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In order to perform predictions of a photovoltaic (PV) system power production, a neural network architecture system using the Nonlinear Autoregressive with eXogenous inputs (NARX) model is implemented using not only local meteorological data but also measurements of neighbouring PV systems as inputs. Input configurations are compared to assess the effects of the different inputs. The added value of the information of the neighbouring PV systems has demonstrated to further improve the accuracy of predictions for both winter and summer seasons. Additionally, forecasts up to 1 month are tested and compared with a persistence model. Normalized root mean square errors (nRMSE) ranged between 9% and 25%, with the NARX model clearly outperforming the persistence model for forecast horizons greater than 15min.

Renewable energy is the cornerstone of preventing dangerous climate change whilst main- taining a robust energy supply. Tidal energy will arguably play a critical role in the renewable energy portfolio as it is both predictable and reliable, and can be put in place across the globe. However, installation may impact the local and regional ecology via changes in tidal dynamics, sediment transport pathways or bathymetric changes. In or- der to mitigate these eects, tidal energy devices need to be modelled in order to predict hydrodynamic changes. Robust mesh generation is a fundamental component required for developing simulations with high accuracy. However, mesh generation for coastal domains can be an elaborate procedure. Here, we describe an approach combining mesh generators with Geographical Information Systems. We demonstrate robustness and e - ciency by constructing a mesh with which to examine the potential environmental impact of a tidal turbine farm installation in the Orkney Islands. The mesh is then used with two well-validated ocean models, to compare their ow predictions with and without a turbine array. The results demonstrate that it is possible to create an easy-to-use tool to generate high-quality meshes for combined coastal engineering, here tidal turbines, and coastal ocean simulations.

The transition to renewable energy systems causes increased decentralization of the energy supply. Solar parks are built to increase renewable energy penetration and to supply local communities that become increasingly self-sufficient. These parks are generally installed in rural areas where electricity grid distribution capacity is limited. This causes the produced energy to create grid congestion. Temporary storage can be a solution. In addition to batteries, which are most suitable for intraday storage, hydrogen provides a long-term storage option and can be used to overcome seasonal mismatches in supply and demand. In this paper, we examine the operational decisions related to storing energy using hydrogen, and buying from or selling to the grid considering grid capacity limitations. We model the problem as a Markov decision process taking into account seasonal production and demand patterns, uncertain solar energy generation, and local electricity prices. We show that ignoring seasonal demand and production patterns is suboptimal. In addition, we show that the introduction of a hydrogen storage facility for a solar farm in rural areas may lead to positive profits, whereas this is loss-making without storage facilities. In a sensitivity analysis, we show that only if distribution capacity is too small, hydrogen storage does not lead to profits and reduced congestion at the cable connection. When the distribution capacity is constrained, a higher storage capacity leads to more buying-related actions from the electricity grid to prevent future shortages and to exploit price differences. This leads to more congestion at the connected cable and is an important insight for policy-makers and net-operators.

Since 2010 the Dutch photovoltaic (PV) market has been growing fast, with around doubling of installed capacity in 2011 and 2012. Four quarterly inventories have been made in 2012 for modules, inverters, and systems that are presently available for purchase in the Netherlands. We have found that the average selling price of modules, inverters, and systems decreased with 44.3, 14, and 7.3-10.2%, respectively: average selling prices are 1.26 €/Wp, 0.41 €/Wp, and 1.46 €/Wp for modules, inverters, and systems on tilted roofs, respectively, at the end of 2012. Average installation costs amount to 0.43 €/Wp. Using an energy yield of 900 kWh/kWp, 25 years system lifetime, 6% discount rate, and 1% operation and maintenance (O&M) cost, a levelized cost of electricity (LCOE) is calculated for a 2.5. kWp system to be 0.194 €/kWh for a system price of 1.98 €/Wp (including installation). Grid parity conditions are apparent, with electricity retail prices of around 0.23 €/kWh.

textabstractIn Europe, Germany is taking the lead in the switch from fossil and nuclear energy to renewables. This creates new challenges as wind and solar energy are fundamentally intermittent and to some degree, unpredictable. It is therefore of considerable interest to investigate what effect these changes have on the overall trend and volatility of the electricity price. While market coupling promises to reduce price volatility, dependence on renewable energy sources (RES) might have the opposite effect. To elucidate the combined impact of these two developments, we investigate the evolution of the electricity price on the German day-ahead market over the course of the last 11 years (2006-2016). Our main observations are that price volatility has decreased rather than increased. Furthermore, excess wind production during off-peak hours correlates well with the occurrence of negative prices. Finally, daily price profiles show a gradual shift in peak- prices away from the day-light hours, and this shift is more pronounced during the summer than in winter. This points to a growing influence of solar production on prices.

The Netherlands aims to be CO2 neutral by 2050, aligning with the Paris Agreement. To achieve this, it is crucial to increase the contribution of geothermal energy to renewable energy sources, necessitating large-scale exploitation to speed up the energy transition. Only small-scale (1–2 km) geothermal field developments exist in the Netherlands primarily for heating. Expanding to extensive geothermal fields (>10 km length) requires a strategic approach to well placement and consideration of the economic constraints associated with geothermal projects. The heterogeneity of the subsurface is a critical factor in developing large-scale geothermal reservoirs. This study introduces an innovative approach to optimising well placement based on geological trends, using a well-density function as a proof of concept. Implementing and optimising flexible well patterns for large-scale geothermal developments significantly enhances profitability compared to conventional oil and gas industry methods. Optimised flexible well patterns favour a long-term utilisation of energy recovered, minimise pressure extrema in the reservoir, and improve sweep efficiency. However, their application depends on reservoir operational decisions. The optimisation process ensures economic viability, even with lower heat prices. Broadly, this methodology could be key to scaling up geothermal developments to meet the objectives of the Paris Agreement. © 2025 The Authors

The application of renewable energy technologies (RETs) in the residential building sector requires acceptance of technical solutions by key stakeholders, such as building owners, real-estate developers, and energy providers. The objective of this study is to identify the current status of public perceptions of RETs that are available in the Finnish market and associated influencing factors, such as perceived reliability, investment cost, payback time, and national incentives. A web-based questionnaire was disseminated to the general public in the Helsinki Metropolitan Area (n = 246). Social perceptions of building-integrated RETs were evaluated through integration of survey data and Stochastic Multicriteria Acceptability Analysis (SMAA), which was applied to analyse the robustness of the survey results. The SMAA demonstrated that Finnish residents exhibit broad acceptance of multiple options, rather than preference for a single RET. Solar technologies and ground source heat pumps were the most preferred options and evaluated as very reliable, whereas wind-based technologies and combined heat and power were ranked as the least popular. In general, respondents indicated a strong willingness to financially invest in RETs as a means to reduce their carbon footprint and preferred tax deductions as an incentive to invest in RETs.