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.

Photovoltaic energy balance estimation based on the building integration level

The photovoltaic module building integration level affects the module temperature and,consequently,its output power.In this work,a methodology has been proposed to estimate the influence of the level of architectural photovoltaic integration on the photovoltaic energy balance with natural ventilation or with forced cooling systems.The developed methodology is applied for five photovoltaic module technologies(m⁃Si,p⁃Si,a⁃Si,CdTe,and CIGS)on four characteristic locations(Athens,Davos,Stockholm,and Würzburg).To this end,a photovoltaic module thermal radiation parameter,PVj,is introduced in the characterization of the PV module technology,rendering the correlations suitable for building⁃integrated photovoltaic(BIPV)applications,with natural ventilation or with forced cooling systems.The results show that PVj has a significant influence on the energy balances,according to the architectural photovoltaic integration and climatic conditions.Keywords:Photovoltaic cooling;BIPV;Photovoltaic;Ventilation;Photovoltaic integration level in building【OA】(2)Graph⁃Based methodology for Multi⁃Scale generation of energy analysis models from IFC,by Asier Mediavilla,Peru Elguezabal,Natalia Lasarte,Article 112795 Abstract:Process digitalisation and automation is unstoppable in all industries,including construction.However,its widespread adoption,even for non⁃experts,demands easy⁃to⁃use tools that reduce technical requirements.BIM to BEM(Building Energy Models)workflows are a clear example,where ad⁃hoc prepared models are needed.This paper describes a methodology,based on graph techniques,to automate it by highly reducing the input BIM requirements found in similar approaches,being applicable to almost any IFC.This is especially relevant in retrofitting,where reality capture tools(e.g.,3D laser scanning,object recognition in drawings)are prone to create geometry clashes and other inconsistencies,posing higher challenges for automation.Another innovation presented is its multi⁃scale nature,efficiently addressing the surroundings impact in the energy model.The application to selected test cases has been successful and further tests are ongoing,considering a higher variety of BIM models in relation to tools and techniques used and model sizes.

Energy-Efficient Approaches for a Machine Tool Building in a University through Field Measurement and Energy Modelling

The heating,ventilating,and air conditioning(HVAC)system consumes nearly 50%of the building’s energy,especially in Taiwan with a hot and humid climate.Due to the challenges in obtaining energy sources and the negative impacts of excessive energy use on the environment,it is essential to employ an energy-efficient HVAC system.This study conducted the machine tools building in a university.The field measurement was carried out,and the data were used to conduct energymodelling with EnergyPlus(EP)in order to discover some improvements in energy-efficient design.The validation between fieldmeasurement and energymodelling was performed,and the error rate was less than 10%.The following strategies were proposed in this study based on several energy-efficient approaches,including room temperature settings,chilled water supply temperature settings,chiller coefficient of performance(COP),shading,and building location.Energy-efficient approaches have been evaluated and could reduce energy consumption annually.The results reveal that the proposed energy-efficient approaches of room temperature settings(3.8%),chilled water supply temperature settings(2.1%),chiller COP(5.9%),using shading(9.1%),and building location(3.0%),respectively,could reduce energy consumption.The analysis discovered that using a well-performing HVAC system and building shading were effective in lowering the amount of energy used,and the energy modelling method could be an effective and satisfactory tool in determining potential energy savings.

Analysis and forecast of residential building energy consumption in Chongqing on carbon emissions

Carbon emissions mainly result from energy consumption. Carbon emissions inevitably will increase to some extent with economic expansion and rising energy consumption. We introduce a gray theory of quantitative analysis of the energy consumption of residential buildings in Chongqing,China,on the impact of carbon emission factors. Three impacts are analyzed,namely per capita residential housing area,domestic water consumption and the rate of air conditioner ownership per 100 urban households. The gray prediction model established using the Chongqing carbon emission-residential building energy consumption forecast model is sufficiently accurate to achieve a measure of feasibility and applicability.

Climate change and building ageing impact on building energy performance and mitigation measures application:A case study in Turin, northern Italy

This study uses a building energy performance simulation to investigate the impact of predicted climate warming and the additional issue of building ageing on the energy performance for a library in Turin,Italy.The climate and ageing factors were modelled individually and then integrated together for several decades.Results from the climate-only simulation showed a decrease in thebuilding heating energy usage which outweighed the increase in the on-site cooling energy demand occurring in a warming scenario.The study revealed a high sensitivity of energy performance to building ageing,in particular due to HVAC(Heating,Ventilation and Air Conditioning) equipment efficiency degradation.Building ageing was seen to negatively affect the energy performance as it induced a further increase of the cooling energy usage in a warming climate,while it also counteracted the reduction of the heating energy usage resulting from warming.Simulations on the combination of mitigation techniques showed a number of potentially retrofit measures that would be beneficial for buildings to avoid an increase in the cooling energy usage due to climate warming.The combination of these retrofit techniques showed a potential decrease of 87.3% in the final cooling energy usage for the considered building.

Building Information Modeling for Environmental Impact Assessment in Early Design Phases: A Literature Review

The building sector is the largest consumer of energy in industrial countries. Saving energy in new buildings or building renovations can thus lead to significant global environmental impacts. In this endeavor, building information modeling (BIM) and building energy modeling (BEM) are two important tools to make the transition to net-zero energy buildings (NZEB). So far, little attention has been devoted, in the literature, to discuss the connection between BIM, BEM, and Life-cycle assessment (LCA), which is the main topic of this article. A literature review of 157 journal articles and conference proceedings published between 1990 and 2020 is presented. This review outlines knowledge gaps concerning BIM, BEM, and environmental impact assessment. It suggests that defining the process with the right technology (at the right time) would result in a more integrated design process (IDP) and bridge current gaps. The most efficient way to improve process and technology is related to the competences of the architects, engineers and constructors (AEC). The review also indicates that the IDP in the early design phases (EDP) is in need of improvement for architects and engineers, where a better connection between design phases, specific levels of development (LOD) and BIM tools is needed. Competences, process and technology are the three main themes addressed in the review. Their relation to design phases and LOD is discussed. The aim is to propose possible solutions to the current hinders in BIM-to-BEM (BIM2BEM) and BIM-for-LCA (BIM4LCA) integration.

Simulation Technology of Environmental Impacts by Zero-energy Residential Buildings Based on Emergy Analysis Method

This paper presents a simulation technology of environmental impact for the building. By emergy analysis method,emergy costs of building( or construction engineering) can be calculated in the life cycle. It includes the engineering cost, environmental cost and social cost of building. Through integrating GIS technology with multi-agent technology,life cycle substance and energy metabolism of building( construction engineering) can be simulated and their environmental influence can be dynamically displayed. Based on the case study of entries works‘Sunny Inside'by Xiamen University in 2013 China International Solar Decathlon Competition,we discovered the changing pattern of surrounding environmental impact from waste streams of the zero-energy building and ordinary construction. The simulation results verified and showed the Odum principles of maximum power. This paper provides a new research perspective and integration approach for the environmental impact assessment in building and construction engineering. The result will help decision-making in design and construction engineering scheme.

Modular energy cost optimization for buildings with integrated microgrid

Buildings are becoming suitable for application of sophisticated energy management approaches to increase their energy efficiency and possibly turn them into active energy market participants.The paper proposes a modular coordination mechanism between building zones comfort control and building microgrid energy flows control based on model predictive control. The approach opens possibilities to modularly coordinate technologically heterogeneous building subsystems for economically-optimal operation under user comfort constraints. The imposed modularity is based on a simple interface for exchanging building consumption and microgrid energyprice profiles. This is a key element for technology separation,replication and up-scaling towards the levels of smart grids and smart cities where buildings play active roles in energy management. The proposed coordination mechanism is presented in a comprehensive realistic case study of maintaining comfort in an office building with integrated microgrid. The approach stands out with significant performance improvements compared to various non-coordinated predictive control schemes and baseline controllers. Results give detailed information about yearly cost-effectiveness of the considered configurations,which are suitable for deployment as short-and long-term zero-energy building investments.

A hybrid agent⁃based machine learning method for human⁃centred energy consumption prediction

Occupant behaviour has significant impacts on the performance of machine learning algorithms when predicting building energy consumption.Due to a variety of reasons(e.g.,underperforming building energy management systems or restrictions due to privacy policies),the availability of occupational data has long been an obstacle that hinders the performance of machine learning algorithms in predicting building energy consumption.Therefore,this study proposed an agent⁃based machine learning model whereby agent⁃based modelling was employed to generate simulated occupational data as input features for machine learning algorithms for building energy consumption prediction.Boruta feature selection was also introduced in this study to select all relevant features.The results indicated that the performances of machine learning algorithms in predicting building energy consumption were significantly improved when using simulated occupational data,with even greater improvements after conducting Boruta feature selection.

安徽省居住建筑终端能耗及碳排放达峰研究

以安徽省既有居住建筑运行阶段为研究对象,采用能源平衡表法、LEAP模型、碳排放因子法和STIRPAT模型等工具和方法,预测碳排放峰值及影响因素,并提出技术路径和政策建议。研究结果表明:安徽省居住建筑实现碳达峰的最佳实施路径应采取蓝图情景。该情景下居住建筑运行阶段碳排放2025年达到峰值3429.29万t, 2060年回落至918.69万t。在影响因素方面,常住人口是居住建筑碳排放的主导因素,大小为-2.646;能源结构也对居住建筑碳排放产生了不小的影响,大小为-1.465,这得益于安徽省建筑消费能源结构的持续优化。因此,开展建筑电气化、发展可再生能源、限制一次能源的使用、优化能源结构至关重要。

燃料电池增程式动力系统能量管理策略研究

以某款纯电动客车为研究对象,以增加车辆续驶里程为目的,提出燃料电池增程式混合动力系统结构,根据性能指标对动力系统各部件进行匹配计算和选型.提出了开关/功率跟随式能量管理策略,基于Cruise和Simulink分别搭建了整车动力系统模型和燃料电池及能量管理策略模型并进行联合仿真.结果表明,采用文中提出的能量管理策略车辆经济性相对于开关式和能量跟随式两种控制策略分别提高62%和31%,续驶里程相对于该两种控制策略分别提高41%和18%.

智慧能源系统与建筑业协同交易的实现机制研究

随着可再生能源的大力开发利用,智慧能源系统与建筑业协同交易将在建筑业碳减排中发挥日益重要的作用,进而成为推进“双碳”战略目标的重要途径。文章在文献研究基础上,从“双碳”目标视角,提出智慧能源系统与建筑业协同交易的具体模式及其低碳贡献,并解析出对这一协同交易的影响因素。依据SCP理论系统构建外部环境、投资决策、价格因素、智慧能源系统特性、建筑业主差异化生产能力、建筑业主的竞争行为与智慧能源与建筑业协同交易的理论模型,建立智慧能源与建筑业协同交易的实现机制。

民居建筑节能评价模型研究——以胶东民居为例

本文基于对居住需求与民居设计的关注,以胶东民居建筑为对象,从建筑设计因素与居住者需求两维度创建综合节能评价体系,构建节能评价模型,借助招远市段家洼村某民居进行评价,分析民居节能设计的合理性对室内温度、建造成本造成的影响,发现不利于节能的设计因素与未满足居住者需求的消极因素,为民居的节能设计和居民福祉的提升提供参考。

蒸发冷却空调的热舒适评价方法综述及展望

在绿色节能的新形势下,蒸发冷却空调相比于传统空调更具有节能减排的优势。目前关于蒸发冷却空调的研究仍集中于系统性能和能效上,而忽略了其所营造的室内环境的热舒适情况。准确预测蒸发冷却空调的热舒适对其发展同样起着不可忽视的作用。文章介绍了国内外蒸发冷却空调的热舒适研究现状并综述了其采用的热舒适评价方法,分析了蒸发冷却空调采用适应性热舒适评价的可能性和必要性。针对蒸发冷却空调所营造的室内热环境特点,提出了蒸发冷却系统的适应性热舒适模型框架。

Evaluation of building energy demand forecast models using multi-attribute decision making approach

With the existence of several conventional and advanced building thermal energy demand forecast models to improve the energy efficiency of buildings,it is hard to find an appropriate,convenient,and efficient model.Evaluations based on statistical indexes(MAE,RMSE,MAPE,etc.)that characterize the accuracy of the forecasts do not help in the identification of the efficient building thermal energy demand forecast tool since they do not reflect the efforts entailed in implementation of the forecast model,i.e.,data collection to production/use phase.Hence,this work presents a Gini Index based Measurement of Alternatives and Ranking according to COmpromise Solution(GI-MARCOS),a hybrid Multi Attribute Decision Making(MADM)approach for the identification of the most efficient building energy demand forecast tool.GI-MARCOS employs(i)GI based objective weight method:assigns meaningful objective weights to the attributes in four phases(1:pre-processing,2:implementation,3:post-processing,and 4:use phase)thereby avoiding unnecessary biases in the expert’s opinion on weights and applicable to domains where there is a lack of domain expertise,and(ii)MARCOS:provides a robust and reliable ranking of alternatives in a dynamic environment.A case study with three alternatives evaluated over three to six attributes in four phases of implementation(pre-processing,implementation,post-processing and use)reveals that the use of GI-MARCOS improved the accuracy of alternatives MLR and BM by 6%and 13%,respectively.Moreover,additional validations state that(i)MLR performs best in Phase 1 and 2,while ANN performs best in Phase 3 and 4 with BM providing a mediocre performance in all four phases,(ii)sensitivity analysis:provides robust ranking with interchange of weights across phases and attributes,and(iii)rank correlation:ranks produce by GI-MARCOS has a high correlation with GRA(0.999),COPRAS(0.9786),and ARAS(0.9775).

基于建筑碳排放模型的管理体系研究

为了有效控制单体建筑的节能减排,增强校园生态可持续发展动力,以中国地质大学(北京)为例,采用聚类分析、主成分分析和因子分析的方法,对建筑单体的边界条件、水电气等的碳排放规律、特点和影响因素进行分析,建立多元统计模型。结果显示:模型可以获得单体建筑的碳排放,可用于衡量不同区域和不同建筑的碳排放规模。