A GIS-integrated Model for Advanced Local Energy Planning

After some introductory remarks upon the Advanced Local Energy Planning issues, methodologies and tools developed in last years, the integration of the space variable into the analysis approach performed with some models of the MARKAL-TIMES family is discussed. Some recent applications performed by the LAME Team are discussed, where a high regionalization of the RES (MATISSE) or new spatial descriptions of the energy trade routes (REACCESS) have been performed. For a local energy planning, where a defined metropolitan area and one of its districts is involved, it is useful to develop specific GIS-integrated modelling tools able to identify (and locate) and to characterize a suitable mix of measures / intervention / technologies and infrastructures in the direction of a “smart” and sustainable society, for exploring significant mid- and long-term scenarios. The LEP-CN (Local Energy Planning for China) Model, derived from the EDPM-CN (Energy Demand Projection Model) developed in the framework of an EU-CHINA 5-Year program (EC2), is presented. This Model is able to assess, in a mid-long term time horizon, the energy consumptions by end-use sector on an urban district scale, by means of a simulation approach and of a geo-referenced characterization of all the buildings in the analyzed area. Construction data related to the building (Floor Area, Number of floors, Volume, Form Factor, Construction Period, Reference Building Type, and so on) and main energy related indicators (per capita Floor Area, number of persons in a single Household, per capita Income, and so on are taken into account. The main technologies adopted by each building for the fulfilment of each Service Demand (Space Heating, Space Cooling, Water Heating, Cooking, Lighting) and the number of electrical appliances (TV, Refrigerators, Washing Machines, Dish Washers, PC, and so on) for each building are also considered. The state of the connections to the district heating and to the natural and city gas networks and the identification of the connecting nodes and parameters describing the “load” of the connection (from a technical/economic point of view) are included. Furthermore, starting from the space heating demand of each building and from the geo-referenced representation of the urban networks, LEP-CN can perform, through an embedded procedure, an analysis on the district heating system; in absence of a local network, it is possible to find (under suitable user-defined constraints) the path that minimizes the total cost and reproduce it in a graphical form on map. Due to the lack of information on suitable Chinese building classifications and considering the limited availability of official and available data, up to twelve reference Building Units have been identified, related to the building dimensions (high rise, medium rise, low rise) and to the construction period, which incorporates the main energy related features. For the purpose of testing the LEP-CN approach an urban zone in Beijing has been identified, where there are low rise buildings belonging to urban villages (Hutong) as well as medium and high rise buildings. The LEP-CN approach resulted suitable for a significant set of urban energy planning exercises.