Optimal planning of flood-resilient electric vehicle charging stations

This study is the first attempt to integrate flood resilience into the electric vehicle (EV) charging station planning process. Instead of fully avoiding flood-prone areas, an optimized placement considering the magnitude of flood inundations can minimize the impact of flood hazards and simultaneously maximize the socio-economic benefit of EV charging station networks. In this study, an integrated framework of the non-dominated sorting genetic algorithm-III (NSGA-III) and the technique for order of preference by similarity to ideal solution (TOPSIS) is proposed to optimize the charging station locations by maximizing the charging convenience, minimizing the impact of flood hazards, and minimizing the impact of existing charging stations. The NSGA-III is applied to solve the multi-objective location optimization of charging stations. TOPSIS is subsequently used to determine the best solution from the feasible candidates generated by the NSGA-III. A case study conducted in the Waikiki area demonstrates that the proposed optimization framework can effectively deal with the trade-off between the impact of flood hazards and the charging service of a charging station network. This study provides new insights into best practices for dealing with multiple conflicting objectives in EV charging station planning under climate change.     

On the role of time-of-use electricity price in charge scheduling for electric bus fleets

As electric buses become increasingly popular, it is imperative to optimize the schedules of electric buses with explicit consideration of their charging requirements. Unfortunately, existing studies failed to properly model the impacts of essential operating factors, including the time-of-use (TOU) electricity price, partial charging, and limited chargers. Our paper proposes a mixed-integer nonlinear program to minimize the total operating cost of an electric bus fleet for fulfilling a group of timetabled trips, considering the above realistic features simultaneously. To effectively solve the problem of global optimality, we convert this model to an equivalent set partitioning model and develop a specialized branch-and-price approach subsequently. Our approach's computational efficiency is verified via extensive numerical experiments. The model is applied to a real-world case study in Nanjing, China. Results show that incorporating the TOU electricity price into the electric bus scheduling problem can produce a sizeable cost saving of up to 22%. Managerial insights unveiled by the numerical results are discussed. These insights inform the practitioners of how the operations of electric buses can be both cost-effective and grid-friendly.     

Co-simulation of innovative integrated HVAC systems in buildings

Integrated performance simulation of buildings' heating, ventilation and air-conditioning (HVAC) systems can help in reducing energy consumption and increasing occupant comfort. However, no single building performance simulation (BPS) tool offers sufficient capabilities and flexibilities to analyse integrated building systems and to enable rapid prototyping of innovative building and system technologies. One way to alleviate this problem is to use co-simulation, as an integrated approach to simulation.

This article elaborates on issues important for co-simulation realization and discusses multiple possibilities to justify the particular approach implemented in the here described co-simulation prototype. The prototype is validated with the results obtained from the traditional simulation approach. It is further used in a proof-of-concept case study to demonstrate the applicability of the method and to highlight its benefits. Stability and accuracy of different coupling strategies are analysed to give a guideline for the required coupling time step.     

A multi-objective framework for energy resource scheduling in active distribution networks

Purpose: The purpose of this paper is to investigate the impacts of electric vehicles' (EVs) charging/discharging decisions in energy resources scheduling problem of active distribution networks. Design/methodology/approach: The problem under study is modelled as a two-stage optimisation problem in which the main requirements of EV owners are introduced as an objective function of the first stage. The total energy costs and the emission factor are considered as the main criteria of the second stage. The output generation schedules of distributed generation (DG) technologies together with the charging/discharging schedule of EVs are proposed as decision variables of the energy scheduling problem. Therefore, some effective methods are presented to model the uncertainties associated with these variables. Findings: The results proved that an efficient compromise can be reached between the emission factor and the energy cost of the system. In addition, it has been emphasised on the importance of such comprehensive energy scheduling frameworks. Originality/value: This paper contributes by: (a) providing a multi-objective framework for energy scheduling of active distribution networks, (b) extracting the mathematical model of this two-stage problem and (c) employing a linearised optimisation model to reach its global optimal solution.     

Modified teaching-learning-based optimization by orthogonal learning for optimal design of an electric vehicle charging station

The provision of a safe environment has led to the growth of electric vehicles (EVs), whose propagation in the market depends on features such as price, battery technology, economy, and improvement of charging stations. This paper proposes a charging station for plug-in electric vehicles (PEVs) connected to the distribution system, along with the energy storage system's batteries, diesel generator, and photovoltaic panels. The charging facilities are also designed and optimized at three levels of fast, medium, and slow speeds. Since this model integrates many decision variables and cannot be accurately solved by traditional mathematical methods, a new modified optimization algorithm is presented. The modified teaching-learning-based optimization (TLBO) based on orthogonal learning (OL), or OLTLBO, is proposed to solve the optimization problem. The results confirm that the model successfully uses all the available options to design the EVCS.     

Evaluation of a PV-integrated building application in a well-controlled outdoor test environment

This paper presents the assessment of experimental data for electrical and thermal performance evaluation of photovoltaic (PV) systems integrated as cladding components into the building envelope, giving input to modelling and analysis work. From the experience gained in several EU research projects, an improved design for a common Test Reference Environment (TRE) has been developed. This specific design of the PV module and TRE makes it possible to study, through electrical and thermal energy flow analysis, the effect on electrical performance of using different materials for PV modules and the construction design of claddings. The results for a glass–glass PV module with forced ventilation are presented.     

A proposed framework for dynamic modelling of photovoltaic systems for DG applications

Dynamic modelling and simulation is essential to predict the overall electrical performance of photovoltaic (PV) systems. PV simulation models in the literature are not suitable for dynamic analysis with decentralised generation (DG) applications. This article proposes a framework for PV system dynamic modelling and simulation process. This framework presents the steps required to model the process of solar power generation, reflecting the environmental variables affecting the generation process. Based on the framework steps, a computer simulation model is developed in MATLAB-Simulink of the PV generator, and validated by comparing the developed PV electrical performance characteristic curves with those of the manufacturer's data sheet and the ones developed by commercial software. The last step of the proposed framework is dedicated for testing the developed PV model for grid-connected operation. The proposed framework resulted in a simulation photovoltaic decentralised generation model which constitutes a computer-aided design tool that is helpful for real-world solar energy engineering.     

A PV installation framework concerning electricity variable rates

This paper assesses building integrated photovoltaic (BIPV) installation parameters based on the profit generated by a photovoltaic system. It takes into consideration a home building case study and it investigates its monthly energy demand based on a specific location and a typical occupancy. The capability of a photovoltaic (PV) system to generate more profit occurs when solar intensity is maximum while the electric energy price is at its highest rate. The paper traces a framework that encompasses different aspects such as energy demand, energy price, and solar intensity. This framework identifies profit alternatives according to different installation parameters. A tool that predicts a PV installation hourly electric energy production is developed. The profit generated is simulated for home buildings located in Beirut (Lebanon) and Xihua (China), both at 33.8° latitude north. The paper highlights a new approach for BIPV installations, taking into account weather conditions, energy demand, and electric energy utility rates.     

Simplified method of sizing and life cycle cost assessment of building integrated photovoltaic system

This paper presents methodology to evaluate size and cost of PV power system components. The simplified mathematical expressions are given for sizing of PV system components. The PV array size is determined based on daily electrical load (kWh/day) and number of sunshine hours on optimally tilted surface specific to the country. Based on life cycle cost (LCC) analysis, capital cost (US$/kW_P) and unit cost of electricity (US$/kWh) were determined for PV systems such as stand-alone PV (SAPV) and building integrated PV (BIPV). The mitigation of CO₂ emission, carbon credit and energy payback time (EPBT) of PV system are presented in this paper. Effect of carbon credit on the economics of PV system showed reduction in unit cost of electricity by 17-19% and 21-25% for SAPV and BIPV systems, respectively. This methodology was illustrated using actual case study on 2.32 kW_P PV system located in New Delhi (India).     

A product modeling approach to building knowledge integration

Knowledge informatics is still playing only a minor role in the design process of buildings and civil engineering efforts, particularly in the inception stage. The primary reason that most knowledge tools are not well integrated into the process is that most tend to be based on stand alone expert system technology. Improving the re-use of existing knowledge is required to increase industry performance. A solution could be a new generation of integrated knowledge systems. One problem that must be addressed is how to cope with the conflicting requirements of each particular subsystem when each is optimized for its own knowledge domain. No optimum solution exists that is able to simultaneously optimize each subsystem for a total solution. This paper discusses an approach to building knowledge integration that attempts to address these shortcomings through the use of combined product model and meta-knowledge approach.     

A comprehensive and well tested energy balance for water supply systems

This paper presents a novel energy balance scheme and performance indicators for assessing energy efficiency in water supply systems. This assessment consists of a three-step procedure: system characterisation and data collection, energy balance calculation and energy performance indicators assessment. The main innovation is the integrated approach between energy and water balances allowing the quantification of energy inefficiencies directly associated with water losses. Comprehensive energy performance indicators can be calculated by utilities with different maturity levels allowing a fair comparison of energy efficiency between systems with different layouts and operational schemes. This energy balance scheme has been applied by 17 water utilities in Portugal. Results have shown that systems provide more than twice the minimum energy necessary to supply their consumers and, consequently, there is a significant energy saving potential: 40% through water loss reduction, 30% for changes in network operation and layout and 30% for pump inefficiency reduction.     

Joint power distribution and charging network design for electrified mobility with user equilibrium decisions

Rapid adoption of electric vehicles (EVs) requires the development of a highly flexible charging network. The design and management of the charging infrastructure for EV-dominated transportation systems are intertwined with power grid operations both economically and technically. High penetration of EVs in the future can increase the charging loads and cause a wide range of operational issues in power distribution networks (PDNs). This paper aims to design an EV charging network with an embedded PDN layout to account for energy dispatch and underlying traffic flows in urban transportation networks supporting electric mobility in the near future. A mixed-integer bilevel model is proposed with the EV charging facility location and PDN energy decisions in the upper level and user equilibrium traffic assignment in the lower level considering an uncertain charging demand. The objective is to minimize the cost of PDN operations, charging facility deployments, and transportation. The proposed problem is solved using a column and constraint generation (C&CG ) algorithm, while a macroscopic fundamental diagram concept is implemented to estimate the arc travel times. The methodology is applied to a hypothetical and two real-world case study networks, and the solutions are compared to a Benders decomposition benchmark. The east-coast analysis results indicate a 77.3% reduction in the computational time. Additionally, the benchmark technique obtains an optimality gap of 1.15%, while the C&CG algorithm yields a 0.61% gap. The numerical experiments show the robustness of the proposed methodology. Besides, a series of sensitivity analyses has been conducted to study the impact of input parameters on the proposed methodology and draw managerial insights.     

Optimal sizing of building integrated hybrid PV/diesel generator system for zero load rejection for Malaysia

In this research, an optimisation for building integrated hybrid PV/diesel generator system for zero load rejection for Malaysia is performed. The optimisation is performed considering a loss-of-load probability (LLP) less than 0.01. However, the daily averages of solar energy for Malaysia and a mathematical model of a hybrid PV/diesel generator system are used in this optimisation. The optimisation presented in this paper aims to calculate the optimum capacities of a PV array and diesel generator, which investigate the minimum system cost. An optimisation problem in terms of system units’ cost is solved graphically in this study. Moreover, the optimised system is compared to other energy source choices to highlight its feasibility. The recommended configuration of a PV/diesel system located in Malaysia is C_A = 1.2, C_DG = 0.3, while the optimum C_B is 0.1. The results of the optimisation show that a PV/diesel generator choice is more feasible compared to a standalone PV system or diesel generator system because it reduces the system cost by 35%.     

Performance comparisons of two system sizing approaches for net zero energy building clusters under uncertainties

Uncertainties have significant impacts on system sizing in net zero energy building(NZEB)clusters and they have to be well considered.Through Monte Carlo simulation and statistical analysis,the impacts of three typical types of parameter uncertainties have been investigated in the study.Considering the uncertainty impacts,this study aims to compare the multi-criteria performance of two design approaches for system sizing of a NZEB cluster.The first one is the conventional separated design in which dedicated systems are separately designed in individual buildings.The second one is the integrated design in which integrated systems are designed to provide services to all buildings.The study results show that the integrated design approach can achieve significant system size reductions and large initial cost savings as compared with the conventional separated design.The initial costs of the air-conditioning,PV and wind turbine systems can be reduced by 14.4%,13.7% and 11.8%respectively.The integrated design also achieves improved grid friendliness and equivalently good indoor thermal comfort in comparison with the conventional separated design.With such improved performance,the integrated design should replace the conventional separated design for system sizing in NZEB clusters as uncertainties considered.     

Evaluation of an Active Building Envelope window-system

Active Building Envelope (ABE) systems are a new enclosure technology which integrate photovoltaic (PV) and thermoelectric (TE) technologies. In ABE systems, a PV-system transfers solar energy directly into electrical energy, which can be used to power a TE heat-pump system. ABE-technologies allow for the development of thermal enclosure systems that have the ability to regulate their temperature (cooling or heating) by interacting with the sun. Applications include various enclosures that require thermal control, including building enclosures. This study considers the performance of the overall prototype ABE window-systems, and also includes the PV systems. This paper reports experimental results to establish the efficiency of the ABE system prototype. Computational analysis based upon PV modeling theories are carried out to simulate the performance of the PV system directly connected to a series of TE modules. The number and type of electrical connections for the TE modules is discussed in order to pursue the maximum power point for PV operation.     

A nodal thermal model for photovoltaic systems: Impact on building temperature fields and elements of validation for tropical and humid climatic conditions

This article deals with both an experimental study and a numerical model of the thermal behaviour of a building whose roof is equipped with photovoltaic panels (PV panels). The aim of this study is to show the impact of the PV panels in terms of level of insulation or solar protection for the building. Contrary to existing models, the one presented here will allow us to determine both the temperature field of the building and the electric production of the PV array. Moreover, an experimental study has been conducted in La Reunion Island, where the climate is tropical and humid, with a strong solar radiation. In such conditions, it is important to minimise the thermal load through the roof of the building. The thermal model is integrated in a building simulation code and is able to predict the thermal impact of PV panels installed on buildings in several configurations and also their production of electricity. Basically, the PV panel is considered as a complex wall within which coupled heat transfer occurs. Conduction, convection and radiation heat transfer equations are solved simultaneously to simulate the global thermal behaviour of the building envelope including the PV panels; this is an approach we call ‘integrated modelling’ of PV panels. The experimental study is used to give elements of validation for the numerical model and a sensitivity analysis has been run to put in evidence the governing parameters. It has been shown that the radiative properties of the PV panel have a great impact on the temperature field of the tested building and the determination of these parameters has to be taken with care.     

An integrated method to optimise the infrastructure costs of bus rapid transit systems

A significant effort has been directed in many countries to develop economically feasible transportation solutions which include, in many cases, buses that run on express lanes or that are used as part of a feeder system; these systems are identified as ‘bus rapid transit systems’ (BRT). The purpose of this paper is to present a reliability cost-based optimisation model of these systems. The model couples the transportation requirements and the mechanical performance of asphalt pavement structures. Also it includes critical transportation parameters such as bus sizes, frequency of the routes and passenger demands. Regarding the pavement, the model takes into account the life-cycle of existing or new pavements, which involves a stochastic model of the pavement's mechanical properties and its overall performance. The model is applied to the actual case of Bogota's rapid transportation system, i.e. Transmilenio, showing the importance of this integrated approach to build efficient BRT systems.     

我国发展快速公交系统的技术探讨与实施对策

随着我国国民经济快速发展，城市规模不断扩大，加上居民生活水平提高，我国汽车保有量飞速增长。截至2003年9月．北京市私人小汽车总量已接近87万辆，从而引发了交通流量的攀升。据统计，1995年至2001年，北京四环路以内100条道路的交通流量增加了近一倍，2002年市区道路交通流量又比上年上升了94％，     

Wind turbine development for rural electrification in Nicaragua

This paper presents the development of a wind turbine designed for rural electrification efforts throughout Nicaragua. The turbine was designed to use locally available and recycled materials in order to reduce production costs and thus make them more feasible for developing countries. A vertical axis configuration was chosen in order to have minimal impact on local ecology and terrain aesthetics. The Bassett Sail-Blade rotor assembly is introduced. In addition, a dual rotor axial flux alternator was constructed with reclaimed automotive parts and imported neodymium magnets using simple hand tools. When integrated into a community battery charging station, the developed turbine can be used as a cost-effective solution to rural electrification and conservation efforts throughout the developing world.     

Agent-based system identification for control-oriented building models

The paper presents a general agent-based system identification framework as potential solution for data-driven models of building systems that can be developed and integrated with improved efficiency, flexibility and scalability, compared to centralized approaches. The proposed method introduces building sub-system agents, which are optimized independently, by solving locally a maximum likelihood estimation problem. Several models are considered for the sub-system agents and a systematic selection approach is established considering the root mean square error, the parameter sensitivity to output trajectory and the parameter correlation. The final model is integrated from selected models for each agent. Two different approaches are developed for the integration; the negotiated-shared parameter model, which is a distributed method, and the free-shared parameter model based on a decentralized method. The results from a case-study for a high performance building indicate that the model prediction accuracy of the new approach is fairly good for implementation in predictive control.