Towards Positive Energy Districts in Smart Cities: A Data-Driven Approach Using Aggregation and Disaggregation of Energy Balance Calculations

Selma Čaušević, G. Huitema, Arun Subramanian, Coen van Leeuwen, M. Konsman
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引用次数: 2

Abstract

Positive energy districts (PEDs) are seen as a promising pathway to facilitating energy transition. PEDs are urban areas composed of different buildings and public spaces with local energy production, where the total annual energy balance must be positive. Urban areas consist of a mix of different buildings, such as households and service sector consumers (offices, restaurants, shops, cafes, supermarkets), which have a different annual energy demand and production, as well as a different consumption profile. This paper presents a data modeling approach to estimating the annual energy balance of different types of consumer categories in urban areas and proposes a methodology to extrapolate energy demands from specific building types to the aggregated level of an urban area and vice versa. By dividing an urban area into clusters of different consumer categories, depending on parameters such as surface area, building type and energy interventions, energy demands are estimated. The presented modeling approach is used to model and calculate the energy balance and CO2 emissions in two PED areas of the City of Groningen (The Netherlands) proposed in the Smart City H2020 MAKING CITY project.
迈向智慧城市的正能量区:利用能量平衡计算的聚合和分解的数据驱动方法
正能量区(PEDs)被视为促进能源转型的有希望的途径。PEDs是由不同的建筑和公共空间组成的城市区域,具有当地的能源生产,每年的总能源平衡必须是正的。城市地区由不同的建筑组成,例如家庭和服务部门消费者(办公室,餐馆,商店,咖啡馆,超市),它们具有不同的年度能源需求和生产,以及不同的消费概况。本文提出了一种数据建模方法来估计城市地区不同类型消费者类别的年度能源平衡,并提出了一种方法来推断特定建筑类型的能源需求到城市地区的总体水平,反之亦然。通过根据表面面积、建筑类型和能源干预等参数,将城市区域划分为不同消费者类别的集群,可以估计能源需求。所提出的建模方法用于模拟和计算荷兰格罗宁根市两个PED区域的能量平衡和二氧化碳排放,该区域是智慧城市H2020制造城市项目中提出的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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