Integrating energy and water optimization in buildings using multi-objective mixed-integer linear programming

Javanmard, Majid Emami; Ghaderi, S.F.; Sangari, Mohamad Sadegh

doi:10.1016/j.scs.2020.102409

Cited by 41 publications

(10 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Among them, incremental cost refers to the additional investment of green buildings compared with reference buildings (or benchmark buildings, i.e., nongreen buildings that only need to meet mandatory standards), mainly due to the application of energy-saving technology. Incremental benefits refer to the direct or indirect benefits brought by the reduction of operating costs during the operation of green buildings compared with the reference buildings [21]. Incremental comprehensive benefit is the difference between incremental benefit and incremental cost, as follows:…”

Section: Evaluation Model Of Incremental Comprehensive Benefitsmentioning

confidence: 99%

Multiobjective Optimization Design of Green Building Energy Consumption Based on Inorganic Thermal Insulation Nanomaterials

Yuan

2022

International Journal of Analytical Chemistry

View full text Add to dashboard Cite

In order to solve the problem that building engineering construction needs to consume a lot of energy and cause environmental pollution, which will pose a great pressure on urban resources and environment, this paper proposes that, in building engineering construction, appropriate green construction technology must be selected in combination with the actual situation, so as to effectively reduce the energy consumption of building engineering and improve the use efficiency of building engineering. Firstly, good thermal insulation nanomaterials are selected, which are cost-effective, safe, and nontoxic and has small thermal conductivity, large heat storage coefficient, stable chemical performance, and good construction performance. Secondly, it also needs to be selected according to the actual service life of the building. Because the current evaluation system is mostly aimed at the planning and design stage, and the structure occupies a large part in the building, for example, the impact on the construction period accounts for more than 50% and the impact on the cost accounts for 35%. Therefore, Duan Xiaorong and others established the grey cluster evaluation model of green building structure design based on the triangular whitening weight function. Finally, according to the relevant national regulations, this paper optimizes the design of green buildings based on the basic principles of energy conservation and emission reduction, high quality, and high efficiency.

show abstract

Section: Evaluation Model Of Incremental Comprehensive Benefitsmentioning

confidence: 99%

Multiobjective Optimization Design of Green Building Energy Consumption Based on Inorganic Thermal Insulation Nanomaterials

Yuan

2022

International Journal of Analytical Chemistry

View full text Add to dashboard Cite

show abstract

“…Numerous research works on various objectives, control schemes, optimization algorithms have made great efforts in developing an intelligent control system for efficient BEMS [31] [32]. However, achieving end-user satisfaction and comfort while maintaining the energy cost at the minimum level remains a challenge [33] [34]. Thus, the achievement of BEMS needs further investigation.…”

Section: Comfort Index Optimizationmentioning

confidence: 99%

Intelligent Controllers and Optimization Algorithms for Building Energy Management Towards Achieving Sustainable Development: Challenges and Prospects

et al. 2021

View full text Add to dashboard Cite

Buildings account for a significant amount of energy consumption leading to the issues of global emissions and climate change. Thus, energy management in a building is increasingly explored due to its significant potential in reducing the overall electricity expenses for the consumers and mitigating carbon emissions. In line with that, the greater control and optimization of energy management integrated with renewable energy resources is required to improve building energy efficiency while satisfying indoor environment comfort. Even though actions are being taken to reduce the energy consumption in buildings with several optimization and controller techniques, yet some issues remain unsolved. Therefore, this work provides a comprehensive review of the conventional and intelligent control methods with emphasis on their classification, features, configuration, benefits, and drawbacks. This review critically investigates the different optimization objectives and constraints with respect to comfort management, energy consumption, and scheduling. Furthermore, the review outlines the different methodological approaches to optimization algorithms used in building energy management. The contributions of controller and optimization in building energy management with the relation of sustainable development goals (SDGs) are explained rigorously. Discussions on the key challenges of the existing methods are presented to identify the gaps for future research. The review delivers some effective future directions that would be beneficial to the researchers and industrialists to design an efficiently optimized controller for building energy management toward targeting SDGs.INDEX TERMS Building energy management, controller, optimization, scheduling, sustainable development goals I. INTRODUCTIONPresently, buildings take the lead in consuming a substantial amount of energy, indicating about 40% of global energy consumption, which is responsible to release one-third of greenhouse gas (GHG) emissions [1], [2]. Another report demonstrates that buildings hold 49% of the total energy worldwide in which 60% of the energy is consumed for heating and cooling purposes [3], [4]. The poor management and ineffective control approach of appliances used in the building may result in a significant loss of energy in a

show abstract

“…The feasibility of the RWH system differs according to building category. Common evaluation models such as the linear programming model (Emami Javanmard, Ghaderi and Sangari, 2020), life cycle assessment (Stephan and Stephan, 2017), and the water balance model (Ghasemi Tousi and Doulabian, 2020； Kolavani and Kolavani, 2020;Shadmehri et al, 2020) require detailed data to describe each building. As a result, it cannot be applied universally in buildings of different scales via selected studies' cases, and the conclusions from an evaluation are unsuitable for region-level assessment.…”

Section: Introductionmentioning

confidence: 99%

How to Predict the Financial Prospects of a Rainwater Harvesting System——An Innovative Approach Based on Catchment Fraction

Shiguang

Sun

Qiuli

et al. 2022

Preprint

View full text Add to dashboard Cite

Rainwater harvesting (RWH) systems are one of the most promising technologies for water supply and economic viability is often a major barrier to their implementation. In order to develop a generic method to assess the economic viability of decentralized RWH systems at a regional level, this paper investigates the effect of variations in building characteristics on the economic performance of rainwater harvesting systems in regions where the water tariffs and rainfall distribution characteristics are fixed. This paper simulated the financial efficiency (expressed as a benefit-cost ratio) of a large number of decentralized RWH systems in Guangzhou, China. It is found that the financial efficiency of RWH systems is closely related to the catchment fraction (the ratio of rainfall catchment surface to total floor area). Based on this dimensionless parameter, explicit equations expressing the financial efficiency of RWH systems were derived using a nonlinear regression method. In addition, the validity of the analytical equations was verified by the root mean square error test, normality test, and error distribution test. This analytical solution provides a simple and generic method for forecasting the investment potential of rainwater harvesting systems. The developed methodology can also be adapted to other regions merely the variations of local water price and rainfall data need to be considered.

show abstract

Integrating energy and water optimization in buildings using multi-objective mixed-integer linear programming

Cited by 41 publications

References 58 publications

Multiobjective Optimization Design of Green Building Energy Consumption Based on Inorganic Thermal Insulation Nanomaterials

Multiobjective Optimization Design of Green Building Energy Consumption Based on Inorganic Thermal Insulation Nanomaterials

Intelligent Controllers and Optimization Algorithms for Building Energy Management Towards Achieving Sustainable Development: Challenges and Prospects

How to Predict the Financial Prospects of a Rainwater Harvesting System——An Innovative Approach Based on Catchment Fraction

Contact Info

Product

Resources

About