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4.3 Decision support for urban energy planning and subsidization

In this section8, we will focus on the decision-making process related to solar energy and building energy refurbishment. We have seen that many works focused on the assessment methods, while the subsequent use of the information to take a decision is usually neglected.

Solar cadastres are meant to answer the most typical questions asked by building owners: “Is my building suitable for energy installations?”; “If yes, how much could I produce?”. Energy planning tools are meant to answer a wider range of questions from a wider range of different stakeholders.

Finally, some of the stakeholders are often faced to the allocation of limited resources to encourage the deployment fo solar energy. Despite the huge potential of solar energy, its yield is often limited or slowed by practical limitations, related for example to regulation, funding and design constraints. Given a restricted number of resources, which can be intended for example as incentives but also as spatial locations, it is interesting to analyze the possible allocation methods. Therefore, we review some of the most typical allocation mechanisms.

We are also interested in allocation methods as a way to assign public incentives to boost the use of renewable energy. These public incentives are not necessarily monetary. Governments in fact can play a role through “subsidies, tax breaks, infrastructural allocation, preferential credit treatment, and permissions or licenses” [80].

4.3.1 Solar cadastres

A solar cadastres or solar map is “a GIS system providing the annual solar irradiation on building surfaces (roofs and/or facades), mostly accompanied by the output of solar thermal or photovoltaic systems, and connected to a website” [140].

Solar cadastres (or solar maps) are tools to provide decision-makers with information about the suitability of a given surface for the installation of solar power systems, such as photovoltaic or solar thermal. They are usually conceived as web-based mapping tools in which the solar potential is displayed as false-colors overlays on maps or ortho-photos of an urban area. Dean et al. [67], Jakubiec and Reinhart [132], Kanters et al. [140] provide an extensive review of solar cadastres in the United States and Europe. The long list of available solar cadastres indicates also the popularity of these instruments among many local authorities, which use them as part of their public investment strategies to encourage the use of solar energy (Section 2.4).

Most of the cadastres in the US listed by [132] are based on raster models using r.sun [248] or PVWatts [73] and they are targeted to roofs. A Daysim-based method [132] has been integrated in the Mapdwell solar cadastre [22], also targeted to roofs. Despite the earlier research on façade analysis (e.g., Carneiro et al. [46], Catita et al. [49]), the interest of solar cadastres is still mainly roofs, arguably for financial reasons. However the Swiss confederation recently released a country-wide solar cadastre (referred in this thesis as SFSC) including both façades and roofs. Despite the advanced 3D information (Ap- pendix A.1.4) used for the analysis, the visualization is still 2D. Its features will be more extensively described in a comparison with this thesis proposed method in Section 13.3.

8_{This section contains some excerpts from a published journal paper [226]: Peronato, G., Rastogi, P., Rey, E., & Andersen, M.}

(2018). A toolkit for multi-scale mapping of the solar energy-generation potential of buildings in urban environments under uncertainty. Solar Energy, 173, 861–874. https://doi.org/10.1016/j.solener.2018.08.017. The text is reproduced here as a courtesy of the publisher and with the agreement of the co-authors. G.P. contributed by conducting and writing the review.

Chapter 4. State of the art

As shown by Kanters et al. [140], the suitability assessment of solar cadastres is generally based on minimum irradiation thresholds. In some cases, the choice of these thresholds is justified by financial assessments to guarantee the payback time of the installation [195, 132, 22]. Surfaces are often classified with different levels of suitability depending on their solar irradiation, such as “reasonable”, “good”, “very good” [140].

As we will see in Chapter 6, error, risk, and uncertainty vary depending on the selected threshold. However, solar cadastres generally have a deterministic approach, which neglects the uncertainty of the result and the concomitant risk in the decision. Thresholds are also sensitive to the geometric regularity of the arrangement of solar modules, an aspect that we will investigated in Section 11.3.3.3. In addition to thresholds, another method to provide information about solar potential is to attribute to each building a solar score. The solar score is usually calculated by reference to a best-case installation, as in the Mapdwell solar maps [22], or by normalizing the data to the best and worst values in a given location, as in the SunNumber website [182]. This method facilitates comparisons between locations with non-homogeneous climate conditions as the score is relative to the specific conditions, allowing cross-country comparisons. However, the score still disregards other factors of uncertainty in the calculation which affect each building differently, such as vegetation modeling.

Solar cadastres focus on the potential of individual buildings, and in some cases differentiate the potential among the surfaces constituting the building envelope, while neglecting the aggregated potential of urban blocks or entire urban areas. They are targeted in fact to building owners, and often have an educational goal [67]. They are sometimes used as back-end planning tools by municipalities, though mostly limited to the evaluation of their own real estate properties [140] rather than planning purposes.

4.3.2 Online PV calculators

Online PV calculators are complementary tools to solar cadastres, which can be used both by building owners and solar energy professionals to have a quick estimate of the solar energy potential of a given solar energy installation. Unlike solar cadastres, they usually have a simplified modeling of shading geometry, using for example angle-based obstructions for the horizon, but allow the user to design a custom installation (e.g., by choosing the tilt and size of the array).

The most popular online PV calculators are PV-GIS [249], which is based on the r.sun model [248] (see also Section 4.1.1), and PVWatts, which is based on the homonym model developed at NREL [73] (see also Section 2.2.6.3).

PV-GIS originally provided radiation databases for Europe and Africa and only recently introduced a worldwide radiation database, while PVWatts natively supports the entire world but it is focused on the US market. There are also country-specific tools, which provide typical parameters for the local context. For example, the calculator of Swissolar [294] also estimates the investment cost, incentives and tax deductions for Switzerland.

4.3.3 Energy-planning tools

Compared to solar cadastres and PV calculators, energy-planning tools focus more explicitly on a wider range of stakeholders, particularly utility companies, and municipalities. Ouhajjou et al. [205] reviewed

4.3. Decision support for urban energy planning and subsidization

some of these tools focusing on the integration of energy systems in urban environments (Table 4.11, 1-6).

Among these tools, Semergy [176] is particularly interesting as it is focused on the building energy refurbishment process. It provides a multi-objective optimization environment that helps choose the best renovation strategy. However, the tool is mostly intended to building-scale analyses, while the related city-planning tool (Ecocities) has been only recently developed. However, both software have only a partial support for PV integration strategies.

Ouhajjou et al. [204, 206, 207] proposed an ontology-based urban energy planning providing a classifi- cation of the PV-suitability of buildings from each stakeholder’s perspective. However, this method then focuses on negotiation and consensus between the different stakeholders rather than the robustness of the single decision.

Fonseca et al. [86] developed a tool for the analysis and optimization of building energy systems, packaged as a ArcGis plugin. The tool, called City Energy Analyst, is still growing and expanding its features, which span from advanced energy modeling (including Life Cycle Analysis) to decision support, through multi-criteria assessment, 3D visualization and benchmarking. It recently included a module for PV simulation based on Daysim, while the platform is oriented towards the integration of multiple energy sources. Hong et al. [113] (CityBES) and Cerezo et al. [53] developed tools that are oriented to the city-scale building energy modeling, with a focus on retrofit and other energy interventions on existing buildings.

Ranalli et al. [239] coupled SAM technical-economical modeling. Through GIS spatial analysis, they created different scenarios (e.g. use of East-West-tilted roofs) to inform decision-makers on different planning policies to adopt. There is however a gap between the techno-economical analysis and the GIS analysis, which is limited on classifications based on tilt, azimuth, orientation rather than on modeling context-specific solar irradiation.

With the notable exceptions of CEA and CityBES, it seems that the reviewed tools are focused on techno- economical modeling or optimization, rather than on the integration between physical modeling and visualization-oriented decision-making. It seems thus that there is a double gap with, on the one hand, the most advanced solar radiation models seen in Section 4.1.1 and 3D geometry described in Sec- tion 2.3.3.2, and, on the other, with the user-friendly web interfaces of solar cadastres of (Section 4.3.1) and PV calculators (Section 4.3.2).

4.3.4 Allocation mechanisms

In the field of solar and building energy refurbishment subsidies9, we find many of the mechanisms that were listed in Section 2.5.1

Funding for public policies encouraging renewable energy and building renovation is usually limited [116] and the demand cannot be completely satisfied. For solar energy, we can cite the cases of Switzerland [141] and Austria[157], which were forced to adopt waiting lists to face the high number of requests for feed-in tariff. These waiting lists are a consequence of a cap in the total amount of subsidies that can allocated.

9_{The DSIRE website website lists all incentive programs and policies promoting renewable energy and energy efficiency in}

Chapter 4. State of the art

Table 4.11 – Non-exhaustive list of energy planning tools.

Table adapted and updated from Ouhajjou et al. [204]

Study Main focus Scale

1 EnerGis [94] Evaluation of building energy needs City 2 SynCity [144] Modeling of urban energy systems City 3 UrbanSim [310] Land-use scenarios development City 4 CommunityViz [160] Policy scenarios development City 5 Semergy [176] Automatic data retrieving + refurbishment decision support Building

6 MEU [43, 213] Optimization of energy flows based on CitySim [256] Neighborhood/City 7 Ouhajjou et al. [204] Ontology-based planning support for PV deployment Neighborhood/City 8 City Energy Analyst (CEA) [86] GIS-based optimization of building energy systems Neighborhood/City 9 CityBES [113] Building energy modeling supporting energy retrofit mea-

sures Neighborhood/City

10 Cerezo et al. [53] Building energy modeling supporting energy interventions

(PV and demand side management) Neighborhood/City 11 Ranalli et al. [239] GIS-based decision support for solar potential Neighborhood/City

Alternative methods are also used, such as competitive bids and lotteries. For example, a former Oregon state incentive program for PV10used the former for small systems (5-10 kWp) and the latter for the larger systems.

In some cases, waiting lists are complemented by other allocation methods. A common pre-allocation method is to limit incentives only to interventions achieving a given threshold. This is for example the case for subsidies which require for PV a minimum peak-power installed (e.g. in Oregon, see footnote 10), and for building energy refurbishment a minimum intervention to be implemented (e.g. target U-value of the envelope11). This corresponds to a minimum cost to be paid by the participants to join the incentive program, i.e. their willigness to pay.

In some cases, this target level can be considered as skill, as it is not defined directly by a minimum design requirement but rather as the output of the design. This is for example the case of a maximum energy demand requirement or target energy label after the refurbishment (see for example the case of Neuchâtel in footnote 11), which can be reached by different design approaches, corresponding to different investments. The skill of the participant is to reach these requirements with the least investment. However, since post-occupancy evaluations are too difficult to implement, the evaluation is usually done through simplified assessments before submitting the building permit.

Similarly, the California Energy Commission assigns incentives and rebates for PV based on analysis using different performance models [153]: they use PVWatts [73] for existing buildings in their California Solar Initiative (CS) and the 5-parameter model [66], coupled with an inverter model, for the New Solar Homes Partnership (NSHP) program12

However, in most other cases, PV subsidies are generally allocated based on the total peak-power installed, with a minimum installation size being necessary to get access to the subsidizing scheme. This criterion does not need any calculation to be done, as it is based only on the size of the system. Moreover, the peak power is not necessarily the maximum power, as at lower temperatures or higher radiation intensities than the Standard Test Conditions the value can be exceeded [96, p. 89]. Access to subsidies is granted based on the willingness to pay, regardless on the actual production (or skill) of the

10_{http://programs.dsireusa.org/system/program/detail/3564 [Last accessed on April 22, 2018]}

11_{The canton of Neuchâtel has different calculation systems based to assign incentives within the “Building Program”}

(Section 3.4.1.1): one based on standard maximum transmittance requirements for the envelope, and other two based on the global energy performance as defined CECB© and the Minergie© label systems.

12_{These models have been discussed in Section 2.2.6.3.}