a b s t r a c tIntegrated spatial and energy planning has become a major field of interest to meet the current renewable energy share expansion and CO 2 emissions reduction targets. Geographic Information Systems (GIS) play a considerable role in supporting decision making in this field. Solar potential maps are a popular strategy to promote renewable energy generation through photovoltaic (PV) panel installations at city and municipal scales. They indicate the areas of roofs that would provide the maximum amount of energy in kW h per year. These are often used to suggest ''optimal locations'' for PV-panels and/or recommend system sizes to achieve a certain level of yearly autarchy. This approach is acceptable if PVs have only a minor share in the local energy supply system. However, increased PV-penetration can lead to instability of the local grid, create hazards for the security of the supply, and considerably escalate the storage and system back-up requirements. To obtain a proper understanding of the consequences for the local energy balance when selecting or rejecting a certain installation, examining the hourly and intra-hourly time series of the potential energy generation from PVs is necessary. This paper introduces a GIS-based procedure to estimate the potential PV-electricity generation time series for every roof-top section within a study area using open source software. This procedure is complemented by a series of strategies to select suitable PV-installations considering the time series analysis of supply and demand. Furthermore, thirteen technical indicators are considered to evaluate the PV-installation sets selected with every strategy. The capabilities of the procedure are tested using data from a German rural municipality. The proposed procedure constitutes an efficient and accessible way to assess solar potentials at the municipal scale and to design roof-top PV exploitation plans, which are more appropriate to fulfill the local energy requirements.
In recent years, with the increased focus on climate protection, electric vehicles (EVs) have become a relevant alternative to conventional motorized vehicles. Even though the market share of EVs is still comparatively low, there are ongoing considerations for integrating EVs in transportation systems. Along with pushing EV sales numbers, the installation of charging infrastructure is necessary. This paper presents a user- and destination-based approach for locating charging stations (CSs) for EVs—the electric charging demand location (ECDL) model. With regard to the daily activities of potential EV users, potential positions for CSs are derived on a micro-location level in public and semipublic spaces using geographic information systems (GIS). Depending on the vehicle users’ dwell times and visiting frequencies at potential points of interest (POIs), the charging demand at such locations is calculated. The model is mainly based on a survey analyzing the average time spent per daily activity, regional data about driver and vehicle ownership numbers, and the georeferenced localization of regularly visited POIs. Optimal sites for parking and charging EVs within the POIs neighborhood are selected based on walking distance calculations, including spatial neighborhood effects, such as the density of POIs. In a case study in southeastern Germany, the model identifies concrete places with the highest overall demand for CSs, resulting in an extensive coverage of the electric energy demand while considering as many destinations within the acceptable walking distance threshold as possible.
Abstract. This study presents a framework for regional smart energy
planning for the optimal location and sizing of small hybrid systems. By
using an optimization model – in combination with weather data – various
local energy systems are simulated using the Calliope and PyPSA energy
system simulation tools. The optimization and simulation models are fed with
GIS data from different volunteered geographic information projects,
including OpenStreetMap. These allow automatic allocation of specific demand
profiles to diverse OpenStreetMap building categories. Moreover, based on
the characteristics of the OpenStreetMap data, a set of possible distributed
energy resources, including renewables and fossil-fueled generators, is
defined for each building category. The optimization model can be applied
for a set of scenarios based on different assumptions on electricity prices
and technologies. Moreover, to assess the impact of the scenarios on the
current distribution infrastructure, a simulation model of the low- and
medium-voltage network is conducted. Finally, to facilitate their
dissemination, the results of the simulation are stored in a PostgreSQL
database, before they are delivered by a RESTful Laravel Server and
displayed in an angular web application.
Spatial assessments of the potential of renewable energy sources (RES) have become a valuable information basis for policy and decision-making. These studies, however, do not explicitly consider the variability in time of RES such as solar energy or wind. Until now, the focus is usually given to economic profitability based on yearly balances, which do not allow a comprehensive examination of RES-technologies complementarity. Incrementing temporal resolution of energy output estimation will permit to plan the aggregation of a diverse pool of RES plants i.e., to conceive a system as a virtual power plant (VPP). This paper presents a spatiotemporal analysis methodology to estimate RES potential of municipalities. The methodology relies on a combination of open source geographic information systems (GIS) processing tools and the in-memory array processing environment of Python and NumPy. Beyond the typical identification of suitable locations to build power plants, it is possible to define which of them are the best for a balanced local energy supply. A case study of a municipality, using spatial data with one square meter resolution and one hour temporal resolution, shows strong complementarity of photovoltaic and wind power. Furthermore, it is shown that a detailed deployment strategy of potential suitable locations for RES, calculated with modest computational requirements, can support municipalities to develop VPPs and improve security of supply.
Regional energy strategies in the conflict of economical, environmental and social interests on the example of Lower Bavaria Regionale Energiestrategien im Spannungsfeld ökonomischer, ökologischer und sozialer Interessen am Beispiel Niederbayern Roland Zink Les stratégies énergétiques régionales en Basse-Bavière face aux enjeux écono...
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