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The German government's goal of achieving climate neutrality by 2045 and increasing the use of renewable energy, particularly wind and solar power, has public support. However, the local siting of wind and solar farms is highly controversial due to land-use conflicts. We have developed a comprehensive Geographic Information System (GIS) model that integrates criteria from the literature to identify optimal locations for ground-mounted photovoltaic (GM-PV). The model is based on a holistic approach considering energy-related factors and broader environmental and climate aspects. The unique feature of the model is its integration of socio-technical and environmental criteria, including a novel approach to achieving a dual land-use climate benefit by protecting erosion-prone soils and conserving soil carbon in areas prone to organic matter decomposition and associated CO 2 release. Our multi-criteria GM-PV model includes 12 restrictions and five suitability criteria representing key socio-technical, economic and environmental aspects. Scenario analysis highlights the sensitivity of Germany's GM-PV potential to defined criteria. In Scenario 1, with minimal constraint, 14.2 % of Germany's land is available for GM-PV, decreasing to 1.9 % in the highly constrained Scenario 12. Suitable areas (>10 ha) account for 0.4 % of Germany's land area, which could cover 8.1 % of Germany's electricity consumption in 2045 in the highly restricted scenario. The spatial distribution results show that the innovative approach of the model changes the preference of GM-PV locations based on factors such as solar radiation in the south and soil carbon storage in the north of Germany. The application of restriction and suitability criteria significantly reduces the potential for GM-PV in Germany but also potential pitfalls for decision-makers. The GIS model can be applied in regional context to integrate stakeholder values and generate region-specific scenarios, as criteria and thresholds can be easily adapted to regional characteristics, preferences, and concerns, including those related to agriculture, biodiversity, and social acceptance. • The model considers climate aspects and integrates socio-technical and ecological criteria. • The novel approach includes soil erosion and CO 2 release from the decomposition of organic matter. • Ground-mounted PV meets at least 8.1 % of Germany's electricity demand in 2045, using 0.4 % of the country's land. • The innovative approach of the model changes the preferred locations for Ground-mounted PV. • The model can integrate stakeholders' local preferences and generate region-specific scenarios. [ABSTRACT FROM AUTHOR]

The electric grid's available capacity to accommodate solar photovoltaic on national scales is currently uncertain. This makes decisions about grid capacity expansion, which can be very costly for local grid operators, difficult to make. Yet, knowledge of national solar photovoltaic grid capacity is central in order to formulate realistic solar PV targets and strategies. We present a methodology based on publicly available data to estimate the grid's hosting capacity of residential solar photovoltaic at both the national and local scale. The model is applied to Sweden, Germany and the UK and shows that low-voltage grid capacity for residential solar photovoltaic is very large, 33 (+5/-7) GW (Sweden), 248 (+5/-24) GW (Germany) and 63 (+1/-14) GW UK, and similar to current total generation capacity. Based on our estimations, we find that with the capacity of the present grid Sweden can supply 24%, Germany 60% and UK 21% of their current annual net electricity consumption from residential solar photovoltaic. In addition, we find that the grid-supported individual solar PV system sizes increase as population density decreases. Finally, our work highlights the importance of implementing sizing incentives for customers when installing their solar PV systems. • We estimate national and local residential solar PV low-voltage grid capacity. • Estimate is done in Sweden, Germany and UK. • Low-voltage capacity for residential solar PV is similar to current installed total generation capacity. • Presents a method for generating synthetic low-voltage grids based on public data. • Low-voltage grid capacity varies significantly based on location. [ABSTRACT FROM AUTHOR]

In this study an intelligent energy supply system is developed. Energy is obtained by wind or solar radiation and stored to cover the electricity and heat demand of a detached house in Germany. For this a heat pump and a storage tank is used. The simulation shows strategies to integrate renewable energies in different regions of Germany while diminishing the need to turn off a wind turbine or feed energy to the grid. For this, the energy consumption in a single house is modelled. Different wind turbines and PV systems are introduced as an energy source. The profitability of these systems is calculated and compared to conventional systems with gas or oil. The analysis shows that at the moment small wind turbines are a feasible option for cover the energy demand under the given conditions. On the other hand, currently PV plants are not suitable for the heat demand coverage as the specific costs outgo the ones for conventional systems. Further research is necessary to look at different case scenarios, taking into account future climate developments. • Small wind turbines are feasible option to cover energy demand of detached houses. • At the moment PV systems are not suitable compared to conventional sources. • Critical component in economics is heat pump - > cost reduction is necessary. [ABSTRACT FROM AUTHOR]

We quantify the cost savings potential of photovoltaic self-consumption by single-family houses with small-scale roof-top photovoltaic systems in Germany against the background of recent storage applications after the end of the legal support period. We analyze different systems where an already installed PV system is combined with a battery storage and/or a power-to-heat solution. A comparison is made in terms of a household's electricity and heating costs under cost-minimizing operation of each system. For this purpose, we carry out comprehensive simulations of site-specific PV production and determine optimal self-consumption as well as optimal charging of the hot water thermal storage and the battery storage. We use 25 representative electricity load profiles, which differ only in temporal distribution of consumption, to obtain a broader picture of the cost savings potential. Results suggest that the major share of the savings potential is due to direct PV self-consumption and thus concerns electricity costs. A profitability analysis reveals that the inclusion of the thermal storage and/or the battery storage system does not pay off when juxtaposing cost savings and investment expenses, at least at current prices. However, since storage application prices are constantly falling, individual profitability is within reach for the next years. • Estimation of the cost savings potential of cross-sector use of residential PV. • Comparison of systems differing in the existence of battery and thermal storage. • Computation of electricity and heating costs for each system as well as self-sufficiency shares. • Consideration of temporal different electricity consumption profiles. [ABSTRACT FROM AUTHOR]

We present possible steps for Germany's capital region for a pathway towards high-level renewable energy contributions. To this end, we give an overview of the current energy policy and status of electricity generation and demand of two federal states: the capital city Berlin and the surrounding state of Brandenburg. In a second step we present alternative, feasible scenarios with focus on the years 2020 and 2030. All scenarios were numerically evaluated in hourly time steps using a cost optimisation approach. The required installed capacities in an 80% renewables scenario in the year 2020 consist of 8.8 GW wind energy, 4.8 GW photovoltaics, 0.4 GW bioenergy, 0.6 GW methanation and a gas storage capacity of 180 GWh. In order to meet a renewable electricity share of 100% in 2030, approximately 9.5 GW wind energy, 10.2 GW photovoltaics and 0.4 GW bioenergy will be needed, complemented by a methanation capacity of about 1.5 GW and gas storage of about 530 GWh. In 2030, an additional 11 GWh of battery storage capacity will be required. Approximately 3 GW of thermal gas power plants will be necessary to cover the residual load in both scenarios. Furthermore, we studied the transmission capacities of extra-high voltage transmission lines in a second simulation and found them to be sufficient for the energy distribution within the investigated region. [ABSTRACT FROM AUTHOR]