building energy efficiency over its entire life cycle. Therefore, this article presents a multi-objective optimization model to assist designers in the schematic building design, by means of the Pareto archived evolutionary strategies (PAES) algorithm with the EnergyPlus simulator coupled to evaluate the solutions. The search process is executed by a binary array where the array components evolve over the generations, together with the other building components. The methodology aims to find optimal solutions (OSs) with the lowest constructive cost associated with greater energy efficiency. In the case study, it was possible to simulate the process of using the optimization model and analyze the results in relation to: a standard building; energy consumption classification levels; passive design guidelines; usability and accuracy, proving that the tool serves as support in building design. The OSs reached an average of 50% energy savings over typical consumption, 50% reduction in CO2 operating emissions, and investment return less than 3 years in the four different weathers.


2021 ◽  
Vol 13 (13) ◽  
pp. 7251
Author(s):  
Mushk Bughio ◽  
Muhammad Shoaib Khan ◽  
Waqas Ahmed Mahar ◽  
Thorsten Schuetze

Electric appliances for cooling and lighting are responsible for most of the increase in electricity consumption in Karachi, Pakistan. This study aims to investigate the impact of passive energy efficiency measures (PEEMs) on the potential reduction of indoor temperature and cooling energy demand of an architectural campus building (ACB) in Karachi, Pakistan. PEEMs focus on the building envelope’s design and construction, which is a key factor of influence on a building’s cooling energy demand. The existing architectural campus building was modeled using the building information modeling (BIM) software Autodesk Revit. Data related to the electricity consumption for cooling, building masses, occupancy conditions, utility bills, energy use intensity, as well as space types, were collected and analyzed to develop a virtual ACB model. The utility bill data were used to calibrate the DesignBuilder and EnergyPlus base case models of the existing ACB. The cooling energy demand was compared with different alternative building envelope compositions applied as PEEMs in the renovation of the existing exemplary ACB. Finally, cooling energy demand reduction potentials and the related potential electricity demand savings were determined. The quantification of the cooling energy demand facilitates the definition of the building’s electricity consumption benchmarks for cooling with specific technologies.


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