Generation of typical meteorological years using genetic algorithm for different energy systems

Computer simulation plays an important role in investigating the thermal/energy performance of buildings and energy systems. In order to reduce the computational time and provide a consistent form of weather data, simulation run with multi-year weather files is generally avoided. In contrast, representative weather data is widely adopted. For developing typical meteorological year (TMY) weather files, Sandia method is one of the commonly adopted approaches. During the generation of TMY, different weighting factors are assigned to some key climatic indices. Currently, the values of weighting factors mainly depend on the researchers' judgement. As these weighting factors can express the relative importance of impact of a particular climatic index on the thermal/energy performance of an energy system, computer simulation using different TMYs may lead to different conclusions. Therefore, it is inappropriate to apply one single TMY for all energy systems. In this study, a novel TMY weather file generator has been developed to link up an optimization algorithm and an energy simulation program. Through four application examples (one air-conditioned building and three renewable energy systems), this weather file generator demonstrated its capability to search optimal/near optimal combinations of weighting factors for generating appropriate TMY for computer simulations of different energy systems.     

Design of isolated renewable hybrid power systems

Isolated electrical power generating units can be used as an economically viable alternative to electrify remote villages where grid extension is not feasible. One of the options for building isolated power systems is by hybridizing renewable power sources like wind, solar, micro-hydro, etc. along with appropriate energy storage. A method to optimally size and to evaluate the cost of energy produced by a renewable hybrid system is proposed in this paper. The proposed method, which is based on the design space approach, can be used to determine the conditions for which hybridization of the system is cost effective. The simple and novel methodology, proposed in this paper, is based on the principles of process integration. It finds the minimum battery capacity when the availability and ratings of various renewable resources as well as load demand are known. The battery sizing methodology is used to determine the sizing curve and thereby the feasible design space for the entire system. Chance constrained programming approach is used to account for the stochastic nature of the renewable energy resources and to arrive at the design space. The optimal system configuration in the entire design space is selected based on the lowest cost of energy, subject to a specified reliability criterion. The effects of variation of the specified system reliability and the coefficient of correlation between renewable sources on the design space, as well as the optimum configuration are also studied in this paper. The proposed method is demonstrated by designing an isolated power system for an Indian village utilizing wind-solar photovoltaic-battery system.     

A review of the economical and optimum thermal insulation thickness for building applications

Energy conservation is an increasingly important issue for the residential sector. Therefore, attention towards the thermal performance of building materials, particularly thermal insulation systems for buildings, has grown in recent years. In this study, a literature review on determining the optimum thickness of the thermal insulation material in a building envelope and its effect on energy consumption was carried out. The results, the optimization procedures and the economic analysis methods used in the studies were presented comparatively. Additionally, a practical application on optimizing the insulation thickness was performed, and the effective parameters on the optimum value were investigated.     

Jaya algorithm-based energy management system for battery- and ultracapacitor-powered ultralight electric vehicle

To improve the driving performance of the electric vehicles, batteries or ultracapacitors (UCs) are frequently preferred in the energizing systems. In hybrid structures with multiple supply sources, an energy management system (EMS) is needed to improve the system efficiency, and to provide the optimum power sharing between a battery and a UC. The purpose of this study is to investigate the effectiveness of the Jaya optimization method for the urban use of the EMS of an ultralight electric vehicle powered by battery/UC. The performance of the proposed method is compared with dynamic programming (DP) that is one of the global optimization methods and particle swarm optimization (PSO) that is one of the other heuristic methods for real-time applications. The simulation results show that Jaya-EMS approached 3.1% to the DP, which yields the optimum result with respect to the total energy loss. In addition, the proposed method yields a loss of less than 1.9% from the PSO-EMS. If all the above situations are considered, the proposed EMS method has less lossy alternative solution for the real-time applications.     

Recommendation on modelling of solar energy incident on a building envelope

It is important to know how to design a building to meet seasonally varying energy needs. In high latitude countries in winter the demand for space heating is high and a building envelope should receive maximum incident solar energy. On the other hand, in summer, walls and roofs exposed to incident solar radiation usually require shading to avoid too much solar gain. Data on solar energy availability are crucial for good building design. However, it is important how the availability of solar radiation is determined. An important aim of the paper presented is to give some results of a comparative analysis of two basic sky models, isotropic: Hottel–Woertz–Liu–Jordan and anisotropic: the HDKR, Hay–Davies–Klucher–Reindl, to recommend one of these models for determination of solar energy availability on a building envelope and to formulate the energy balance of a building. Differences between results obtained from both models increase with the slope of exposed surfaces. The biggest differences (12–15%) are evident for vertical south surfaces, especially in summer. The simplified isotropic sky model is not recommended for evaluation of solar radiation availability on the building envelope. Underestimation of solar gains can lead to the selection of an unsuitable concept and construction of a building and result in poor indoor thermal comfort, i.e. overheating of rooms in summer.     

Determination of the economical insulation thickness of building envelopes simultaneously in energy-saving renovation of existing residential buildings

When the energy saving rate of existing residential buildings renovation is determined, the thermal performances of external walls, windows, and roof interact with each other. Therefore, it is necessary to study the determination of economical insulation thickness of building envelopes considering the interaction among building envelope performances. The objective function and its bound of envelope thermal performance optimization in the energy-saving renovation of existing residential buildings in severe cold and cold zones in China were established. It is the conditional extremum problem and can be solved through Lagrange’s method of multipliers to determine the economical insulation thickness of external walls and roofs simultaneously. The method is proved to be feasible by an existing residential building in Beijing. When the same window types are selected, the energy-saving renovation program of the building envelope determined by the Lagrangian optimization method can produce the minimum investment in insulation, minimum investment payback period, and the largest net present value (NPV) of the life cycle.     

约束型ME-PP模型在大坝安全评价中的应用

鉴于大坝安全综合评价中的权重选取关系到评价结果的可靠性、合理性,为充分挖掘大坝监测数据所携带的信息,并考虑影响大坝基岩安全的因素特征,从投影寻踪方法的优化函数和约束条件两个方面改进传统算法,即采用最大熵原理与投影寻踪耦合模型改进投影寻踪方法的优化函数,结合实测指标的特征改进投影寻踪法的约束条件,从而得到约束型最大熵投影寻踪耦合模型。将该模型计算得到的各实测指标权重运用于灰色聚类综合评价,并利用聚类系数向量的灰度进行方法优劣的判别。实例应用结果表明,将本文方法求得的权重用于综合评价是合理可行的,相比于熵权法、传统投影寻踪法,更符合大坝基岩实测数据的特征,且得到的评价结果灰度更小,更易区分所属灰类。     

电力系统源-网-荷-储协调水平综合评价方法研究

在源-网-荷-储协调优化成为电力系统发展趋势的背景下,对系统协调水平进行全面、合理的评估有利于把握影响系统协调能力的关键环节,指导规划方案的优化.首先,分析源-网-荷-储协调运行背景下,影响系统协调能力的不确定性因素,构建计及多主体交互的分层级评价指标体系;然后,建立各指标数学模型,提出基于AHP-Delphi赋权法的...     

Soft computing methodologies for estimation of energy consumption in buildings with different envelope parameters

In this study, soft computing methods are designed and adapted to estimate energy consumption of the building according to main building envelope parameters such as material thicknesses and insulation K-value. In order to predict the building energy consumption, novel intelligent soft computing schemes, support vector regression (SVR), and adaptive neuro-fuzzy inference system (ANFIS) are used. The polynomial, linear, and radial basis function (RBF) is applied as the kernel function of the SVR to estimate the optimal energy consumption of buildings. The performance of proposed optimizers is confirmed by simulation results. The SVR results are compared with the ANFIS, artificial neural network (ANN), and genetic programming (GP) results. The computational results show that an improvement in predictive accuracy and capability of generalization can be achieved by the ANFIS approach in comparison to the SVR estimation. Based on the simulation results, the effectiveness of the proposed optimization strategies is verified. The data used in soft computing were obtained from 180 simulations in EnergyPlus for variations of building envelope parameters.     

Review on multi-criteria decision analysis aid in sustainable energy decision-making

Multi-criteria decision analysis (MCDA) methods have become increasingly popular in decision-making for sustainable energy because of the multi-dimensionality of the sustainability goal and the complexity of socio-economic and biophysical systems. This article reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation. The criteria of energy supply systems are summarized from technical, economic, environmental and social aspects. The weighting methods of criteria are classified into three categories: subjective weighting, objective weighting and combination weighting methods. Several methods based on weighted sum, priority setting, outranking, fuzzy set methodology and their combinations are employed for energy decision-making. It is observed that the investment cost locates the first place in all evaluation criteria and CO₂ emission follows closely because of more focuses on environment protection, equal criteria weights are still the most popular weighting method, analytical hierarchy process is the most popular comprehensive MCDA method, and the aggregation methods are helpful to get the rational result in sustainable energy decision-making.     

建筑墙体热工性能测试技术研究

针对建筑围护结构热阻的检测技术进行分析与探讨,结合理论计算和实验研究对建筑围护结构的热工性能进行分析,归纳出所得结果。通过实验研究,提出合理的检测技术及方法,以供设计各种墙体砌块的孔型及空心率,使建筑围护结构的热工性能达到国家标准提出的节能50％的要求。     

既有建筑的围护结构节能改造分析

以某办公建筑和住宅楼为模型,对其进行围护结构节能改造分析.通过计算比较改造前后室内负荷的变化,发现节能效果相当显著,证明在我国既有建筑围护结构节能改造存在相当大的潜力.     

Fault diagnosis of low-speed rolling bearing based on weighted reconstruction of vibration envelopes

The main bearing supports the rotation of the main shaft of a wind turbine. It bears heavy dead weights as well as variable speed dynamic loading during operations; thus, it is a vulnerable part in a wind turbine drive train. Because of the low speed and time-varying operations of the main bearing, vibrations generated by bearing faults are often weak in response amplitudes, low in frequency range, and smeared in damage feature energy. As a result, the applicability of the conventional acceleration envelope analysis (AEA) technique, a traditionally effective technology for bearing fault diagnosis, is limited in such cases. In order to resolve this, a modified AEA method specially designed for bearings with low and variable speed operation is proposed in this paper. First, the structural response is decomposed by means of variational mode decomposition (VMD) for the low frequency components to form a series of band-limited intrinsic mode functions (BLIMFs). Next, weighting factors are determined for the BLIMFs by defined energy ratios. Finally, a new envelope is reconstructed by weighting the envelopes of each BLIMF for bearing fault diagnosis. The effectiveness and practicality of the proposed method for the diagnosis of main bearing faults in wind turbines is verified through the analysis of measured data from a wind turbine in the field. The proposed method provides an effective way for bearing fault diagnosis at low and variable rotational speeds.     

混合型多属性群决策的油田节能项目优选模型——基于Vague集TOPSIS方法的研究

油田属于高耗能企业,加大油田节能降耗工作的实施力度不仅需要降低能耗,节约能源,还需要降低生产成本,提高油田的竞争力.实施节能项目是油田挖掘节能潜力,降低能源消耗和生产成本的重要途径,也是油田节能工作的具体表现.为合理选择节能项目和节能方法,提高油田节能效益,以油田节能项目为研究对象,结合其多属性、不确定和群决策等特点,同时考虑到专家群体对属性主观赋权的偏好和决策者对决策重要性认识的偏好,以及决策存在未知信息等因素,结合专家和决策者的特点以及油田节能工作的具体要求,构建油田节能项目的混合型多属性决策模型,提出一种考虑专家评价习惯和决策者对决策重要性认识的权重确定方法.通过将该方法应用于油田节能项目优选模型的应用实例中,为油田节能项目选出最优方案.结果表明,基于Vague集TOPSIS方法的混合型多属性群决策的油田节能项目优选模型切实可行,更符合油田节能工作的实际要求,为油田节能项目优选提供了新思路.     

河流健康评价中赋权方法的研究

河流健康评价体系中指标众多,指标权重的确定是关键步骤之一。针对指标权重计算的问题,首先介绍了层次分析法、熵值法、超标倍数法及主成分分析法四种指标权重赋权方法,再基于离差平方和准则构造最优化组合赋权法,将四种赋权方法结合,并采用指数型隶属函数得到模糊关系矩阵。对比各种方法的评价结果,并应用到某市河流健康评价中,不同赋权方法的计算结果均表明该河流健康状况为良,符合实际情况,表明不同赋权方法均有其合理性,为河流健康评价研究奠定了基础。     

Estimating the potential yield of small building‐mounted wind turbines

The wind profile in the urban boundary layer is described as following a logarithmic curve above the mean building height and an exponential curve below it. By considering the urban landscape to be an array of cubes, a method is described for calculating the surface roughness length and displacement height of this profile. Firstly, a computational fluid dynamics (CFD) model employing a k‐? turbulence model is used to simulate the flow around a cube. The results of this simulation are compared with wind tunnel measurements in order to validate the code. Then, the CFD model is used to simulate the wind flow around a simple pitched‐roof building, using a semi‐logarithmic inflow profile. An array of similar pitched‐roof houses is modelled using CFD to determine the flow characteristics within an urban area. Mean wind speeds at potential turbine mounting points are studied, and optimum mounting points are identified for different prevailing wind directions. A methodology is proposed for estimating the energy yield of a building‐mounted turbine from simple information such as wind atlas wind speed and building density. The energy yield of a small turbine on a hypothetical house in west London is estimated. The energy yield is shown to be very low, particularly if the turbine is mounted below rooftop height. It should be stressed that the complexity of modelling such urban environments using such a computational model has limitations and results can only be considered approximate, but nonetheless, gives an indication of expected yields within the built environment. Copyright © 2007 John Wiley & Sons, Ltd.     

河流健康评价中赋权方法的研究

河流健康评价体系中指标众多,指标权重的确定是关键步骤之一。针对指标权重计算的问题,首先介绍了层次分析法、熵值法、超标倍数法及主成分分析法四种指标权重赋权方法,再基于离差平方和准则构造最优化组合赋权法,将四种赋权方法结合,并采用指数型隶属函数得到模糊关系矩阵。对比各种方法的评价结果,并应用到某市河流健康评价中,不同赋权方法的计算结果均表明该河流健康状况为良,符合实际情况,表明不同赋权方法均有其合理性,为河流健康评价研究奠定了基础。     

Multi-Objective Particle Swarm Optimization(MOPSO) for a Distributed Energy System Integrated with Energy Storage

Distributed energy systems are considered as a promising technology for sustainable development and have become a popular research topic in the areas of building energy systems. This work presents a case study of optimizing an integrated distributed energy system consisting of combined heat and power(CHP), photovoltaics(PV), and electric and/or thermal energy storage for a hospital and large hotel buildings located in Texas and California. First, simulation models for all subsystems, which are developed individually, are integrated together according to a control strategy designed to satisfy both the electric and thermal energy requirements of a building. Subsequently, a multi-objective particle swarm optimization(MOPSO) is employed to obtain an optimal design of each subsystem. The objectives of the optimization are to minimize the simple payback period(PBP) and maximize the reduction of carbon dioxide emissions(RCDE). Finally, the energy performance for the selected building types and locations are analyzed after the optimization. Results indicate that the proposed optimization method could be applied to determine an optimal design of distributed energy systems, which reaches a trade-off between the economic and environmental performance for different buildings. With the presented distributed energy system, a peak shaving in electricity of about 300 kW and a reduction in boiler fuel consumption of 610 kW could be attained for the hospital building located in California for a winter day. For the summer and transition seasons, electricity peak shaving of 800 kW and 600 kW could be achieved, respectively.     

建筑室内人体太阳辐射得热特性及数值模拟

太阳辐射对建筑室内人体热舒适和建筑能耗有着显著影响.通过实测验证了daylight coefficient(DC)算法模拟太阳辐射强度的准确性.随后基于假人仿真模型采用DC算法计算室内人体平均辐射温度增量(ΔMRT),与SolarCal(SC)算法结果作对比,并对SC算法进行改进.相比原SC算法,改进SC算法与DC算法...     

A new constraint handling method for wind farm layout optimization with lands owned by different owners

For wind farm optimizations with lands belonging to different owners, the traditional penalty method is highly dependent on the type of wind farm land division. The application of the traditional method can be cumbersome if the divisions are complex. To overcome this disadvantage, a new method is proposed in this paper for the first time. Unlike the penalty method which requires the addition of penalizing term when evaluating the fitness function, it is achieved through repairing the infeasible solutions before fitness evaluation. To assess the effectiveness of the proposed method on the optimization of wind farm, the optimizing results of different methods are compared for three different types of wind farm division. Different wind scenarios are also incorporated during optimization which includes (i) constant wind speed and wind direction; (ii) various wind speed and wind direction; and (iii) the more realistic Weibull distribution. Results show that the performance of the new method varies for different land plots in the tested cases. Nevertheless, it is found that optimum or at least close to optimum results can be obtained with sequential land plot study using the new method for all cases. It is concluded that satisfactory results can be achieved using the proposed method. In addition, it has the advantage of flexibility in managing the wind farm design, which not only frees users to define the penalty parameter but without limitations on the wind farm division.