Operation optimization strategy of existing residential building energy-saving renovation market:From the perspective of subject behavior

The energy-saving renovation of existing residential buildings is a crucial measure to achieve the strategic goal of energy conservation and emission reduction in China and build ecologically livable cities.This article focuses on the perspective of subject behavior,starting from analyzing the current situation and difficulties of the operation of the energy-saving renovation market for existing residential buildings in China,drawing on the practical experience of the operation of the existing residential building energy-saving renovation market abroad.Based on principles such as systematicity,humanization,feasibility,and sustainability,the article constructs an operation optimization system of the existing residential building energy-saving renovation market from the perspective of subject behavior.In order to provide a reference for the healthy and orderly operation of the existing residential building energy-saving renovation market,this paper proposes implementation strategies for optimizing the operation of the existing residential building energy-saving renovation market.Suggestions are proposed from four aspects:optimizing the market environment,innovating the financing model,building the information sharing platform,and utilizing the synergies of the main subjects.

Multi-subject and multi-objective integrated optimization system and implementation strategy for energy-saving renovation of the existing residential buildings

The core of the healthy and orderly operation of the existing residential building energy-saving renovation market lies in the exploration of the implementation mechanism of multi-subject and multi-objective integrated optimization.The multi-agent and multi-objective integrated optimization system framework is a powerful tool to guide the scientific decision-making of the market core structural entities in the future market practice. This paper analyzes the practical dilemma of energy-saving renovation of theexisting residential buildings in China, summarizes the practical experience of multi-subject and multi-objective integrated optimization of energy-saving renovation of the existing residential buildings in foreign countries, and puts forward beneficial practical enlightenment on the basis of comparison at home and abroad;The design principles of the target integrated optimization system have established a multi-subject and multi-objective integrated optimization system framework for the energy-saving renovation of the existing residential buildings, from six aspects: government guidance, trust consensus, value co-creation, risk sharing, revenue sharing, and social responsibility sharing. This paper proposes a multi-subject and multi-objective integrated practice strategy, in order to promote the efficient and orderly development of China's existing residential building energy-saving renovation market.

Optimization and implementation strategy of ESCO driving force in the development of energy-saving transformation market of existing buildings

The development of the existing building energy-saving transformation market is inseparable from the internal driving force of ESCO.Giving full play to the driving role of ESCO scientifically is the internal requirement to promote the healthy and orderly operation of the existing building energy-saving transformation market.This paper summarizes the practical experience of developing ESCO driving force operation in foreign existing building energy-saving transformation market,analyzes the bottleneck of developing ESCO driving force operation in China’s existing building energy-saving transformation market,and puts forward useful practical enlightenment based on the comparison between home and abroad;According to the optimization principle of ESCO driving force operation in the development of existing building energy-saving transformation market,the optimization design framework of ESCO driving force is proposed,and the implementation strategy of ESCO driving force optimization in the development of existing building energy-saving transformation market is planned.In order to optimize and improve the effectiveness of the operation and development of the energy-saving transformation market of existing buildings with the internal driving force of ESCO.

Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer

The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worker constraints.As one critical factor of production,effective utilization of worker resources can increase productivity.Meanwhile,energy consumption is a growing concern due to the increasingly serious environmental issues.Therefore,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this paper.To solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling schemes.To further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are proposed.These strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto solutions.The effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 instances.The results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.

Parameters Optimization and Performance Evaluation of the Tuned Inerter Damper for the Seismic Protection of Adjacent Building Structures

In order to improve the seismic performance of adjacent buildings,two types of tuned inerter damper(TID)damping systems for adjacent buildings are proposed,which are composed of springs,inerter devices and dampers in serial or in parallel.The dynamic equations of TID adjacent building damping systems were derived,and the H2 norm criterion was used to optimize and adjust them,so that the system had the optimum damping performance under white noise random excitation.Taking TID frequency ratio and damping ratio as optimization parameters,the optimum analytical solutions of the displacement frequency response of the undamped structure under white noise excitation were obtained.The results showed that compared with the classic TMD,TID could obtain a better damping effect in the adjacent buildings.Comparing the TIDs composed of serial or parallel,it was found that the parallel TIDs had more significant advantages in controlling the peak displacement frequency response,while the H2 norm of the displacement frequency response of the damping system under the coupling of serial TID was smaller.Taking the adjacent building composed of two ten-story frame structures as an example,the displacement and energy collection time history analysis of the adjacent building coupled with the optimum design parameter TIDs were carried out.It was found that TID had a better damping effect in the full-time range compared with the classic TMD.This paper also studied the potential power of TID in adjacent buildings,which can be converted into available power resources during earthquakes.

Exploration of Energy-Saving Technologies in Building Electrical System Design

Green energy conservation is the mainstream trend in the current development of the construction industry.The application of energy-saving technology in building electrical system design can effectively reduce energy consumption,avoid unnecessary energy consumption,and truly achieve energy conservation and environmental protection.Based on this,the article elaborates on the principles of energy-saving design in building electrical systems,and actively explores the application of energy-saving technologies from different perspectives such as optimizing power supply and distribution system design,adopting high-efficiency energy-saving lighting equipment,applying renewable energy,promoting smart home technology,and improving the efficiency of building electrical equipment.

Research on the Optimization of Green Building Performance Based on BIM Technology

With the acceleration of urbanization,the construction industry has developed rapidly worldwide but has also brought serious environmental problems.Traditional architectural design methods often only focus on the function and beauty of the building while ignoring its impact on the environment.In addition,the lack of effective design and construction management methods also led to high resource and energy consumption.To overcome this challenge,the concept of green building came into being.Green buildings emphasize reducing the negative impact of buildings on the environment and improving resource utilization efficiency throughout the entire life cycle.BIM technology provides strong support for achieving this goal.Based on this,starting from the role of BIM technology in green building performance optimization,this article analyzes the optimization of green building performance solutions based on BIM technology in detail to promote the sustainable development of buildings.

Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

A performance comparison of multi-objective optimization algorithms for solving nearly-zero-energy-building design problems

Integrated building design is inherently a multi-objective optimization problem where two or more conflicting objectives must be minimized and/or maximized concurrently.Many multi-objective optimization algorithms have been developed;however few of them are tested in solving building design problems.This paper compares performance of seven commonly-used multi-objective evolutionary optimization algorithms in solving the design problem of a nearly zero energy building(n ZEB) where more than 1.610 solutions would be possible.The compared algorithms include a controlled non-dominated sorting genetic algorithm witha passive archive(p NSGA-II),a multi-objective particle swarm optimization(MOPSO),a two-phase optimization using the genetic algorithm(PR_GA),an elitist non-dominated sorting evolution strategy(ENSES),a multi-objective evolutionary algorithm based on the concept of epsilon dominance(ev MOGA),a multi-objective differential evolution algorithm(sp MODE-II),and a multi-objective dragonfly algorithm(MODA).Several criteria was used to compare performance of these algorithms.In most cases,the quality of the obtained solutions was improved when the number of generations was increased.The optimization results of running each algorithm20 times with gradually increasing number of evaluations indicated that the PR_GA algorithm had a high repeatability to explore a large area of the solution-space and achieved close-to-optimal solutions with a good diversity,followed by the p NSGA-II,ev MOGA and sp MODE-II.Uncompetitive results were achieved by the ENSES,MOPSO and MODA in most running cases.The study also found that 1400-1800 were minimum required number of evaluations to stabilize optimization results of the building energy model.

Integrated Building Envelope Design Process Combining Parametric Modelling and Multi-Objective Optimization

As an important element in sustainable building design, the building envelope has been witnessing a constant shift in the design approach. Integrating multi-objective optimization (MOO) into the building envelope design process is very promising, but not easy to realize in an actual project due to several factors, including the complexity of optimization model construction, lack of a dynamic-visualization capacity in the simulation tools and consideration of how to match the optimization with the actual design process. To overcome these difficulties, this study constructed an integrated building envelope design process (IBEDP) based on parametric modelling, which was implemented using Grasshopper platform and interfaces to control the simulation software and optimization algorithm. A railway station was selected as a case study for applying the proposed IBEDP, which also utilized a grid-based variable design approach to achieve flexible optimum fenestrations. To facilitate the stepwise design process, a novel strategy was proposed with a two-step optimization, which optimized various categories of variables separately. Compared with a one-step optimization, though the proposed strategy performed poorly in the diversity of solutions, the quantitative assessment of the qualities of Pareto-optimum solution sets illustrates that it is superior. © 2016, Tianjin University and Springer-Verlag Berlin Heidelberg.

Parameters Optimization and Energy-Saving of Highway Tunnel Backlighting with LED

In order to acquire the most energy-saving luminairedistribution-parameters(LDPs)of highway tunnel interior zone backlighting,the parameters optimization model(POM)of backlighting for tunnel interior zone was established.Yanlieshan tunnel of Jiujing highway was taken as an example for the optimization.The optimal LDPs of the backlighting system of the tunnel interior zone were obtained by the POM,a comparison between the optimization results and those of Yanlieshan tunnel’s actual lighting system was performed,which showed that the optimized backlighting system with LED lamps installed according to the optimized LDPs could save energy remarkablely even under full capacity lighting condition.Illuminance and illuminance uniformity of the tunnel road surface still met the lighting demands even the LED lamp’s luminance decreased by 30%.A backlighting simulation experiment with the optimized backlighting LDPs for Yanlieshan tunnel was accomplished in the software Dialux.The simulation results basically agreed with the optimization calculated results from the POM which proved the correctness of the backlighting POM.

Modeling and optimization of a multi-carrier renewable energy system for zero-energy consumption buildings

For the carbon-neutral,a multi-carrier renewable energy system(MRES),driven by the wind,solar and geothermal,was considered as an effective solution to mitigate CO2emissions and reduce energy usage in the building sector.A proper sizing method was essential for achieving the desired 100%renewable energy system of resources.This paper presented a bi-objective optimization formulation for sizing the MRES using a constrained genetic algorithm(GA)coupled with the loss of power supply probability(LPSP)method to achieve the minimal cost of the system and the reliability of the system to the load real time requirement.An optimization App has been developed in MATLAB environment to offer a user-friendly interface and output the optimized design parameters when given the load demand.A case study of a swimming pool building was used to demonstrate the process of the proposed design method.Compared to the conventional distributed energy system,the MRES is feasible with a lower annual total cost(ATC).Additionally,the ATC decreases as the power supply reliability of the renewable system decreases.There is a decrease of 24%of the annual total cost when the power supply probability is equal to 8%compared to the baseline case with 0%power supply probability.

Design of Low Carbon and Energy-saving New Rural Residential Buildings in Western Parts of Heilongjiang Province

It is researched that rural residential buildings in Heilongjieng consume high energy and the living environment is poor. The research aimed at designing low-carbon and energy-saving buildings in order to reduce energy consumption by applying energy storage. Besides, the research used composite solar panel, waste- based inorganic foam materials, and polystyrene board as construction materials and integrated energy collection, living environment and farming by energy storage system. It is notable that the research would reduce pollution on environment caused by residential buildings, which coincides with national economy development and en- ergy strategy, promoting construction material industry development, with high social and economic benefits.

Investment risk evaluation of existing building energy-saving renovation project for ESCO

The investment risk management of the existing building energy-saving renovation project for ESCO cannot be separated from the scientific risk measurement and evaluation. The investment risk assessment is the basis of investment decision and project implementation. Based on the content analysis and balance of evaluation principle of investment risk evaluation on the existing building energy-saving renovation project, we set up three levels of existing building energy-saving renovation project investment risk evaluation index system, use fuzzy comprehensive evaluation method to evaluate the quantitative process, get the scientific assessment of the investment risk of existing building energy-saving renovation project, and support the investment risk response strategy and control measures of existing building energy-saving renovation project for ESCO.

Assessing effectiveness of existing building energy-saving reconstruction policy adapted to market development

The market development and policy matching of existing building energy-saving retrofits determine the effectiveness of policies in promoting the operation of existing building energy-saving retrofit market.Based on the perspective of market development to evaluate the effectiveness of existing building energy-saving transformation policy,it is necessary to clarify the basic connotation of the effectiveness of existing building energy-saving transformation policy,systematically analyze the evaluation content,construct a multi-level evaluation index system,and select scientific and effective quantitative evaluation methods to implement a strict evaluation process.

Benefit evaluation on ESCO driving force for market development of energy-saving building

ESCO is the internal driving force for the development of the existing building energy-saving renovation market,and the driving effect of the ESCO market depends on scientific and effective comprehensive benefit evaluation.Based on analysis of the status qua at home and abroad,this paper reveals the necessity and value of research existing Building Energy Saving ESCO market development driving force effectiveness evaluation.The purpose of ESCO driving force benefit evaluation-oriented,establish the basic principles of evaluation index system of choice.Through the analysis of the evaluation content of the three dimensions of economic benefit,environmental benefit and social benefit,the comprehensive evaluation index system of the target level,criterion level and index level of the benefit evaluation of the existing building energy-saving renovation market development is constructed.AHP and fuzzy comprehensive evaluation of the combination,construct quantitative models of energy-saving drive ESCO market development role in the evaluation of the effectiveness of existing buildings.Based on the quantitative evaluation process of ESCO’s role in the development of our country’s existing building energysaving renovation market,it is necessary to scientifically understand the current status of ESCO’s driving role,and reveal the path to improve the efficiency of ESCO-driven development of the existing building’s energy-saving renovation market,in order to enhance the internal driving force of ESCO to promote.The existing building energy-saving renovation market is developing in a healthy and orderly manner.

Orthogonal experiment on reclaimed water treatment and economic optimization model in green building

The efficacy of superior drainage in green building treated by combinational technique of coagulation sedimentation and constructed wetland was launched. The results show that the regression equation relating to effluent BOD5,cubage load (Nv),temperature (t) and addition dosage (ρ) is BOD5=2.05Nv-0.41t-0.82ρ+38.9. The orthogonal experiment results of constructed wetland post-treatment show that the regression equation relating to effluent BOD5,cubage load (NA),and temperature (t) is BOD5=1 190NA-0.32t+12.2. Based on the two orthogonal regression equations,combined of green building municipal gray reclaimed water quantity requirements in different seasons,a technology investment on economic optimization model of combinational technique was established. The results offer technological support for reclaimed water treatment,which regards superior drainage as the source and is purified by combinational technique of coagulation sedimentation and constructed wetland. According to the model,the reasonable scale of reclaimed water treatment systems can be determined,the treatment efficacy can be well predicted,and both the design and operating can be effectively guided.

Energy-saving potential analysis for teaching building with intermittent heating system in university of Tianjin

An energy consumption analysis based on the heating characteristic of a building with central heat exchanger in a university of Tianjin was done,and the feasibility of intermittent heating with variable speed pumps was discussed. By comparing various methods of energy consumption analysis,a modified Bin method based on the weather data in Tianjin was adopted. The heat consumption of the buildings under intermittent heating mode was calculated and compared with continuous heating mode,the result shows that intermittent heating can reduce energy consumption for 1 941 759 kW·h,save standard coal for 341 t,and reduce pump power consumption for 72 679 kW·h annually. Intermittent operation by means of varying the pump frequency not only leads to savings in fuel consumption and reduction in pollutant emissions,but also reduces operating costs significantly and it is an ideal energy-saving method. By analyzing the results,the recommendations of heating operation regulation and the transformation of pipe network were proposed separately to different kinds of buildings in colleges,such as laboratory building,teaching building.

Development and Application of Decision Support Model for the Performance Optimization of Office Buildings Based on Grasshopper

With the expansion of the office building area,the energy consumption of office buildings is growing.High⁃performance building design contributes to energy saving and the development of green buildings.However,there is a lack of high⁃performance building tools and the workflow is often time⁃consuming.The building performance simulation,multiple objective optimizations,and the decision support model are the new approaches of high⁃performance building design.This paper proposes a newly developed decision support model,a high⁃performance building decision model named HPBuildingDSM,which integrates the building performance simulation,building performance multiple objective optimizations,building performance sampling,and parameter sensitivity analysis to design high⁃performance office buildings.In this research,the HPBuildingDSM was operated to search for the desirable office building design results with low⁃energy and high⁃quality daylighting performances.The simulated results had better daylighting performance and lower energy consumption,whose UDI100-2000 was 37.94%and annual energy consumption performance was 76.28 kWh/(m2·a),indicating a better building performance than the optimized results in the previous case study.

GPPre:A Python⁃Based Tool in Grasshopper for Office Building Performance Optimization

With the development of the economic and low⁃carbon society,high⁃performance building(HPB)design plays an increasingly important role in the architectural area.The performance of buildings usually includes the building energy consumption,building interior natural daylighting,building surface solar radiation,and so on.Building performance simulation(BPS)and multiple objective optimizations(MOO)are becoming the main methods for obtaining a high performance building in the design process.Correspondingly,the BPS and MOO are based on the parametric tools,like Grasshopper and Dynamo.However,these tools are lacking the data analysis module for designers to select the high⁃performance building more conveniently.This paper proposes a toolkit“GPPre”developed based on the Grasshopper platform and Python language.At the end of this paper,a case study was conducted to verify the function of GPPre,which shows that the combination of the sensitivity analysis(SA)and MOO module in the GPPre could aid architects to design the buildings with better performance.