Identification of the Sustainable Wind and Solar Potential in Urban Areas Using a GIS Methodology

In recent years the publication of new legislation in the renewables sector, namely the one related to microgeneration systems, has contributed to an in-crease in the installation of renewable energy systems in Portugal. Neverthe-less, the investment in these systems is still high and the risk of considering sites with reduced resource constitutes a barrier to the development of this sub-sector. In the sequence of the previous work developed in the wind energy planning area, a methodology to identify the sustainable wind and solar potential in urban areas was developed, in order to reduce the pre-installation costs related to a less suitable site selection, and also to identify the real potential of the urban areas. In order to do so, a geographical information system was used and a set of tools was developed. The methodology was structured to enable its replication in other geographical locations and is suffi-ciently interactive to allow for the variation of the main input data. A case study in two urban environments is presented in this document to illustrate the developed methodology.


Introduction
In the last two decades renewable energy sector has experienced a huge growth in Portugal mainly due to national incentives. As a consequence of this high growth, namely in the wind sector, most of the best sites for wind energy deployment are currently taken or reserved. This sudden growth has imposed a Energy and Power Engineering pressing on the authorities to grant the suitable permits for grid connection and highlighted the need to define clear rules for the identification and characterization of areas with high wind potential still available for this purpose. In this context, a structured and systematic classification of the wind data available, suitable for the wind resource assessment, was initiated and this enabled the development of a database of wind potential [1], and Portuguese Wind Atlases-onshore and offshore [2]. At the same time, the development of a tool for wind deployment planning based on a methodology to identify the sustainable wind potential using GIS-Geographical Information Systems [3] was initiated. In this line of work, the developed methodologies were adapted in order to be able to apply them to the domestic electricity micro generation sector using wind and solar photovoltaic (PV) systems. The need to accomplish with the European directives, and with the National Plans for Renewable Energies, reinforced the need to develop methodologies for the assessments of installation of such systems. In addition, most of the European Municipalities have signed the Covenant of Mayors that includes not only actions related with energy efficiency (especially on services buildings) but also with the installation of renewable energy systems for electricity production.
Cities use a high amount of energy, requiring more than 75% of global energy production and generating about 80% of greenhouse effect gases on a global scale. It is in this context that the concept of Smart City has become of great importance in the cities way of live. According to [4], a Smart City is a technological medium-sized community, connected, sustainable, comfortable, attractive, safe, and able to manage the use of resources in the most efficient manner. The optimization of available local resources, the use of new features as well as new investments, combined with the concepts of reuse and recycling of raw materials, are the essential foundations for fully achieving the Smart City model. In this context, encouraging the use of renewable energy in a domestic scale, a structured plan for the identification of suitable sites for the development of those systems is crucial and demands the development and application of suitable tools for this purpose at an urban scale.
This paper aims to contribute to the development of a set of tools that enable the quantification of the most important renewable resources for the production of electricity in an urban environment, i.e. the wind and solar resources (for photovoltaic applications). In this context, methodologies for the identification of the renewable energy potential available in urban environments with simple and less costly tools based on geographical information systems techniques are described. The results obtained are presented through two case studies.

Planning Methodologies for Urban Renewable Energy Systems Installation
Several studies and methods were developed in the latest years for the identification of renewable potential in urban areas. Most of the research developed in this area is mainly focused on solar and wind energy systems and uses technologies to manage and process this information and constitutes an asset for this kind of studies. The authors in [5], used a set of data from anemometric stations and also wind atlas data to study the wind in the city of Guelph in Canada. These authors developed an urban wind potential map and estimated the number of turbines to install in each building. In Iowa in the United States, a GIS methodology was developed to plan the installation of wind energy systems [6]. These authors developed a model that considers a large set of restrictions, including soil use, wind resource, and environmental restrictions, among other. This methodology was developed for standard wind farms, but according to its authors, it can be of great interest to extend its application to other technologies. LNEG-Laboratório Nacional de Energia e Geologia, I.P., has developed a methodology to identify the sustainable wind potential for the development of wind farm projects in Portugal [1] [7] which can also be applied to different geographies and types of environments being, therefore, a valuable planning tool.
In [8], the authors used a GIS to identify suitable sites for wind and solar systems installation aiming the production of Hydrogen. [9] identified suitable sites for the installation of PV systems, using GIS as a decision-making tool to identify which renewable technology to use in a certain site or region. [10] developed a methodology to identify the most suitable technology to install in the region of Múrcia, Spain (PV, Wind, Hybrid Wind-PV, Hybrid Wind-Diesel) [11], have developed the program GISA Sol 1.0. This program incorporates a tool for the identification of suitable sites for PV installation and considers around 80 layers of information for spatial analysis. The developed methodology allows the planning of renewable energy systems and also the management of existing systems already in operation in extensive areas.
It is thus clear that GIS platforms are of outmost importance for planning purposes since they enable the management of large amounts of information, and also provide tools to handle different kinds and formats of geo-referenced layers. Using these platforms it is also possible to automatically update maps, tables and other elements, in an easier and precise way, enabling online data publication and fast results update.

Methodology for the Identification of the Available Renewable Energy Potential
The methodology for the identification of the available renewable energy potential is based on the establishment of criteria, which refer to the minimum requirements for the installation of renewable energy systems in a given location, and thus guarantee an efficient performance of each system. In a general way, In the case of urban environments, especially when the objective is to study the whole city or district, the criteria are not so comprehensive, since the main objective is to identify the suitable areas for the installation of renewable energy systems, the detailed studies being only performed in a later stage. In this sequence, the main criteria to be applied from a planning perspective are related, in a first approach, to the suitable energy resource and available area for the installation of the renewable energy systems

Methodology for the Identification of the Available Solar Potential
The identification of the available wind potential is performed in two phases using mapped and geo-referenced information on the wind resource (meaning wind speed and power density) and on buildings geometries. In a first phase, this information is inserted in a GIS platform and tools are programed considering the suitable conditions for the installation of these renewable energy systems.
The output of this procedure is the definition of the available areas for the installation of the wind energy systems. In a second phase, the area occupied by a small wind turbine is defined and the sustainable wind potential is then calculated according to this parameter.
For the first phase, the definition of the input conditions related to the wind resource is necessary. This is done by imposing a minimum capacity factor (F c ) (Equation (1)) that enables the efficient operation of the wind turbines. In this sequence, minimum values for the remaining resource parameters-mean wind speed and power density-are defined. Limits between 10% and 20% are considered normal for the F c parameter of small wind turbines (Trust, 2008). These input data area then reclassified in order to obtain a final map with the areas of interest for this purpose (expressions 2 and 3). correspond to the same parameters after reclassification.

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The reclassified resource maps are then multiplied in order to obtain the resultant grid-points that obey all the conditions imposed to each parameter (Equation (4)). This final map will enable the calculation of the available area to use in the sustainable wind potential calculation.
After the selected areas are found, the mean suitable area to install a wind turbine must be established. This area is determined according to the wind turbine model characteristics, namely the rotor diameter and the distance between wind turbines. The minimum area occupied by each turbine, including the space to consider between them, is obtained from where min A represents the minimum area, D the wind turbine's rotor diameter and 1 N and 2 N are the minimum number of diameters spacing each wind turbine in the crosswind and along wind directions. In this case, the minimum distance to consider between each wind turbine is 3 diameters in the crosswind direction and 8 diameters in the along wind direction which corresponds to a final area of 24D 2 . The sustainable wind potential is then obtained from Equation (6), where sust Pot is the sustainable wind potential of the area under study (in kW), tot A is the total area occupied by the grid points that obey the selection conditions, and WT Pot is the nominal power of the wind turbine model selected for the study.

Methodology for the Identification of the Available Solar Potential
The identification of the available solar potential is also based in GIS methods.
The main input data is the spatial distribution of the solar potential (irradiation in MWh/(m 2 •year)), and as for the wind potential, the buildings geometry layer.
Most of the GIS platforms already include solar radiation tools which facilitate the mapping of the solar potential without having to use other programs. This is Pto where Pto sust is the grid-point that fulfils the suitability conditions, Irr is the irradiation value at point i and A min/roof is the minimum area of the roof that can be used to install the solar systems. The total area corresponds to the area occupied by all the selected grid-points, where pol i A is the area of each polygon formed by the selected points.
Still, in what concerns the available area, most rooftops are occupied with antennas, air condition equipment and other elements. Also the income irradiation is not being one hundred percent used since in this study plane rooftops and horizontal PV systems are being considered. Therefore, 10% of the available area is discounted to the overall area of the buildings. The final area is then calculated by Equation (9).

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fin tot The available solar potential is then calculated, by selecting a standard solar technology and by considering its conversion efficiency. Equation (10) was used to estimate the available solar potential for a certain urban area, available fin nom tec where P available is the available solar potential (W), A tec is the area occupied by the solar panel and P nom is the corresponding nominal power.

Methodology for the Identification of the Available Renewable Potential (PV + Wind)
The determination of the joint available potential (wind + PV) is performed assuming that the usage of space can be shared by both technologies with little interference. Thus, given that the areas of interest have already been determined by applying the methods previously described, it is necessary to define the strategy to deal with the potential interference in occupation by both technologies.
Based on the minimum distance required for the installation of small wind turbines, it is unlikely to install more than one, or at the most, two wind turbines, on a building rooftop, which makes it difficult to define an appropriate value for the occupation percentage in common areas. However, and considering a conservative scenario, it was decided to deduct 10% [12] also to areas obtained for wind technology in the previous procedure. The renewable capacity is then  Subsequently, areas are determined corresponding to the placement of each set. In common points, it is considered that the both technologies may co-exist. Assuming a conservative and planning perspective of space use, it is possible to overlay technologies. It is however noted that, in a scenario of superimposition of two technologies, there is interference related to the shading of wind turbines in photovoltaic panels (PV panels do not cause interference in the operation of wind turbines). Thus, the shadow area caused by wind turbines in photovoltaic panels is estimated, considering the worst case scenario, i.e. the shading produced on the 21st December (winter solstice), through the Equations (14) to (16), considering that the support tower of the reference wind turbine has a height of 10 m [13].
where Obst H is the height of the obstacle, Sh L is the shadow length and α is the solar altitude angle given by [14]: where G n is the day of the month in the Gregorian calendar.
In the present case, the maximum length of the shadow obtained for the center west region of Portugal, which represents the country average, was 22.4 m.
The shade of the area depends on the diameter of a reference wind turbine, so that the shadow it produces shall be, in a worst case scenario, equal to the area of a rectangle with length equal to the maximum width of the shade produced by the support tower plus the rotor plane of the wind turbine.
The power per unit area related to "n" wind turbine models available on the market is then determined using the mean value of the power per shadowed area (Equation (17)).
where Sh P A represents the power per unit of shadowed area, P n is the nominal reference power, Sh A is the shadowed area produced by a Wind turbine, and a and b are the regression coefficients that assume the values of 0.0089 and 0.1302, respectively.
The shadowed area produced by the Wind turbines to be installed in the common area, ShWT A , is calculated through Equation (18).
N WT is the number of wind turbines to install in the common area for both technologies.
In this sequence, the joint available potential is obtained according to Equation (19).
where dispE S P + is the Wind and PV available potential; A SE is the suitable area to install both technologies; A S is the suitable area for the installation of PV systems; is the nominal power of a reference wind turbine, and PVsh P is the PV solar potential in a shadowed area which can be calculated by Equation (20).

Case Study
The presented methodology is illustrated with a case study for two urban areas in Portugal, corresponding to two administrative regions inside a municipality where it was possible to obtain information on buildings polygons and attributes related to building's heights. The wind and solar potential maps were calculated using a methodology developed by [15] and are used in the present work to illustrate the methodology. Figure 1 and Figure 2 represent the irradiation, wind and power density maps in the areas under study, respectively.
Several tools were developed using the ArcG is functionality Model Builder [16] in order to enable the development of an automated process in a user-friendly and interactive way, so that the input layers and threshold values can be changed according to the user's objective. The results obtained for the two urban areas for the identification of the available wind potential, solar PV potential, and wind and solar PV joint potential with the developed tools are presented in Figures 3-5 and in Tables 1-3. The wind potential in the urban areas was calculated for 10 m above buildings height (for buildings height varying from 3 to 30 m, approximately). Identification of the available wind potential; Identification of the available solar PV potential; Identification of joint potential (wind + solar PV).

Discussion of the Results
The determination of the available and/or sustainable wind potential has been a relatively unexplored subject in recent years, therefore the methodology pre-     author has separated the building typologies namely in what concerns the type of use-residential and industrial-and the type of roof-flat or sloped, being the study referred to the rooftops only. In the present work, the approach is a little different since there is no separation between the use of the buildings and the analysis of the rooftop slope is not performed. This fact is mainly due to the lack of information on the roofs geometry and corresponding slope which led to consider that all the buildings have flat roofs in the development of this methodology. In terms of energy analysis, the assumption that all the buildings have flat roofs may lead to an underestimate of the solar resource on one hand since the optimum slopes are disregarded, but on the other hand the resource is overestimated due to shadow disregard of inclined roofs in opposite directions to sun exposure. It is then considered that there is an equilibrium in the obtained results. In the same way [23] does not consider the buildings facades since in the region where the study is referred the solar resource is reduced and has little exploitation potential. The same approach is used in the present work, although the justification is different. The urban fabric is highly variable being characterized by neighborhoods with old buildings densely distributed and where shadowed facades are expected, and also with sparsely constructed zones with open areas between the buildings. Also, the installation of PV panels in facades of existing buildings demands complex civil construction work, being more predictable that the use of PV panels in facades occurs in new buildings projected with its integration in mind. Finally, the methodology here developed intends to be In the present case the available potential was identified by means of a GIS set of tools, developed especially for this objective. In a first phase two tools were developed, one for the identification of the wind available potential and another for the solar PV available potential. To do that, the tools were programed in such a way that they can be replicated to other geometries and enable the user to change the input data according to its objectives (resource maps, input selection parameters, and other). In a second phase an interactive tool was developed for the identification of the joint potential (wind + solar PV). It is considered that this methodology brings added value and is an important contribution for the urban planning of renewable energy systems integration for several purposes in a smart cities context.

Final Notes
In this work a methodology for the identification and quantification of urban renewable potential was developed as a contribution to sustainable energy development of cities in the context of Smart Cities.
The identification of urban renewable potential was based on the mapping of energy resources obtained with Geographic information techniques and using the outputs of methodologies developed for the characterization of wind a solar potential in urban areas. To this end, interactive tools were developed in a way that enables the user to change the input data (maps of wind and solar energy resource) and to vary the selection parameters. It is also possible to introduce other restrictions on the installation of renewable electricity generation systems, since they can be adapted to the format accepted as input in any geographical information system platform. The developed tools allow in a first phase, the identification of wind power and solar PV available as independent systems. In a second phase the identification and quantification of the wind and solar PV joint potential were performed assuming that both systems can be installed together. The methodology here presented-despite the fact that it was applied to a city scale-can be applied to large-sized areas, i.e. counties or provinces.
The methods are simple and easy to apply, as desired, and constitute an asset for the energy planning of cities in a Smart Cities context by integrating wind and solar photovoltaic systems in these environments.
It is important to notice that the presented method was developed for planning purposes and, in this sense, to identify suitable places for renewable energies installation. For investment decision, more detailed studies are needed, using local measurements for a more accurate project evaluation.