MUROS Y FACHADAS

A heat map (HM) is a fundamental GIS based method/tool which is used to assess, manage, and track heat demand at an urban district level. HMs are also used for analysing the efficiency and feasibility of District Heating (DH) as well as Combined Heat and Power (CHP) energy systems. DH is an approach to deliver thermal energy in the form of hot water through a local network of highly insulated pipelines [141]. In this way, heat rather than fuel is delivered to buildings. The capability to assess Urban Heat Islands (UHI) is among other advantages of HM. UHI indicates the temperature of surfaces of buildings (roofs) and streets in a city. Two examples in this regard are illustrated in Figures 2.19 and 2.20 where a HM can be used to measure the differences between the surface temperature in a city centre with countryside for instance, to show the impact of cars/motorcycles on street temperature.

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Figure 2.19. (left)Urban Heat Island map [142]; (right) Boston, Massachusetts, Surface temperature,

[143]

HM is used in the current research to assess and manage thermal energy demand at the campus level. A methodology for generating of HMs was developed for smart managing of heat demand- surplus of the university buildings.

The high efficiency of DH systems is a reason for considering it as a key method to reduce fossil energy consumption in several countries such as Denmark, Canada and UK [144-146]. In Scotland initial endeavours to promote HM started in 2007 [147] where a heat map at a resolution of 1km2 was used to indicate the location of both key supply and demand drivers as shown in Figure 2.20.

Figure 2.20. Scottish Heat Map Project [147]

The ability of combining several data layers in GIS such as geographical, energy & building data, and climate information with urban features is one of the fundamental characters of HM which has led to new urban planning proposals. The technique generates a mapping tool used by urban planners, architects and professionals [19, 148, 149]. Additionally, HM is also a useful tool to assess the end use energy at urban scale. For instance, New York HM illustrated in Figure 2.21

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which shows the city’s total annual energy demand density at block level helps policy makers and urban planners to understand the local dynamics of energy consumption of buildings. A web- based annual end use energy consumption database was developed [159] by performing a multiple linear regression to obtain electricity and total fossil fuel density for eight different building types in New York City. Total floor area of each building type was used as a predictor index for electricity and total fuel consumption. To calculate the end use energy density in a building, its total energy consumption per year was divided by total building area.

Figure 2.21.HM of New York City [150]

Although considering buildings in New York as single use was a weakness of the method, the ability to manage energy consumption at a large scale was a valuable aspect of it. The map shows density of energy demand which is valuable for energy suppliers and other professionals.

In recent studies DH was frequently acknowledged from the environmental, economic, and energy efficiency perspective; hence, it was recommended as a future energy system due to the capability of integration with renewable energy sources [144]. Developing of HM which plots existing and future heat demands vs. existing and future heat supply is a crucial prerequisite for improving DH systems.

HMs involve depicting both heat demand and supply within a group of buildings in a given urban district. In this context, demand refers to the building size, density, functions, orientation, geometry, heat systems efficiency, local energy rules and policy. Heat supply on the other hand, refers to waste heat (machines, human & livestock, industry), surplus heat, urban heat islands, fossil and renewable sources of thermal energy. The structure of HM contains three key factors including sinks, sources, and the heat network and its smart control hub as follows:

56 A) Heat sinks [144]:

1. Building physics data such as age, material, orientation, envelop, geometry, size. 2. Estimating heat demand by understating of building types, activities, heating systems,

heating policy (in public and large buildings), energy end use 3. All heat losses due to conversion, transmission, and distribution B) Heat sources [144]:

1. Existing landfill sites (in terms of biomass) and future plans regarding waste heat, for example the heat generated by industry

2. Fossil fuel and renewable sources of energy, potentials and capability 3. Urban morphology regarding UHI as a local source of heat

C) Heat network & network brain (smart hub)

1. Existing and future heat network such as DH/CHP 2. Heat hubs (smart control centres)

2.8.1. Advantages of District Heating

The network based heating system known as District Heating (DH) is a method in which heat energy is generated in a centralised location and then distributed across a network for space heating and domestic hot water (DHW) usage [151]. Historically from the 14th _{century DH system}

has been used [152]. In comparison with individual boilers, a DH system is more efficient and produces less CO2 [153]. Since DH can utilise waste heat from various sources, for example from

renewable energy sources, it is more efficient, greener, and more cost-effective in a long term [146, 154, 155]. Table 2.12 shows a momentous growth to approximately 30 million m2in terms of the amount of building area using DH systems in the US and Canada between 2003 and 2006 [156]. DH forms a part of heating systems in the case study universities and based on this fact a new concept of sharing surplus heat was developed in this PhD research. Together with Poland, Germany is the biggest market for DH in EU. The total installed DH capacity in Germany was 49,691 MWth in 2013 [157].

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Recently, a new method of DH was developed which uses low temperature water (30-50 ˚C) in DH network rather than 70-85 ˚C as is usually used in the conventional method. The network in the new method is connected with a Thermal Bank (TB) so each member of the network at the boundary of building can apply its own heat source for instance, heat pump or solar thermal to raise the temperature of flow water to a favourite degree [153]. The DH network is similar to the smart electricity grid; however, the smart heat network is in its primary stages and needs to be developed to work as a smart district heating (SDH) system. TB is a large thermal storage place (tank) for storing hot water. Figure 2.22 shows the schematic feature of a DH.

Figure 2.22. Schematic feature of a DH system [153]

The price of supplying an efficient installation can be divided between network members [153]. At a large scale such as a community users of a DH system could make much superior modifications in terms of cost-effective and environmental benefits [158]. DH increases urban air quality by reducing fossil fuel consumption as follows:

1. Building types with a net annual cooling demand such as food stores, refrigerators can act as a heat source

2. Heat could be gathered through passive solar systems, human activity or waste heat from industry or commercial activities

3. Urban heat island can be used as a source of heat

DH has the potential to be used as a smart heating system. Developing and managing the smart systems relies upon IT and mapping tools. Particularly, from the viewpoint of suppliers where the interpretation of heat maps is crucial. Modelling of time-variable heat demand-generation helps

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to increase the stability and efficiency of the system and reduce the role of back up (mostly fossil) energy source.