Renewable Capacity Research Articles

Forecasting China’s total renewable energy capacity using a novel dynamic fractional order discrete grey model

Accurately forecasting renewable energy capacity is crucial for informing national energy policies and promoting sustainable socio-economic growth. This study proposes a novel dynamic fractional-order discrete grey model (DFDGM (1,1)) for forecasting China's total renewable energy capacity. The model constructs a dynamic fractional time delay polynomial, which enhances the adaptability of the model to different sample sizes. The time response function of model is directly derived from the discrete equation, preventing errors caused by the transition from discreteness to continuity. Furthermore, the proposed model represents the unified form of six grey models, effectively expanding the model's application domain and scope. The method introduces a double error approach to facilitate optimal parameter selection, successfully addressing overfitting and randomness challenges in parameter selection. Empirical studies show that the proposed model outperforms eleven other methods, with fitting and forecasting errors of 0.39% and 1.13%, respectively. Finally, the proposed model forecasts the future development trend of China’s total renewable energy capacity. In general, this research not only improves the precision of predictions but also progresses the dynamic theory in prediction studies.

Psychomotor Skills-Self Renewal Capacity of Students with the PACE Model based on Project Based Learning

Psychomotor abilities in students' self renewal capacity are still low in competence in practicing MySQL databases so it is estimated that students have problems in completing the final assignment project in object oriented programming courses. This study aims to improve students' psychomotor abilities in completing their final project through the implementation of the use of the PACE model based on project based learning. PACE is a learning model based on constructiveness with phases: Project, Activity, Cooperative Learning and Exercise, this model is suitable to be combined with project based learning to increase students' self renewal capacity in doing programming practice. This type of research is descriptive with a qualitative approach. There were 23 students of the Informatics Engineering Education study program as the subject of this research. The results showed that the average score of students' psychomotor skills is 81,2% with very good criteria. Then Self renewal capacity shows a percentage of 71.7% with good criteria. In conclusion, the application of the PACE model based on Project Based Learning in object-oriented programming courses can be an alternative to increase self-renewal capacity in students' psychomotor abilities.

Optimization of integrated energy system considering multi-energy collaboration in carbon-free hydrogen port

Renewable energy is highly efficient, clean, and low-carbon, and it has become the key to energy transformation. The lack of renewable energy consumption capacity has become a major restriction on the development of renewable energy generation industry, and the application of hydrogen storage technology to port integrated energy systems (IES) is considered an effective solution to the problem of grid-connection of renewable energies. The application of hydrogen storage technology to improve renewable energy consumption and integrated energy use has important research significance. This paper studies optimization of the IES considering multi-energy collaboration in carbon-free hydrogen ports. Security constrained unit commitment (SCUC) is a key issue in the operation of IES. A mixed integer linear programming (MILP) model is constructed with objectives of minimizing the operating cost of energy system. Furthermore, a customized enhanced particle swarm optimization (PSO) method is designed to solve the SCUC optimization problem. Enhanced PSO can obtain satisfying solutions in large-scale instances within a short time. Extensive numerical experiments have been conducted and the results demonstrate the applicability and efficiency of enhanced PSO in solving problems.

T-Bet Overexpression Increases 4-1BB-Costimulated CAR T Cell Potency

Data from our lab and others has demonstrated that CAR T cells form a mixed Th1/Th2 population which, in contrast to canonical T cell differentiation, produce both interferon gamma (IFN-γ) and IL-4. Whereas a growing body of evidence has highlighted the importance of IFN-γ in the CAR T cell response, IL-4 can have immune-suppressive functions. IFN-γ from CD4+ CAR T cells (CAR4s), has been shown to promote cytotoxic effector functions of CD8+ CAR T cells (CAR8s), as well as bolster activation of endogenous immune cells including CD8 T cells and NK cells (Boulch et al Sci Immunol. 2021). Given the importance of IFN-γ to effective anti-tumor immune responses, we generated murine CAR T cells that target CD19 with a CD28 costimulatory domain (1928z) and compared them to CAR T cells that overexpress T-bet (T-bet-1928z) in an effort to skew CAR T cells away from IL-4 production and towards IFN-γ production. Upon stimulation of CAR T cells with the murine B-cell acute lymphoblastic leukemia (B-ALL) cell line E2A-PBX, fewer T-bet-1928z CAR4s produced IL-4 compared to 1928z CAR4s. This suggests T-bet overexpression is a viable strategy to reduce Th2-like programming of effector functions in CAR4s. To determine the impact of T-bet overexpression on early CAR T cell efficacy in vivo, we adoptively transferred 1928z or T-bet-1928z CAR T cells into leukemia-bearing C57Bl6/J recipients and analyzed CAR T cells from the bone marrow at peak expansion of CAR T cells as well as post-contraction. Both CARs eliminated CD19+ cells from the bone marrow and mediated long-term survival. T-bet-1928z CAR4s demonstrated increased expansion at Day 4 compared to 1928z CAR4s (p=0.0412), although there was no significant difference in CAR8 numbers at this timepoint. At Day 11 post-CAR, we observed an increase in the number of T-bet-1928z CAR T cells present in the bone marrow (p<0.0001), observed in both CAR4s (p<0.0001) and CAR8s (p=0.0074). While levels of memory-associated transcription factors TCF1 and FOXO1 were the same between CARs, fewer T-bet-1928z CAR T cells expressed IL7Rα (p=0.0002) and eomesodermin (p<0.0001), which are associated with the ability of T cells to self-renew and persist in the bone marrow. To determine the impact of T-bet on the persistence and renewal capacity of 1928z CAR T cells, we adoptively transferred 1928z or T-bet-1928z CAR T cells into leukemia-bearing RAG1-knockout recipients to eliminate endogenous T cell responses to E2A-PBX. After initial leukemia clearance, we rechallenged these mice with E2A-PBX and analyzed the bone marrow after 13 days. Both CARs were able to clear the leukemia rechallenge. While CAR4s were present in the bone marrow at similar numbers, the number of CAR8s was significantly higher among mice treated with T-bet-1928z CAR T cells (p=0.0317). Our results suggest that while T-bet may enhance in vivo expansion of CAR T cells, it provides no long-term benefit or deficit to the CAR T cell response. 4-1BB co-stimulated CAR T cells are less potent than CD28-costimulated CAR T cells and have reduced effector functions. We therefore hypothesized that T-bet overexpression would improve the efficacy of 4-1BB-costimulated CAR T cells by boosting effector functions and potency. To test this, we transduced T cells with a CAR targeting CD19 that contains a 4-1BB costimulatory domain (19BBz), or a 19BBz CAR and T-bet (19BBz-T-bet). We adoptively transferred 19BBz or 19BBz-T-bet CAR T cells into leukemia-bearing C57Bl6/J recipients. Despite no difference in CAR T cell numbers in the bone marrow, we observed fewer leukemia cells in mice treated with 19BBz-T-bet CAR T cells (p=0.0318) at Day 4 post-CAR. Treatment with 19BBz-T-bet CAR T cells also significantly improved survival of leukemia-bearing mice compared to 19BBz CAR T cells (p=0.0494). Our data demonstrate T-bet overexpression improves CD28-costimulated CAR T cell expansion but does little to augment long-term responses and diminishes features associated with capacity for self-renewal. In contrast, T-bet overexpression boosts the potency of 4-1BB-costimulated CAR T cells without impairing persistence, resulting in improved overall efficacy of 4-1BB-costimulated CAR T cell therapies.

A review of wind energy potential in Morocco: New challenges and perspectives

Morocco has a significant wind energy potential due to its favorable climate proximity to the Atlantic Ocean, and temperature conditions. The governments recognize the importance of transitioning to sustainable energy sources and have taken strategic steps to promote the renewable energy sector, particularly wind energy, to reduce dependence on finite fossil fuels and promote eco-friendly alternatives. Local and international enterprises, along with private investors, have undertaken various wind energy projects in the country. Despite overreliance on conventional resources like coal and gasoline leading to an energy crisis, Morocco sees wind energy as a viable solution due to its increasing accessibility and cost effectiveness. This study comprehensively explores Morocco’s wind energy landscape, defining wind energy and its global and local potential. It highlights challenges and opportunities in wind energy development and outlines strategies to enhance wind resource utilization. By 2021, Morocco achieved a significant milestone by raising the proportion of clean energy in its mix to 37, 6% with wind energy contributing 45% of this. Building on this success, Morocco aims to further increase its renewable energy capacity, targeting 52% of total capacity from renewable source by 2030 according to (IRENA). This showcases Morocco’s commitment to sustainable energy and its progressive approach to creating a greener and more resilient energy future.

Discrete optimal designs for distributed energy systems with nonconvex multiphase optimal power flow

The optimal selection, sizing, and location of small-scale technologies within a grid-connected distributed energy system (DES) can contribute to reducing carbon emissions, consumer costs, and network imbalances. There is a significant lack of studies on how DES designs, especially those with electrified heating systems, impact unbalanced low-voltage distribution networks to which most DES are connected. This is the first study to present an optimisation framework for obtaining discrete technology sizing and selection for grid-connected DES design, while simultaneously considering multiphase optimal power flow (MOPF) constraints to accurately represent unbalanced low-voltage distribution networks. An algorithm is developed to solve the resulting Mixed-Integer Nonlinear Programming (MINLP) formulation. It employs a decomposition based on Mixed-Integer Linear Programming (MILP) and Nonlinear Programming (NLP) and uses integer cuts and complementarity reformulations to obtain discrete designs that are also feasible with respect to the network constraints. A heuristic modification to the original algorithm is also proposed to improve computational speed. Improved formulations for selecting feasible combinations of air source heat pumps (ASHPs) and hot water storage tanks are also presented. Two networks of varying size are used to test the optimisation methods. Designs with electrified heating (ASHPs and tanks) are compared to those with conventional gas boilers. The algorithms outperform one of the existing state-of-the-art commercial deterministic MINLP solvers, which fails to find any solutions in two instances within specified time limits. While feasible solutions were obtained for all cases, convergence was not achieved for all, especially for those involving the larger network. Where converged, the algorithm with the heuristic modification has achieved results up to 70% faster than the original algorithm. Results for case studies suggest that including ASHPs can support up to 16% higher renewable generation capacity compared to gas boilers, albeit with higher ASHP investment costs, as local generation and consumption minimises network violations associated with excess power export. The results also show the importance of including nonlinear power flow constraints in DES design problems. The optimisation framework and results can be used to inform stakeholders such as policymakers and network operators, to increase renewable energy capacity and aid the decarbonisation of domestic heating systems.

Vimentin Localization in the Zebrafish Oral Cavity: A Potential Role in Taste Buds Regeneration.

The morphology of the oral cavity of fish is related to their feeding habits. In this context, taste buds are studied for their ability to catch chemical stimuli and their cell renewal capacity. Vimentin RV202 is a protein employed as a marker for mesenchymal cells that can differentiate along different lineages and to self-renew, while Calretinin N-18 is employed as a marker of sensory cells, and ubiquitin is a protein crucial for guiding the fate of stem cells throughout development. In this study, a surface morphology investigation and an immunohistochemical analysis have been conducted. The results of the present study reveal, for the first time, the presence of Vimentin RV202 in a taste bud cell population of zebrafish. Some taste bud cells are just Vimentin RV202-immunoreactive, while in other cells Vimentin RV202 and Calretinin N-18 colocalize. Some taste buds are just reactive to Calretinin N-18. Vimentin RV202-immunoreactive cells have been observed in the connective layer and in the basal portion of the taste buds. The immunoreactivity of ubiquitin was restricted to sensory cells. Further studies are needed to elucidate the role of Vimentin RV202 in the maturation of taste bud cells, its potential involvement in the regeneration of these chemosensory organs, and its eventual synergic work with ubiquitin.

Does environmental regulation improve energy transition performance in China?

This study examines the relationship between environmental regulation and energy transition performance in China. With the pressing need to mitigate climate change and reduce environmental impact, understanding the effectiveness of environmental regulations in facilitating the transition to cleaner energy sources is of paramount importance. Using comprehensive data on environmental regulations and energy transition indicators in China, this research investigates whether stringent environmental regulations positively influence the country's energy transition performance. The study employs statistical analysis techniques to analyze the correlation between environmental regulation stringency and various energy transition metrics, including renewable energy capacity, carbon intensity, and energy efficiency. The findings provide valuable insights into the role of environmental regulation in shaping China's energy transition landscape. Understanding this relationship can guide policymakers and stakeholders in formulating effective strategies and policies to accelerate the transition towards a sustainable and low-carbon energy system in China and beyond.

Decarbonising building heating and cooling: Designing a novel, inter-seasonal latent heat storage system

The global heating and cooling demands have increased to mitigate the effects of the rise in extreme weather events due to climate change. This has led to an increase in global greenhouse gas emissions due to the use of fossil fuels to meet these demands. The current study evaluates how an alternative low-carbon heating and cooling system may provide thermal comfort in residential buildings, specifically in regions that have a humid temperature oceanic climate-for example, the United Kingdom. To meet the net-zero emissions targets set in the United Kingdom by 2050, greenhouse gas emissions generated from heating in residential buildings must fall by 95 %. The leading decarbonisation strategy proposed by their government requires the electrification of the heating system through the installation of heat pumps. Consequently, the average electricity consumption per household is expected to increase. This will impose considerable pressure on electricity networks to source additional (ideally renewable) capacity, which will ultimately be costly. To circumvent this issue, the current study proposes a novel alternative method of providing nearly zero-carbon space and water heating, that can operate almost independently of the electricity grid. This requires the use of solar energy as the thermal energy source, and a solid-liquid phase change material as an inter-seasonal energy storage medium. A design optimisation study was thereafter carried forward to showcase the capability of such a system for a semi-detached house in London, United Kingdom.

Renewable origin, additionality, temporal and geographical correlation – eFuels production in Germany under the RED II regime

E-fuels are a promising technological option to reduce the carbon footprint in the transportation sector. To ensure the renewable origin of electricity-based fuels and minimize the impact of power-to-liquid facilities on the electricity grid, the European Union implemented electricity purchase conditions within the Renewable Energy Directive II. In this work, we analyze the impact of these electricity purchase conditions on the optimal placement, dimensioning and operation of facilities and the German electricity system. The results show that implementing the proposed electricity purchase conditions increases electrolysis capacity by 15.8% and reduces utilization by 672 h in 2030. With the constrained electricity supply, the power-to-liquid facilities concentrate on network nodes with high renewable potential, while the carbon dioxide supply loses importance. Overall, the German electricity system is not heavily affected by the proposed purchase conditions as the required renewable generation capacities only increase slightly. At the same time, carbon dioxide abatement costs rise by 14.3% by introducing the electricity purchase conditions.

Increasing temporal resolution in greenhouse gas accounting of electricity consumption divided into Scopes 2 and 3: case study of Germany

PurposeAs renewable energy sources (RES) experience short-term variability, electricity greenhouse gas (GHG) emissions also fluctuate. Increasing temporal resolution in electricity emissions accounting allows capturing these fluctuations. However, existing time-resolved models either neglect indirect impacts, adopt a generation perspective, or are based on non-public country-specific data. We provide an approach for calculating time-resolved GHG emission factors (EFs) of electricity consumption based on open access data for European countries and examine the temporal variability of German EFs.MethodsTime-resolved electricity GHG EFs are calculated within the framework of attributional life cycle assessment (LCA) with up to quarter-hourly resolution. The approach involves top-down calculation of annual combustion emissions, validation and scaling of time-resolved electricity generation data, as well as calculation of inland consumption EFs for each interval throughout a year. The EFs are divided by the stages of net generation, consumption by hydro-pumped storage (HPS), and transmission and distribution (T&D) losses, as well as Scopes 2 and 3, enabling GHG Protocol Corporate Standard-compliant reporting. The approach is exemplarily applied to Germany and its transmission system operator zones at quarter-hourly resolution for the years from 2017 to 2020 to investigate the relation between grid mix composition and temporal variability of EFs.Results and discussionThe annual average EF of the German consumption mix, encompassing direct and upstream emissions, declined from 499 (2017) to 377 g CO2e/kWh (2020), while quarter-hourly variability increased by 12%. Neglecting upstream emissions and intermediate steps between generation and consumption in Germany in 2020 resulted in an underestimation of 13% on an annual level, while quarter-hourly Scope 3 EFs reached up to 100 g CO2e/kWh. On a sub-national level, annual average EFs varied between 157 g CO2e/kWh (TenneT zone) and 505 g CO2e/kWh (50Hertz zone) in 2020. Temporal variability is the greatest in electricity systems with both fossil-fuel and renewable capacity sufficient to dominate short-term electricity generation. At an advanced level of RES integration, the fluctuations of EFs start declining, as demonstrated by the TenneT case.ConclusionAn increased temporal resolution in electricity emissions accounting can enhance a posteriori LCA results’ accuracy during the energy transition phase. The provided EFs link the life cycle-based perspective with time-resolved emissions accounting. With increasing reliance on RES, indirect emissions, including those related to energy storage, will gain in significance. The next step should focus on integrating physical cross-border electricity exchanges to complete the consumption perspective, as well as examining practical implementation to other countries.

Changes in bud bank and their correlation with plant community composition in degraded alpine meadows.

Bud banks are considered a crucial factor in regulating the species composition of grassland communities and maintaining the ecological function of alpine grasslands. However, few studies have paid attention to the dynamic changes of bud banks from undisturbed to severely degraded alpine meadows. Therefore, this study examined the correlations between plant diversity and bud bank traits at different stages of alpine meadows degradation. Grass biomasses and plant diversity were found to be highest in moderately degraded meadows, and sedge biomasses were highest in lightly degraded meadows. Lack of disturbance and moderate disturbance by herbivores increased the bud bank density of alpine meadows. Consistent with the changes in bud bank density, bud bank diversity was highest in undisturbed meadows. The structural equation model indicated that the densities of rhizome and the densities and diversities of tiller buds play crucial roles in facilitating the greater diversity of the plant community. Our findings suggest that the diversities and densities of rhizome and tiller buds in the degradation stages are synchronized with changes in plant diversity, and in the regenerative ability of bud banks, which largely determine the outcome of restoration in degraded meadows. These findings could provide a frame of reference for effectively restoring degraded alpine regions by regenerating bud banks. The potential driving force and renewal capacity of bud banks should be taken into account in restoring the Qinghai-Tibet Plateau's degraded meadow.

Sustainable Power Generation Expansion in Island Systems with Extensive RES and Energy Storage

Insular networks constitute ideal fields for investment in renewables and storage due to their excellent wind and solar potential, as well the high generation cost of thermal generators in such networks. Nevertheless, in order to ensure the stability of insular networks, network operators impose strict restrictions on the expansion of renewables. Storage systems render ideal solutions for overcoming the aforementioned restrictions, unlocking additional renewable capacity. Among storage technologies, hybrid battery-hydrogen demonstrates beneficial characteristics thanks to the complementary features that battery and hydrogen exhibit regarding efficiency, self-discharge, cost, etc. This paper investigates the economic feasibility of a private investment in renewables and hybrid hydrogen-battery storage, realized on the interconnected island of Crete, Greece. Specifically, an optimization formulation is proposed to optimize the capacity of renewables and hybrid battery-hydrogen storage in order to maximize the profit of investment, while simultaneously reaching a minimum renewable penetration of 80%, in accordance with Greek decarbonization goals. The numerical results presented in this study demonstrate that hybrid hydrogen-battery storage can significantly reduce electricity production costs in Crete, potentially reaching as low as 64 EUR/MWh. From an investor’s perspective, even with moderate compensation tariffs, the energy transition remains profitable due to Crete’s abundant wind and solar resources. For instance, with a 40% subsidy and an 80 EUR/MWh compensation tariff, the net present value can reach EUR 400 million. Furthermore, the projected cost reductions for electrolyzers and fuel cells by 2030 are expected to enhance the profitability of hybrid renewable-battery-hydrogen projects. In summary, this research underscores the sustainable and economically favorable prospects of hybrid hydrogen-battery storage systems in facilitating Crete’s energy transition, with promising implications for investors and the wider renewable energy sector.

Prediction of renewable energy hosting capacity using multiple linear regression in KEPCO system

In order to prepare measures for the stable operation of the power system to expand renewable energy, the renewable energy hosting capacity (HC) in the system shall be identified in advance. This paper proposes a methodology for predicting monthly HC based on factors affecting HC. It was found out that these factors are: Total generation, ratio of nuclear, coal, liquefied natural gas (LNG), and other power generations. A prediction model was developed using multiple linear regression by integrating and separating data of elements from weekend data. A comparison of the determination coefficients showed that the models incorporating weekend data exhibited the best accuracy. In conclusion, the proposed model has the characteristics of predicting various HCs simply and quickly with five factors.

Multilateral Debt Relief for Clean Ocean Energy

As states bring more and more offshore wind online and build renewable energy capacity, the promise of large-scale ocean renewables such as offshore wind is not shared equally across all coastal states. This paper examines the situation of coastal states identified by the World Bank as Heavily Indebted Poor Countries (HIPCs) in the context of the boom in offshore wind investment. Specifically, the paper looks at the limited access to renewable energy production exacerbated by ongoing public debt loads, and the almost complete lack of access to clean ocean energy development for the poorest coastal states. Using statistics from the International Renewable Energy Agency and datasets from the Our World in Data project, this paper highlights that the most indebted coastal states only have access to 0.69% of the available renewable energy even though these states represent 4.6% of the global population. In the context of state responsibility for failing to meet climate obligations under the UNFCCC, this paper argues that a sovereign debt relief package offers an equitable remedy to HIPC coastal states, many of whom owe a substantial portion of their GDP as external public debt. The debt service payments would be invested in the upfront capital costs of ocean-based clean energy. These types of debt relief arrangements address international state responsibility and offer the dual co-benefits of long-term economic development and low-carbon sustainability.

Wind-solar-storage trade-offs in a decarbonizing electricity system

Exploring cost-effective wind-solar-storage combinations to replace conventional fossil-fuelled power generation without compromising grid reliability becomes increasingly important in a steadily decarbonizing electricity system. For a renewable energy-rich state in Southern India (Karnataka), we systematically assess various wind-solar-storage energy mixes for alternate future scenarios, using Pareto frontiers. The simulated scenarios consider assumed growth in electricity demand, and different levels of base generation and supply-side flexibility from fossil fuels and hydropower. Our approach uses hourly load data, simulates generation based on hourly weather reanalysis data, and models the effects of battery charging and discharging on battery lifetimes. In the context of declining base generation and limited flexibility in the state electricity grid, the reliability of meeting demand is limited by the generation curtailment that is permitted. We show that adding battery storage capacity without concomitant expansion of renewable generation capacity is inefficient. Keeping the wind-solar installations within the officially assessed renewable potential, a fully decarbonized grid with limited flexibility can have approximately 63% reliability even after using adequate battery storage. Achieving 99% grid reliability would be expensive, requiring large wind-solar installations that exceed officially assessed potential, constrained by land allocation. The findings highlight the importance of a fresh examination of curtailment thresholds, available renewable potential, and possibilities of demand-side management based on consumers' willingness to modify hourly demand patterns.

The Magic of Media and Culture

The Magic of Media and Culture

A REVIEW ON DEVELOPMENT OF RENEWABLE ENERGY SOURCES IN INDIA

Energy generation and environmental conservation are the twin issues arising from exploitative interaction of humans with natural resources. Excessive utilization of coal and oil for energy generation lead to the multiple environmental problems. In the current scenario the global energy needs can only fulfill by adopting non conventional sources of energy.The present review deals with efforts and achievements of India to develop sustainable, efficient and cleaner energy resources not only in urban but also in rural areas .India has always shown its willingness in leadership to fight climate change. Presently, India is worlds third renewable energy producer with 40% of energy capacity in installed in the year 2022 (160 GW of 400 GW) coming from renewable sources.Ernst & Youngs (EY)2021 Renewable Energy Country Attractiveness index(RECAI) ranked India third behind USA and China. In November 2021. India had a renewable energy capacity of 150 GW consisting of solar (48.55 GW), wind (43.03 GW) hydro power (51.34 GW) and Biomass (10.62 GE). India has committed for a girl of 500 GB renewable energy capacity by 2030. The countrys vision is to achieve Net Zero Emissions by 2070.

Geothermal energy exploitation in an island-based 100% renewables strategy. Case study of Tenerife (Spain)

The large-scale integration of non-dispatchable renewable energy must be carefully planned, especially in poorly robust electrical energy systems. Tenerife is the most populated of the islands in the Canary Archipelago (Spain) and has an isolated electrical system. It is envisaged for the horizon of 2040 that the island will have a high contribution of non-dispatchable renewable energies (fundamentally wind and solar photovoltaic). Tenerife also has exploitable high enthalpy geothermal resources. An energy planning model is implemented in this paper based on which different scenarios with high non-dispatchable renewable energy penetration in the island's electrical system are simulated. Geothermal energy is also incorporated in the simulations as a dispatchable renewable energy source, with the power required sized according to the hypotheses of each scenario. The results are compared according to different technical and economic parameters. An evaluation is also made of the influence that the capacity of the electrical system to take on higher non-dispatchable renewable power and the presence of energy accumulation systems might have on the minimization of losses in the non-dispatchable renewable energy capacity factor. The results of the simulated scenarios show that geothermal energy could meet up to 28.8% of the island's electrical energy demand, increasing the stability, flexibility and supply guarantee of system. A 100% renewable system could be possible through the incorporation of this energy source and the planning of energy accumulation systems. In the case study, the economic saving for Spain's electrical system could exceed 400 €million per year.

Long-Term Forecasting Framework for Renewable Energy Technologies’ Installed Capacity and Costs for 2050

Published forecasts underestimate renewable energy capacity growth and potential cost reductions, creating uncertainty around investment decisions and slowing progress. Scenario-based projections diverge widely, driven by variations in modelling techniques and underlying assumptions, with policy-based models typically being overly conservative. With historical generation capacity and cost data readily available, this research demonstrates that data-driven approaches can be leveraged to improve long-term capacity and cost forecasts of solar, wind, and battery storage technologies. Unlike exponential growth models prevailing over shorter time scales, logistic curves requiring asymptotic limits, or machine learning algorithms dependent on extensive datasets, this analysis demonstrates that temporal quadratic regressions are a better starting point to represent capacity growth trends over two to three decades. When coupled with published learning rates, trend-based capacity forecasts provided tighter and lower capital and levelized cost of energy outlooks than most reviewed scenarios, with photovoltaics global average levelized cost of energy reducing from 0.057/kWh to below USD 0.03/kWh by 2030 and below USD 0.02/kWh by 2040. Greater transparency on manufacturing ecosystems is proposed so that more advanced analytical techniques can be utilized. This analysis indicates that without direct interventions to accelerate the growth in wind power generation, global renewable energy technology deployment will fall short of the generation capacities required to meet climate change objectives.