Integrating Virtual Reality and Energy Analysis with BIM to Optimize Window-to-Wall Ratio and Building’s Orientation for Age-in-Place Design at the Conceptual Stage

This study unfolds an innovative approach aiming to address the critical role of building design in global energy consumption, focusing on optimizing the Window-to-Wall Ratio (WWR), since buildings account for approximately 30% of total energy consumed worldwide. The greatest contributors to energy expenditure in buildings are internal artificial lighting and heating and cooling systems. The WWR, determined by the proportion of the building’s glazed area to its wall area, is a significant factor influencing energy efficiency and minimizing energy load. This study introduces the development of a semi-automated computer model designed to offer a real-time, interactive simulation environment, fostering improving communication and engagement between designers and owners. The said model serves to optimize both the WWR and building orientation to align with occupants’ needs and expectations, subsequently reducing annual energy consumption and enhancing the overall building energy performance. The integrated model incorporates Building Information Modeling (BIM), Virtual Reality (VR), and Energy Analysis tools deployed at the conceptual design stage, allowing for the amalgamation of owners’ inputs in the design process and facilitating the creation of more realistic and effective design strategies.

Composition Modeling and Equivalence of an Integrated Power Generation System of Wind, Photovoltaic and Energy Storage Unit

利用间接组合建模的方法,在建立典型的双馈风机、光伏发电单元和储能单元的装置级机电暂态模型基础上,采用等值方法建立三者电站级的机电暂态模型,最终通过组合建模得到了风光储联合发电系统的机电暂态模型。在大型电力系统分析软件包的PSD-BPA暂态稳定程序中实现了风光储联合发电系统的仿真功能,通过典型算例和张北＂国家风光储输示范工程＂的仿真分析验证了模型的正确性,为风光储联合发电系统的并网研究提供了分析手段。

Prospects of key technologies of integrated energy systems for rural electrification in China

Owing to increasing environmental concerns and resource scarcity, integrated energy system shave become widely used in communities. Rural energy systems, as one of the important links of the energy network in China, suffer from low energy efficiency and weak infrastructure. Therefore, it is particularly important to increase the proportion of electricity consumption and build an integrated energy system for rural electrification in China(IESREIC) with a rural distribution network as the core, in line with national conditions. In this study, by analyzing the Chinese regional differences and natural resource endowments, the development characteristics of the IESREIC are summarized. Then, according to the existing rural energy problems, key technologies are proposed for the IESREIC, such as those for planning and operation, value sharing, infrastructure, and a management and control platform. Finally, IESREIC demonstration projects and business models are introduced for agricultural production, rural industrial systems, and rural life. The purpose is to propose research concepts for the IESREIC, provide suggestions for the development of rural energy, and provide a reference for the construction of rural energy systems in countries with characteristics similar to those of China.

Functional Integrals and Free Energy in sine-Gordon-Thirring Model with Impurity Coupling

The free energy at low temperature in 1D sine-Gordon-Thirring model with impurity coupling is studied by means of functional integrals method. For massive free sine-Gordon-Thirring model, free energy is obtained from perturbation expansion of functional determinant. Moreover, the free energy of massive model is calculated by use of an auxiliary Bose field method.

A unified model for diagnosing energy usage abnormalities in regional integrated energy service systems

An integrated energy service company in an industrial park or commercial building is responsible for managing all energy sources in their local region, including electricity, water, gas, heating, and cooling. To reduce energy wastage and increase energy utilization, it is necessary to perform efficiency analyses and diagnoses on integrated energy systems(IESs). However, the integrated energy data necessary for energy efficiency analyses and diagnoses come from a wide variety of instruments, each of which uses different transmission protocols and data formats. This makes it challenging to handle energy-flow data in a unified manner. Thus, we have constructed a unified model for diagnosing energy usage abnormalities in IESs. Using this model, the data are divided into working days and non-working days, and benchmark values are calculated after the data have been weighted to enable unified analysis of several types of energy data. The energy-flow data may then be observed, managed, and compared in all aspects to monitor sudden changes in energy usage and energy wastage. The abnormal data identified and selected by the unified model are then subjected to big-data analysis using technical management tools, enabling the detection of user problems such as abnormalities pertaining to acquisition device, metering, and energy usage. This model facilitates accurate metering of energy data and improves energy efficiency. The study has significant implications in terms of fulfilling the energy saving.

Functional Integrals and Excitation Energy in Three-Band Hubbard Model

The normal and anomalous Green＇s functions of antiferromagnetie state in three-band Hubbard model are studied by using functional integrals and temperature Green＇s function method. The equations of energy spectrum are derived. In addition, excitation energy of Fermi fields are calculated under long wave approximation.

Optimal dispatching method for integrated energy system based on robust economic model predictive control considering source-load power interval prediction

Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.

Impact of interconnections and renewable energy integration on the Philippine-Sabah Power Grid systems

This study presents a comprehensive impact analysis of the rotor angle stability of a proposed international connection between the Philippines and Sabah,Malaysia,as part of the Association of Southeast Asian Nations(ASEAN)Power Grid.This study focuses on modeling and evaluating the dynamic performance of the interconnected system,considering the high penetration of renewable sources.Power flow,small signal stability,and transient stability analyses were conducted to assess the ability of the proposed linked power system models to withstand small and large disturbances,utilizing the Power Systems Analysis Toolbox(PSAT)software in MATLAB.All components used in the model are documented in the PSAT library.Currently,there is a lack of publicly available studies regarding the implementation of this specific system.Additionally,the study investigates the behavior of a system with a high penetration of renewable energy sources.Based on the findings,this study concludes that a system is generally stable when interconnection is realized,given its appropriate location and dynamic component parameters.Furthermore,the critical eigenvalues of the system also exhibited improvement as the renewable energy sources were augmented.

Component modeling and updating method of integrated energy systems based on knowledge distillation

Amid the backdrop of carbon neutrality, traditional energy production is transitioning towards integrated energy systems (IES), where model-based scheduling is key in scenarios with multiple uncertainties on both supply and demand sides. The development of artificial intelligence algorithms, has resolved issues related to model accuracy. However, under conditions of high proportion renewable energy integration, component load adjustments require increased flexibility, so the mathematical model of the component must adapt to constantly changing operating conditions. Therefore, the identification of operating condition changes and rapid model updating are pressing issues. This study proposes a modeling and updating method for IES components based on knowledge distillation. The core of this modeling method is the light weighting of the model, which is achieved through a knowledge distillation method, using a teacher-student mode to compress complex neural network models. The triggering of model updates is achieved through principal component analysis. The study also analyzes the impact of model errors caused by delayed model updates on the overall scheduling of IES. Case studies are conducted on critical components in IES, including coal-fired boilers and turbines. The results show that the time consumption for model updating is reduced by 76.67 % using the proposed method. Under changing conditions, compared with two traditional models, the average deviation of this method is reduced by 12.61 % and 3.49 %, respectively, thereby improving the model's adaptability. The necessity of updating the component model is further analyzed, as a 1.00 % mean squared error in the component model may lead to a power deviation of 0.075 MW. This method provides real-time, adaptable support for IES data modeling and updates.

A Multi-slack Bus Model for Bi-directional Energy Flow Analysis of Integrated Power-gas Systems

The bi-directional energy conversion components such as gas-fired generators(GfG)and power-to-gas(P2G)have enhanced the interactions between power and gas systems.This paper focuses on the steady-state energy flow analysis of an integrated power-gas system(IPGS)with bi-directional energy conversion components.Considering the shortcomings of adjusting active power balance only by single GfG unit and the capacity limitation of slack bus,a multi-slack bus(MSB)model is proposed for integrated power-gas systems,by combining the advantages of bi-directional energy conversion components in adjusting active power.The components are modeled as participating units through iterative participation factors solved by the power sensitivity method,which embeds the effect of system conditions.On this basis,the impact of the mixed problem of multi-type gas supply sources(such as hydrogen and methane generated by P2G)on integrated system is considered,and the gas characteristics-specific gravity(SG)and gross calorific value(GCV)are modeled as state variables to obtain a more accurate operational results.Finally,a bi-directional energy flow solver with iterative SG,GCV and participation factors is developed to assess the steady-state equilibrium point of IPGS based on Newton-Raphson method.The applicability of proposed methodology is demonstrated by analyzing an integrated IEEE 14-bus power system and a Belgian 20-node gas system.

Modeling and Analysis of Internal Heat Integrated Distillation Columns

A generalized steady-state model is being developed for an internal heat integrated distillation column (IHIDiC). A procedure incorporating the Newton-Raphson method is devised for solving the model equations. Separation of an ethanol-water binary mixture is simulated and analyzed with the model. Two pinch points are found within the process, making the separation extremely difficult and expensive. Two sharp fronts in the temperature and the composition profiles are being observed. With the introduction of heat integration, satisfactory separation may be obtained in a limited number of stages with lower reflux ratios. Increasing the pressure difference between the rectifying and the stripping sections, however, would bring about a reduced relative volatility between the two components involved, creating adverse separation performances. It is obvious that optimization of the IHIDiC is of prime importance.

Load-forecasting method for IES based on LSTM and dynamic similar days with multi-features

To fully exploit the rich characteristic variation laws of an integrated energy system(IES)and further improve the short-term load-forecasting accuracy,a load-forecasting method is proposed for an IES based on LSTM and dynamic similar days with multi-features.Feature expansion was performed to construct a comprehensive load day covering the load and meteorological information with coarse and fine time granularity,far and near time periods.The Gaussian mixture model(GMM)was used to divide the scene of the comprehensive load day,and gray correlation analysis was used to match the scene with the coarse time granularity characteristics of the day to be forecasted.Five typical days with the highest correlation with the day to be predicted in the scene were selected to construct a“dynamic similar day”by weighting.The key features of adjacent days and dynamic similar days were used to forecast multi-loads with fine time granularity using LSTM.Comparing the static features as input and the selection method of similar days based on non-extended single features,the effectiveness of the proposed prediction method was verified.

Time Series Analysis of Energy Intensity, Value Added Tax and Corporate Income Tax: A Case Study of the Non-Ferrous Metal Industry, Jiangxi Province, China

Unprecedented industrialization and urbanization have led to China’s poor energy efficiency. In response, the Chinese government has set goals to reduce energy consumption that may include implementing new tax policies. In this paper, we investigate the relationship between energy intensity, an indicator that measures the efficiency of energy consumption, and two sources of government revenue in China (i.e., value-added tax (VAT) and corporate income tax). As a case study, we developed a Granger co-integration model to analyze the dynamic relationship of energy intensity, VAT and corporate income tax in the non-ferrous metal industry, Jiangxi Province, China, between 1996 and 2010. Augmented Dickey-Fuller tests were used to validate the model. In our time series analyses, we found when controlling for corporate income tax, a one log unit increase of VAT resulted in a decrease of 1.17 log units of energy intensity. However, when controlling for VAT, a one log unit increase of corporate income tax resulted in an increase of 0.34 log units of energy intensity. Understanding the relationship between energy intensity and taxation in industries that consume high volumes of energy can greatly enhance China’s goal to reduce energy consumption. We believe our findings add to this on-going discussion.

多园区综合能源系统接入主动配电网双层优化调度研究

随着园区综合能源系统的不断发展与普及,其与上级大电网并网实现交互已成为大势所趋。文中构建了通过联络线相耦合的多园区综合能源系统接入主动配电网的双层优化调度模型。在主动配电网层面,以最小运行成本为目标,充分考虑了联络线功率、分布式电源、储能设备、柔性负荷、电动汽车等可调度资源;在园区层面,以多园区总运行成本最小为目标,考虑了相互联结的多类型园区的并网情况。利用目标级联法对双层模型进行求解。通过算例验证,文中所构建模型具有良好的经济特性与削峰填谷效果,充分证明了文中所提模型的经济性与有效性。

基于组合赋权与灰云模型的综合能源系统需求响应效益评价

考虑到当前综合能源系统研究缺乏完善的需求响应量化评估方案,难以在优化运行层面综合评估需求响应效益这一问题,提出了一种基于改进AHP群决策—CRITIC组合赋权与灰云模型的综合能源系统需求响应效益评价方法。首先,从综合能效性、社会经济性和需求侧互动性三个维度构建了需求响应效益评价指标体系。其次,采用一致性和权重拟合性更优的指数标度法构造判断矩阵,降低赋值误差,并通过AHP群决策法确定主观权重,从而削弱主观极值偏差对权重的影响;在由CRITIC法确定客观权重后,基于最小欧氏距离建立组合权重模型,并通过非线性规划求取最优组合权重;针对评价等级信息的模糊性与隶属等级的随机性,采用正态灰云白化权模型确定指标分类等级与场景评分。最后,以北方某综合能源系统为例,根据用户参与需求响应方式设置了4种运行场景,分析了不同需求响应对系统运行的影响与作用,算例结果表明所提指标体系与评价方法科学有效。

综合能源系统下虚拟储能建模方法与应用场景研究综述及展望

为了促进多能耦合互补和实现可再生能源就地消纳,综合能源系统已成为多领域的研究热点。考虑到能源设备及网络的多样性、复杂性以及多种能源时间尺度的差异性,根据能量平衡原理,对系统内具有可调特性的源、网、荷进行储能化建模,并构成虚拟储能系统参与到综合能源系统的优化调度中。为了准确把握虚拟储能的研究重点,首先介绍了虚拟储能的定义、逻辑架构和技术内涵;其次针对综合能源系统源、网、荷端设备或网络,总结和归纳了4种虚拟储能建模方法和特性指标;然后重点分析了虚拟储能在4种典型场景的具体应用;最后展望了虚拟储能未来的发展方向。

基于多能流耦合规律的综合能源系统潮流及流分析

从能量流和流两个角度分析综合能源系统的多能流耦合规律,建立系统能流稳态潮流模型和流模型,根据模型特点研究系统潮流和流分布计算方法,以算例验证计算方法的可行性并分析计算数据,验证流机理模型相比于黑箱模型在局部分析方面的优越性。以算例数据为例,分析其潮流及流分布特点,结果表明:算例系统中能源转换环节的地方损最大,为系统薄弱环节,值得着重改进;同时电、热网络也有部分管段损较大,优化局部网络时也应纳入考虑。

基于Modelica与Julia的气-热-电综合能源系统动态特性分析

综合能源系统实现了多种能流的综合管控与协同优化,是未来社会能源系统发展的必然趋势,研究综合能源系统动态特性对综合能源系统科学管理具有重要意义。目前,针对综合能源系统建模仿真的研究已取得很多有价值的成果,但对综合能源系统网络动态传输过程的模拟还存在诸多不足,尤其是特殊流动现象还无法得到很好的模拟。因此,以气—热—电综合能源系统为研究对象,采用模块化的建模方法,基于Modelica和Julia语言建立充分考虑网络动态特性的电—气—热综合能源系统模型,并对输气管道的快瞬变流、慢瞬变流特性以及传输过程的“水锤”“热惯性”等现象进行模拟验证。最后,对综合能源系统负荷变化时不同能流之间的动态响应情况进行仿真分析。结果表明,该方法对描述综合能源系统的网络动态特性以及不同能流之间的动态响应均有良好效果,研究结果可支撑综合能源系统运行优化及多主体在线能流分析等研究,为提高综合能源系统的科学管理能力提供依据。

基于区间理论的油田综合能源系统优化规划

针对油田的能源结构和用能负荷的特征,构建了油田综合能源系统架构;考虑可再生能源出力的不确定性和油田多元负荷用能的随机性,建立了光伏、光热出力的区间模型,热负荷区间模型和基于价格型响应的电负荷区间模型;通过分析设备投资成本的时间价值和区域碳中和途径,建立一种计及源荷不确定性的综合能源系统规划模型,并结合仿射算法和区间序关系,将不确定性优化问题转化为确定性的多目标优化问题进行求解。算例分析表明,油田综合能源系统架构符合油田能源禀赋和负荷实际耦合情况,设备配置方案投资回收年限短,不确定性权重系数越高,投资越大,年净收益区间越大,结果验证了规划方法的有效性。与传统鲁棒凸规划优化方法相比,所提方法为决策者提供了满足区间约束的解集,避免了规划方案的保守性。

西南油气田天然气与新能源深度融合的路径探索

中国石油西南油气田公司(以下简称西南油气田)正全力推进国家天然气(页岩气)千亿立方米级产能基地建设,面临绿色低碳转型发展和实现“双碳”目标的双重挑战,迫切需要推动天然气与新能源深度融合发展。为此,分析了融合发展的资源基础,梳理总结了过往融合发展的思路与探索历程,并明晰了当前面临的3方面挑战:内部资源禀赋差、外部资源获取难度大;新技术新装备不够成熟、经济效益偏差;新业务资源认识不系统、利用不充分。在此基础上,提出了天然气与新能源深度融合的路径思路:“区内有序、区外聚焦”发展风光地热业务;大力发展余压发电、伴生资源、CCUS、氢能等特色业务;探索发展地下空间利用和生物天然气等新赛道业务。最后,提出4方面建议:立足当前、着眼未来,统筹考虑经济性;考虑业务成长性及技术迭代需要,有序推进产业规模由小及大;培育市场竞争意识,深化合作交流,共同推动产业发展;创新机制,探索通过多种机制、模式助力产业发展。