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Battery-electric buses (BEBs) are a promising technology for replacing diesel buses and reducing their environmental burden. However, their charging process can take several hours, depending on the charging technique and strategy, making them susceptible to schedule disruptions. Furthermore, the selection of the charging strategy and battery size can increase the total capital investment and operational expenses of a BEB fleet, which is a major obstacle to its adoption. Therefore, to minimize the total cost of ownership (TCO) and prevent schedule disruptions, it is essential to establish a well-defined approach to determine an appropriate battery size and charging strategy for BEB fleets. This paper presents a method for reducing the TCO of BEB by determining the optimal battery size and charging strategy for each bus while satisfying operating constraints. The method involves a two-step optimization algorithm that uses Dynamic Programming and Genetic Algorithm. The study applies this approach to the bus fleet serving line 21 in Paris and generates the optimal battery sizing, charging strategy, and required charging infrastructure. The results indicate that 100 kWh batteries offer the best trade-off between capital and operational expenditure for the fleet deployment if used with 65–85 kW chargers at bus terminals. • Proposes a co-optimization method for e-bus battery size and charging strategy • Minimizes a comprehensive cost of deployment of electric bus fleet • Considers all different types of stationary charging infrastructure • Optimizes a comprehensive list of design and operation parameters [ABSTRACT FROM AUTHOR]

With the deployment of battery electric buses (BEB) increasing worldwide, proper battery sizing becomes more critical for operators as it dictates bus driving range and costs. In this paper, we present a battery sizing framework based on comprehensive energy needs assessment for BEB. The bus operating conditions are first defined for different types of bus service (City, intercity, shuttle, regional, rapid-transit). Then, BEB energy consumption is evaluated using a comprehensive energy model developed by the authors. Finally, the required battery size is estimated for different types of charging infrastructure. Modeling results show that BEB energy consumption is sensitive to bus service type, ranging widely between 2 and 4.6 kWh/km, and that intercity buses require the largest battery size (320–680 kWh). A practical finding for operators from our Paris case study is that city bus batteries are unnecessarily oversized to accommodate a typically small fraction of trips in rare extreme cold weather conditions. • Study proposes a battery sizing framework for electric buses. • Evaluates energy consumption and battery sizing for different types of bus service. • Tool to estimate the required battery size and charging infrastructures. • Bus energy consumption and battery size are sensitive to its transit service type. • City bus Batteries oversized to accommodate small number of trips during the year. [ABSTRACT FROM AUTHOR]

In order to contribute to the decarbonization of heating consumption, France has set some objectives to develop District heating and/or cooling networks (DHCN). In this context, it is useful to identify the most appropriate district areas for implementing DHCN, and to assess their potential of development. After introducing the situation of DHCN in France, this paper presents a typology to assess the potential of development of those networks in France, based on an original method that involves the calculation of 3 variables: the linear heating/cooling density (LHD/LCD), the Proportion of Buildings anterior to 1990 and the share of energy consumption from the residential sector, to assess respectively the energy density, the supply temperatures and the energy mix between the different sectors of activities. LHD and LCD are calculated using a Delaunay triangulation and Kruskal's algorithm applied to buildings whose heating and cooling demands are calculated at a local scale. 18 different types of districts are defined for both DHN and DCN, among which 9 have a sufficient LHD/LCD. Then, the potential of development for DHN and DCN is calculated on the French territory. Thus, the DHN potential is assessed to 132 TWh/y while the DCN potential is assessed to 7.8 TWh/y. • Evolution of District Heating and/or Cooling Network (DHCN) in France. • A method to assess the linear density for potential networks. • A new typology of districts built from the point of view of the heating/cooling network integration. • An estimation of the potential of development for DHN and DCN in France. [ABSTRACT FROM AUTHOR]

Abstract: To face winter electricity peaking issues the authors proposes an analysis of the potential of distributed gas technologies for demand side management. This impact has to be analysed at small scale before any large scale extrapolation. Bi-energy technologies (gas and electricity) are a path to transfer loads from one system to another. Indeed, the flexible gas infrastructure adapts to load while electricity demand variations cause risk of black-out. The impacts of two hybrid technologies are studied at transformer level with 1-min experimental load profiles of 40 dwellings equipped with micro Combined Heat and Power (μCHP) boilers over a year in France. An absolute peak load reduction by 17% at small scale is found. Different technology mixes are then simulated to assess the effect on local infrastructure. Finally a methodology for temperature dependence analysis of load is used to assess different potential benefits of gas technologies. [Copyright &y& Elsevier]

With the announced plans to ban diesel in major European cities from 2025, battery-powered electric buses (BEB) are attracting attention to replace diesel fleets, given their zero tailpipe emissions. However, their large-scale deployment faces several challenges, namely the limited driving range (DR) and the need for adequate charging infrastructure. The limited DR is due to the lower battery specific energy compared to oil-based fuels. Also, the use of electric auxiliaries, especially, air conditioning, reduces the DR further. The DR problem could be resolved either by increasing the battery capacity, which increases the bus cost or by rightsizing the battery alongside an adequate charging strategy to avoid schedule disruption. Therefore, this paper presents a comprehensive energy modeling of a BEB using Dymola, encompassing the different energy systems encountered in BEB. The proposed model serves as a platform to evaluate the bus energy needs during its service to properly size the battery. A powertrain model is presented to emulate the propulsion load. Then, a cabin model alongside a heating ventilating and air conditioning system are developed emulating the thermal load. Finally, auxiliaries necessary for the bus operation are modeled. The energy consumption of each system is assessed under several operating conditions. Image 1 • Study proposes a modeling methodology to assess battery electric buses energy consumption. • Assesses the impact of different driving and weather conditions and passengers load on the energy consumption. • Model serves as a platform to evaluate battery electric buses energy needs to properly size the battery. • Cabin thermal needs and auxiliaries reduce driving range by more than 50% under extreme weather and driving conditions. [ABSTRACT FROM AUTHOR]