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Energy conversion from conventional ground-mounted photovoltaic systems requires a significant amount of land, which can compete with food production. Agrivoltaic systems, which integrate electricity generation and crop production, can help reduce this land competition. The profitability of agrivoltaic systems is expected to be a crucial factor for decision-makers and stakeholders considering their adoption. This work aims to analyze the economic performance of one-axis, vertical and elevated agrivoltaic systems compared to conventional ground-mounted photovoltaic systems across Europe focusing on countries such as Sweden, Denmark, Germany and Italy. By employing a stochastic approach with Monte Carlo simulations, this research makes a significant contribution to forecasting the profitability and cost-effectiveness of agrivoltaic projects in European countries for the next years. Moreover, it identifies the key parameters that significantly impact the net present value and levelized cost of electricity. The economic findings reveal a notable trend: agrivoltaic projects (i.e., one-axis, vertical, and elevated) are likely to be profitable throughout Europe. However, the agricultural profit generated from these systems is minimal for the investigated crop rotations compared to the benefits derived from energy conversion. Among the systems evaluated, one-axis agrivoltaic setups demonstrate higher profitability and cost-effectiveness compared to vertical and elevated setups. They also have a shorter discounted payback period and a lower levelized cost of electricity than conventional ground-mounted photovoltaic systems. These findings are particularly significant for decision-makers and stakeholders involved in developing agrivoltaic policies. This is especially relevant for Sweden which currently lacks agrivoltaic policies, regulations, and definitions, in contrast to Germany and Italy where policies for promoting agrivoltaics have previously been implemented or are in progress. 

Agrivoltaic systems combine food production and solar energy conversion on the same land, offering a dual-use approach to address land use concerns in renewable energy development. One of the main research and market challenges for agrivoltaic systems is the ability to predict food and energy yields prior to installation. The photovoltaic modules reduce solar irradiation on the ground, altering the energy balance at the ground and crop levels, affecting thus evapotranspiration and photosynthesis. The photovoltaic modules also influence local rain distribution and wind patterns, creating a microclimate that impacts both crop production and photovoltaic efficiency. The need to evaluate these effects and their impact on crop growth before installation is underscored by the recent implementation of new standards, guidelines, and regulations governing agrivoltaic systems in various regions. This study provides a critical review of existing research with a focus on the modelling, simulation, and optimisation of agrivoltaic systems. It highlights recent advancements in simulating and optimising the design of agrivoltaic systems through integrated simulations of shading, microclimates, electrical performance, and agricultural productivity. This study highlights the critical role of optimised light distribution in enhancing both crop yields and electricity production within agrivoltaic systems. However, the diversity of modelling approaches from the PV and agricultural sectors, coupled with the absence of standardised benchmarks, complicates the selection of appropriate models for specific systems and conditions. Future research should prioritise the development of standardised benchmarks to enable consistent comparisons across models, facilitating a better understanding of trade-offs between computational efficiency, interpretability, and accuracy. Collaborative efforts, publicly available datasets, and benchmarking initiatives are essential for validating models across diverse agrivoltaic configurations and regions.

In recent years, power systems have been experiencing shutdowns triggered by high-impact, low-probability events resulting from climate change. These incidents have a negative impact on system infrastructure and lead to significant economic losses. Thus, the power community has accelerated research on mitigating these impacts on power systems. This paper presents an extensive review of recent literature on the evaluation, metrics, and enhancement of power system resilience. To improve power system resilience, this paper discusses hardening and operational strategies for various groups, addressing the main challenges. Hardening strategies focus on the physical hardiness of the power grid and aim to reduce the magnitude of high-impact, low-probability events, while operational strategies aim to minimize restoration time. Additionally, the paper examines microgrid strategies for enhancing power system resilience, classifying them based on local and global resilience and providing a detailed comparison of microgrids for global resilience-based restoration and microgrids for local resilience-based self-healing strategies. This paper presents the different objective functions, constraints, and optimization methods used in the modelling process. Moreover, the evaluation metrics to assess resilience are examined. The research shows that microgrid technology has a high potential to improve power system resiliency against major events.

Microgrids have been developing nowadays as aninitiative aiming to operate modern power distribution systemsmore reliably and efficiently. With the decreasing price ofbattery energy storage systems (BESSs), BESSs are highlyrecommended to be exploited in the operation of microgrids inthe distribution network system. The advancements in BESS,increasing trends of distributed generation, and proliferation ofthe prosumer community require effective energy utilization inthe microgrid paradigm. The Peer-to-Peer (P2P) energy tradingmechanism establishes a marketplace where prosumers canengage in energy transactions, reduce energy consumption costsand increase resilience. However, it leads to a complicatedproblem particularly when multi-energy systems participate theenergy trading. In previous studies, P2P trading models havebeen primarily considered with only prosumers possessingrenewable energy resources. However, it is believed thatdynamic components such as BESS and the Distribution SystemOperator (DSO) will continue to have a significant role in theLocal Energy Market (LEM). This paper therefore proposes atrading model in a prosumers-based P2P in the LEM thatincludes several local energy providers and pure energyconsumers, in addition to a market community coordinatorwhich is namely a P2P market manager (P2PM). In theproposed market model, each prosumer is considered a marketparticipant, who tends to negotiate with each other in a way thatfollows their benefits. Each prosumer has a different distributedgenerator photovoltaic (PV), wind turbine, and storage unit tosatisfy its load demand. To handle the market clearing andenergy balance problem, the P2PM is responsible for theimplementation of functions for the centralized problem of theP2P model. The results of two different cases for the proposedLEM scheme are compared to verify the effectiveness of thesolution.

Agrivoltaic systems represent an intelligent solution combining electricity production from solar photovoltaic technology with agricultural production to avoid land use conflicts. Geographic Information System technologies can support the implementation and spread of agrivoltaic systems by identifying the most suitable areas using useful spatially explicit information concerning techno-agro-socio-economic criteria. In this study, we have developed a procedure to identify and classify suitable areas for agrivoltaic systems in Sweden. An Ordinal Priority Approach based multi-criteria decision-making algorithm is established to calculate the weights of the selected evaluation criteria through expert interviews. The land use data refers to the Corine Land Cover 2018 product. The results show that about 8.6% of the Swedish territory, approximately 38,485 km2, is suitable for installing agrivoltaic systems. Among this area, about 0.2% is classified as “excellent”, about 15% as “very good”, about 72% as “good”, about 13% as “moderate”, and about 0.1% as “poor”. Most “excellent”-classified areas are in Kalmar, Skåne, and Gotland. In contrast, most “very good” sites are in Skåne, Kalmar, and Östergötland. By deploying vertically mounted agrivoltaic systems with bifacial photovoltaic modules, the total potential installed capacity for “excellent” areas is about 2.5 GWp, while for areas classified “excellent” and “very good” is about 221 GWp. The total “excellent” areas can potentially supply about 2.4 TWh of electricity against the electricity consumption in 2021 of about 143 TWh. On the other hand, the land classified as “excellent” and “very good” could potentially provide about 207 TWh. The County of Västra Götaland shows the greatest potentials in terms of total potential electricity supply from agrivoltaic systems with about 227 TWh, followed by Skåne with a total potential of 206 TWh. 

With growing gas and oil prices, electricity generation based on these fossil fuels is becoming increasingly expensive. Furthermore, the vision of natural gas as a transition fuel is subject to many constraints and uncertainties of economic, environmental, and geopolitical nature. Consequently, renewable energies such as solar and wind power are expected to reach new records of installed capacity over the upcoming years. Considering the above, North Africa is one of the regions with the largest renewable resource potential globally. While extensively studied in the literature, these resources remain underutilized. Thus, to contribute to their future successful deployment and integration with the power system, this study presents a spatial and temporal analysis of the nature of solar and wind resources over North Africa from the perspective of energy droughts. Both the frequency and maximal duration of energy droughts are addressed. Both aspects of renewables’ variable nature have been evaluated in the North Atlantic Oscillation (NAO) context. The analysis considers the period between 1960 and 2020 based on hourly reanalysis data (i.e., near-surface shortwave irradiation, wind speed, and air temperature) and the Hurrel NAO index. The findings show an in-phase relationship between solar power and winter NAO index, particularly over the coastal regions in western North Africa and opposite patterns in its eastern part. For wind energy, the connection with NAO has a more zonal pattern, with negative correlations in the north and positive correlations in the south. Solar energy droughts dominate northern Tunisia, Algeria, and Morocco, while wind energy droughts mainly occur in the Atlas Mountains range. On average, solar energy droughts tend not to exceed 2–3 consecutive days, with the longest extending for five days. Wind energy droughts can be as prolonged as 80 days (Atlas Mountains). Hybridizing solar and wind energy reduces the potential for energy droughts significantly. At the same time, the correlation between their occurrence and the NAO index remains low. These findings show the potential for substantial resilience to inter-annual climate variability, which could benefit the future stability of renewables-dominated power systems. 

Agrivoltaic systems emerge as a promising solution to the ongoing conflict between allocating agricultural land for food production and establishing solar parks. This field experiment, conducted during the spring and summer seasons of 2023, aims to showcase barley production in a vertical agrivoltaic system compared to open-field reference conditions at Kärrbo Prästgård, near Västerås, Sweden. The dataset presented in this article encompasses both barley kernel and straw yields, kernel crude protein levels, starch content in kernels and thousand kernel weight. All collected data underwent analysis of variance (ANOVA) with Tukey pairwise comparison when possible, using dedicated software RStudio 4.3.2. This dataset article illustrates the effects of the vertical agrivoltaic design system on barley productivity. Interested researchers can benefit from this data to better comprehend barley yield under this specific agrivoltaic design and conduct further analyses and comparisons with yields from different locations or design configurations. The experimental data holds the potential to foster collaborations and advance research in agrivoltaic systems, providing a valuable resource for anyone interested in the subject. It was observed that the mean barley yield in all the different areas of the vertical agrivoltaic system were higher than the one in the control area. Additionally, weather and solar irradiance data collected during the growing season are provided in the repository for further usage.

Agrivoltaic systems, which allow the coexistence of crop and electricity production on the same land, are an integrated water–energy–food nexus solution that allows the simultaneous attainment of conflicting Sustainable Development Goals. This study aims to analyse experimental results on the responses of ley grass yield and quality to shadings in the first agrivoltaic system in Sweden. It also aims to validate an integrated modelling platform for assessing agrivoltaic systems' performances before installation. An economic analysis is carried out to compare the profitability of agrivoltaic versus conventional ground-mounted photovoltaic systems and, using a Monte Carlo Analysis, to identify the parameters that most affect the profitability. Despite the agrivoltaic systems’ supporting structures and photovoltaic modules producing an average ∼25% reduction in photosynthetically active radiation at ground level, no statistically significant difference was observed between the yield of the samples under the agrivoltaic system compared to the yield of the samples in the reference area. The agrivoltaic system attained land equivalent ratios of 1.27 and 1.39 in 2021 and 2022, respectively. The validation results of the integrated modelling platform show that the sub-model concerning the crop yield response to shading conditions tends to underestimate ∼7% the actual average crop yield under the agrivoltaic system. The results of the economic analysis show that, from a net present value perspective, agrivoltaic systems have a profitability that is ∼30 times higher than a conventional crop rotation in Sweden.

The integration of renewable energy sources into the goal of sustainable energy significantly alters power systems, necessitating the development of innovative approaches to ensure grid stability. The emergence of grid-forming technology is a disruptive approach that deviates from conventional grid-following methods, facilitating autonomous operation. The decoupling of power generation from frequency and voltage enables the utilization of decentralized resources such as solar energy, hence improving grid stability in the face of variations caused by renewable sources. This paper examines current developments in various aspects, including principles, control techniques, microgrid resilience, flexibility in both grid-connected and islanded modes and the problems associated with these breakthroughs. It highlights the significant capacity of grid-forming converters to drive transformational changes in the development of resilience. It is strongly recommended that stakeholders from academic, business, and policy sectors use this technology to facilitate the smooth integration of renewable energy sources and ensure the power grid’s resilience.

In recent years, power systems have suffered powerfailures caused by severe weather conditions resulting fromclimate change and global warming. These events can negativelyaffect the system equipment and lead to significant financial losses.Thus, mitigating these impacts on power systems using microgridswill help avoid power outages and ensure continuity of service.This paper presents a case study where the resilience of themicrogrid based on a modified IEEE 37-bus feeder test system istested and evaluated as performance indices without renewableenergy resources. The proposed scenario mainly relies onconventional distributed generators as a resource to restorecritical loads during night interruptions. The proposed frameworkuses two optimization algorithms to maximize the number ofrestored critical loads when faults occur in multi-location. Theperformed research lays out the importance of microgrids fordistributed systems in the context of resilience, including differentfaults.