Multi-Objective Optimization Approach for Improving Performance of Building

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)).

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.


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

Proceedings ◽  
2020 ◽  
Vol 65 (1) ◽  
pp. 11
Author(s):  
Vincenzo D’Agostino ◽  
Arturo Lapietra ◽  
Luca Petrungaro

This study provides an estimation of pay-4-performance (P4P) rates that energy providers are willing to offer in a P4P scheme in EU according to the classification of Energy efficiency measures (classes of EEMs). Seven different categories of EEMs are identified and 4 different tables for evaluating the EEMs are devised. After devising the classes of EEMs, the P4P rate concept is presented through the mechanism of the Energy Efficiency obligation schemes and considering the energy providers’ perspective. The proposed approach is not focused on quantifying the P4P rates, but on identifying which variables and parameters can affect these rates.


Buildings ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 88
Author(s):  
Shobhit Chaturvedi ◽  
Elangovan Rajasekar ◽  
Sukumar Natarajan

Operational uncertainties play a critical role in determining potential pathways to reduce the building energy footprint in the Global South. This paper presents the application of a non-dominated sorting genetic (NSGA II) algorithm for multi-objective building design optimization under operational uncertainties. A residential building situated in a mid-latitude steppe and desert region (Köppen climate classification: BSh) in the Global South has been selected for our investigation. The annual building energy consumption and the total number of cooling setpoint unmet hours (h) were assessed over 13,122 different energy efficiency measures. Six Pareto optimal solutions were identified by the NSGA II algorithm. Robustness of Pareto solutions was evaluated by comparing their performance sensitivity over 162 uncertain operational scenarios. The final selection for the most optimal energy efficiency measure was achieved by formulating a robust multi-criteria decision function by incorporating performance, user preference, and reliability criteria. Results from this robust approach were compared with those obtained using a deterministic approach. The most optimal energy efficiency measure resulted in 9.24% lower annual energy consumption and a 45% lower number of cooling setpoint unmet h as compared to the base case.


2008 ◽  
Vol 40 (9) ◽  
pp. 1747-1754 ◽  
Author(s):  
Christina Diakaki ◽  
Evangelos Grigoroudis ◽  
Dionyssia Kolokotsa

2019 ◽  
Vol 52 (25) ◽  
pp. 477-482 ◽  
Author(s):  
Vassil G. Guliashki ◽  
Galia I. Marinova ◽  
Peter P. Groumpos

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