• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>IAEE International Conference;International Association for Energy Economics >MODELLING THE PRIVATE HOUSEHOLDS SECTOR AND THE IMPACT ON THE ENERGY SYSTEM
【24h】

MODELLING THE PRIVATE HOUSEHOLDS SECTOR AND THE IMPACT ON THE ENERGY SYSTEM

机译：私人家庭部门建模及其对能源系统的影响

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

OverviewAs part of the project Dynamis (Dynamic and Intersectoral Evaluation of Measures for the cost-efficientDecarbonisation of the Energy System) [1] the Forschungsstelle für Energiewirtschaft develops a model of theGerman energy system which couples its energy supply optimisation models ISAaR and MInGa with four energyapplication submodels for the industry, the commerce, trade and service, the transport and the private householdssector. The target of this paper is to introduce a methodology of modelling measures to reduce CO_2 Emissions in theprivate households sector taking into account the requirements of the ever changing energy system. The focus of thispaper lies on the heating of households because of its high share of total emissions [2]. In this regard an overview ofthe methodology explains the dependencies between the different models. The exemplary results show the reductioncosts for a demand side measure. Finally the conclusions are given describing the characteristics of the privatehouseholds sector.MethodsThe main objective of Dynamis is to determine the CO_2 abatement costs for different measures considering thespecific characteristic of the sectors. Modelling the energy system in a dynamic way also means to link the modelsmentioned above. The sector-inherent costs and emissions of the demand side are calculated by the privatehouseholds sector model whereas the supply side and therefore the energy carrier related costs and emissions aresimulated by ISAaR (electricity generation) and MInGa (gas market). The analysis is being carried out from 2015 to2050 in steps of five years. The sector model consists of two main parts (centre in fig. 1): the sector state and the sector modelling. The sectorstate on the one hand includes detailed parameter sets of buildings, white goods and heating systems such as buildingcategories [3], energy efficiency, age and energy demand. On the other hand the model combines the information ofthe sector state and the measure implementation level to calculate a new sector state (5 years later). In order to do soit has to perform several tasks: 1. The dismantling-rate of technologies and buildings is used to estimate the yearly potential for newtechnologies and buildings.2. The implementation of CO_2 reduction measures leads to a substitution of reference technologies. Differentstrategies can be applied here, such as the substitution of the oldest, the most expensive or the mostinefficient technologies.3. The useful energy demand (kWh/a) is calculated with the parameter set of the buildings.4. The final energy demand can be derived from the useful energy demand and the efficiency of eachtechnology.5. Load profiles are applied in order to get a time series from the annual value.6. Costs and emissions for two scenarios (reference and measure) are calculated.ResultsAs an exemplary result Fig. 2 shows the total costs of energetic renovation per building category. Old multi-familyhouses (MFH) should be renovated first considering cost efficiency. This can mainly be explained by a good ratio oftheir area to their volume. Also old one-family houses (EFH) are represented by a large area in the chart. This isprimarily due to the high amount of buildings and the generally low insulation standard. Other building categoriesplay a minor role. But when it comes to reaching the ambitious reduction targets, even those expensive measureshave to be realized. The maximum reduction of energy by energetic renovation is 66 %. Reasons are the protectionof historical buildings and an economic maximum in insulation depth. More results from the simulation will bedescribed in the final paper.ConclusionsDue to a relatively long life span of buildings and technologies the sector private households is characterized by verylimited transformation rates. In order to meet the climate targets by 2050 it is therefore necessary to start thetransformation of the sector towards energy efficiency and low-carbon heat generation technologies as soon aspossible. As shown in fig.2 (right) aiming for several distinct targets (e.g. on for 2030 and one for 2050) can result incost inefficiencies. Therefore the focus should be on the main climate target in 2050. The decarbonization of thesector private households can be achieved by efficiency-measures and technologies using renewable energies.Results have shown that improving efficiency first often leads to the implementation of smaller scaled technologies,hence lower costs.
机译：概述 作为项目的一部分（动态和跨部门评估措施的成本效益） 能源系统的脱碳）[1] ForschungsstellefürEnergiewirtschaft开发了一个模型。 德国能源系统将其能源供应优化模型ISAaR和MInGa与四种能源结合在一起 工业，商业，贸易和服务，运输和私人家庭的应用子模型 部门。本文的目的是介绍一种减少二氧化碳排放的建模措施的方法学。 私营家庭部门考虑了不断变化的能源系统的要求。重点 由于其在总排放量中所占的比例很高，因此该论文主要依靠家庭取暖[2]。在这方面的概述 该方法论解释了不同模型之间的依赖性。示例性结果表明减少了 需求方措施的成本。最后给出结论，描述了私有企业的特征。 住户部门。 方法 动力的主要目标是确定不同措施的CO_2减排成本，考虑到 部门的具体特征。以动态方式对能源系统进行建模还意味着链接模型 上文提到的。需求方的部门固有成本和排放由私营部门计算 家庭部门模型，而供应方以及因此与能源载体相关的成本和排放为 由ISAaR（发电）和MInGa（天然气市场）模拟。这项分析是从2015年至 到2050年将以五年为单位。扇区模型包括两个主要部分（图1中的中心）：扇区状态和扇区建模。部门 一方面，状态包括建筑物，白色家电和建筑物等供暖系统的详细参数集 类别[3]，能源效率，年龄和能源需求。另一方面，该模型结合了以下信息： 部门状态和度量实施级别以计算新的部门状态（5年后）。为了这样做 它必须执行几个任务： 1.技术和建筑物的拆除率用于估计每年的新建筑潜力 技术和建筑。 2.减少CO_2的措施的实施导致了参考技术的替代。不同的 可以在这里应用策略，例如替换最旧，最昂贵或最 低效的技术。 3.使用建筑物的参数集计算有用能量需求（kWh / a）。 4.最终的能源需求可以从有用的能源需求和每种能源的效率中得出 技术。 5.应用负载曲线以便从年值中获取时间序列。 6.计算了两种方案（参考和度量）的成本和排放。 结果 作为示例性结果，图2显示了每种建筑物类别的能源改造的总成本。古老的多户家庭 房屋（MFH）应首先考虑成本效益进行翻新。这主要可以通过一个很好的比率来解释 他们的面积到他们的体积。在图表中，较大的区域也代表了旧的独户房屋（EFH）。这是 主要是由于建筑物数量高和绝缘标准普遍较低。其他建筑类别 扮演次要角色。但是，要实现雄心勃勃的减排目标，即使是那些昂贵的措施 必须实现。通过高能改造最大减少了66％的能源。原因就是保护 的历史建筑和绝热深度方面的经济最大化。模拟的更多结果将是 在最后的论文中描述。 结论 由于建筑物和技术的使用寿命较长，因此该部门的私人家庭的特点是 转化率有限。为了达到2050年的气候目标，因此有必要启动 尽快实现该部门向能源效率和低碳热发电技术的转变 可能的。如图2（右）所示，针对几个不同的目标（例如，针对2030年目标和针对2050年目标）可能会导致 成本低效。因此，重点应放在2050年的主要气候目标上。 可以通过使用可再生能源的效率措施和技术来实现私营部门的家庭。 结果表明，首先提高效率通常会导致实施规模较小的技术， 因此降低了成本。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号