Corrigendum to ‘Review of sizing methodologies for hydropower-based hybrid energy systems: a techno-economic perspective’ [Renew Sustain Energy Rev 232 (2026) 116778

ABSTRACT The Arctic archipelago of Svalbard is currently undergoing a profound energy transition, shifting from coal-based infrastructure towards a low-carbon hybrid energy system. Following the closure of the last coal mine in 2025, a range of renewable energy technologies is expected to be implemented in accordance with a new national energy plan. This article investigates the expectations that residents of Longyearbyen have for this socio-technical transformation, with particular attention to the roles of institutional trust, energy citizenship, identification with nature and climate change denialism. Drawing on survey data, the study identifies five distinct public expectation profiles regarding the renewable energy transition. Two of these – Risk and Unreliable – reflect deep-seated concerns, while three – Opportunities, Climate and Innovation – express more optimistic outlooks. The findings highlight institutional trust as a key predictor of optimistic expectations, often in conjunction with energy citizenship. In contrast, identification with Svalbard’s natural environment and climate change denialism are more strongly associated with the concerned profiles. While prior research has emphasized the importance of institutional trust in energy transitions, this study demonstrates how trust also shapes future-oriented expectations and operates in tandem with energy citizenship norms. The article concludes by outlining strategic opportunities for fostering inclusive community support and mitigating the risk of political polarization in Svalbard’s evolving energy landscape.

This work presents the design and implementation of a hybrid power conversion system integrating solar energy, battery storage, and grid support to ensure reliable and efficient energy management. The proposed system employs a multi-stage power electronic architecture consisting of a DC–DC boost converter, a bidirectional buck–boost converter, and an AC–DC converter interconnected through a common DC link. The boost converter is utilized to regulate and enhance the variable output of the photovoltaic source, while the bidirectional converter facilitates controlled charging and discharging of the battery, enabling energy storage and supply balancing. The grid interface operates as a supplementary power source to maintain continuity during fluctuations in solar generation. A proportional–integral (PI) controller is implemented as the primary control strategy for regulating voltage and current across the system. To maximize energy extraction from the photovoltaic source, an incremental conductance (INC)-based maximum power point tracking (MPPT) algorithm is employed in conjunction with the PI controller. This approach ensures accurate tracking of the optimal operating point under varying environmental conditions. The bidirectional converter control is also governed by PI regulation to achieve stable energy transfer between the battery and DC link, thereby maintaining system equilibrium. The proposed configuration offers a simple, cost-effective, and reliable solution for hybrid energy systems. It demonstrates effective coordination between renewable generation, storage, and grid support while maintaining system stability and performance. The results validate that the combined use of PI control and INC-based MPPT provides satisfactory dynamic response, reduced steady-state error, and improved energy utilization. This work highlights the feasibility of implementing conventional control techniques for efficient operation of integrated renewable energy systems.

The building sector accounts for nearly 30% of global energy use and 28% of CO2 emissions, with residential buildings in Canada contributing about 17% of national energy demand. In cold regions such as Labrador, approximately 82% of this consumption is associated with space heating and domestic hot water, making heating the dominant residential load, while fossil-fuel furnaces and electric baseboard heaters remain common. These conditions highlight the need for efficient and sustainable heating alternatives for cold-climate residential buildings. This study examines the design and performance of a hybrid solar photovoltaic (PV) and geothermal heat pump (GTHP) system for a typical detached home in L’Anse-au-Loup, Labrador, Newfoundland and Labrador, Canada (51.52° N, 56.84° W), with the goal of improving energy efficiency and reducing dependence on the electrical grid. Heating and cooling loads were developed using the Hourly Analysis Program (HAP 6.1), while system operation and economic performance were assessed through the Hybrid Optimization Model for Electric Renewables (HOMER Pro 3.18.3). The proposed design combines a rooftop PV array, a ground-source heat pump, and second-life lithium-ion batteries repurposed from retired electric vehicles to lower costs and support short-term energy storage. The system is modelled under grid-connected conditions to reflect realistic operation for northern households. Results show that the hybrid system can meet annual electrical and thermal needs while reducing grid consumption by more than half. Annual carbon emissions decrease by roughly 4–5 tonnes, and repurposed batteries offer a cost-effective alternative to new storage. Overall, the study demonstrates that PV–GTHP systems can provide reliable, efficient, and practical energy solutions for cold-climate homes.

The global shift toward net-zero carbon emissions requires flexible, multi-source energy systems capable of overcoming disruptions in renewable energy sources. This study presents a comprehensive technical, economic and environmental assessment of a hybrid energy system designed for the Faculty of Technology and Education at Sohag University, Egypt. The research evaluates three operational scenarios, involving the integration of the utility grid (UG), photovoltaic (PV) cells, a battery energy storage system (BESS), and a green hydrogen production subsystem consisting of an electrolyzer, hydrogen storage (H2), and fuel cells (FC). Scenario 1 (PV/BESS/UG) serves as the baseline configuration, achieving a renewable fraction of 74.7% but maintaining significant dependence on the electrical grid. Scenario 2 (PV/FC/H2/UG) demonstrated the economic infeasibility of a hydrogen subsystem configured to operate on a daily charge–discharge cycle rather than functioning as a long-duration or seasonal storage system; the optimization results favored grid electricity over fuel cell dispatch. Scenario 3 (PV/FC/BESS/H2/UG) emerges as the most effective configuration. Despite exhibiting a higher net present cost (NPC: 823,477 USD) and a levelized cost of energy (LCOE: 0.0832 USD/kWh), it achieved a renewable fraction of 75.7% and ensured nearly 100% supply reliability with negligible unmet electrical load. The results indicate that the integration of BESS for short-term response and H2 for long-term energy reserve provides a strategic energy buffer capable of mitigating the effects of solar PV power outages and grid instability.

The growing participation of prosumers equipped with renewable generation and storage systems is reshaping distribution network operation. However, most existing studies treat technical and economic objectives separately, often neglecting coordinated demand response (DR) and reactive power management. This paper proposes a comprehensive optimization framework for the optimal placement and operation of prosumers integrating photovoltaic (PV), wind, and hybrid systems with battery energy storage (BESS). The model minimizes total operational cost by jointly considering power purchase and sale, distribution losses, battery degradation, curtailed renewable energy, reactive power penalties, and DR incentives, ensuring balanced techno-economic trade-offs. Furthermore, inverter-based PV and BESS units are leveraged for reactive power support and power factor improvement, while flexible EV charging is modeled as a time-shiftable load to enhance demand-side flexibility. The proposed framework is tested on the IEEE 33-bus distribution network under twelve scenarios combining variations in prosumer placement, DR participation, and reactive power pricing. Results show that coordinated prosumer integration with DR leads to a 50.5 % reduction in energy purchase costs and a 37.5 % drop in reactive power penalties compared to the base case. However, excessive active power injection degraded the network power factor below 0.5, highlighting the necessity of reactive-power control. Time-variable capacitor compensation at buses with high reactive loads (low power factor) effectively improved the network power factor above 0.9 and reduced the total cost by 52.6 %. The model also demonstrates that optimal placement of a limited number of prosumers achieves nearly the same performance as the unrestricted case, confirming its robustness. • A model optimizes prosumer placement with solar, wind, and hybrid energy systems. • Demand response incentives reduce grid costs more than energy buyback increases. • Active power injection lowers power factor, requiring compensation strategies. • Power factor improved using reactive penalties and time-variable capacitors. • Even limited prosumer placement offers strong technical and economic benefits.

Hydrogen and electro-fuels play a crucial role in decarbonizing hard-to-abate sectors, while the comprehensive cost-effectiveness of their global trade driven by regional cost variations remains underexplored. This study presents a techno-economic assessment of importing hydrogen carriers (liquid hydrogen, liquid methane, methanol, ammonia, and liquid organic hydrogen carriers) via deep-sea shipping, compared with their domestic production. Incorporating country-specific capital expenditures (CAPEX) and weighted average cost of capital (WACC), the production costs of these hydrogen carriers are evaluated through cost-minimizing optimization of capacity configuration and operation strategy for wind-PV-grid hybrid energy systems. Additionally, this study improves shipping cost models by accounting for a comprehensive range of ship types and size categories specific to each hydrogen carrier. For the imports of electro-fuels from China to Sweden during 2025–2050, the levelized import costs of methane, methanol, and ammonia are 98–206, 93–204, and 93–126 EUR/MWh, respectively, which are 12%–22% lower than domestic production costs in Sweden. This cost advantage is attributed to lower country-specific CAPEX and WACC in China, while it comes with higher CO 2 emissions due to China's more carbon-intensive electricity grid. However, if electro-fuels require reconversion to hydrogen, the total import costs for all hydrogen carriers exceed the domestic hydrogen production costs. Moreover, if hydrogen production scale is doubled to 200 million kgH 2 /year, or if shipping distance is reduced to less than 8000 nautical miles, importing liquid hydrogen could become cost-competitive with domestic production. Finally, uncertainty analysis reveals that overall costs are highly sensitive to CAPEX, WACC, and electrolyzer performance, highlighting the significance of accounting for these country-specific factors in global hydrogen trade. • Techno-economic analysis of e-fuel and hydrogen imports versus domestic production. • Integrating country-specific CAPEX and WACC of renewables and electrolyzer systems. • Improved shipping cost models with ship selection specific to each hydrogen carrier. • Importing electro-fuels for direct use is 12–22% cheaper than domestic production. • Upscaling production or shortening distance enables cost-effective hydrogen imports.

A day ahead scheduling model of a smart hydrogen-based microgrid taking into account PV production and electrical load demand forecasting errors

Reoperation of hydro–hydrogen–dominated hybrid energy systems to adapt to ecological uncertainty

Low-energy miniature wearable air-conditioner with direct cold-air delivery: A novel water–electricity hybrid energy system

Optimization of fossil-geothermal hybrid energy systems: Thermodynamics and exoeconomic approach

To achieve sustainable hydrogen production, systems powered by renewable energy must replace conventional fossil fuel-based routes. This study evaluates the techno-economic feasibility and optimal sizing of seven distinct hybrid renewable energy system configurations—comprising wind, solar, biomass, and pumped hydro energy storage (PHES)—for producing one ton of green hydrogen per day in Finland. The energy systems are modelled by Aspen Plus and MATLAB and analyzed within tax-based and non-tax-based frameworks concerning biogenic CO 2 emissions from biomass combustion. Four multi-objective optimization problems use the non-dominated sorting genetic algorithm II (NSGA-II) to determine the Pareto set for four scenarios that minimize the levelized cost of hydrogen (LCOH) and capital expenditure (CAPEX). A decision-making method is then employed to choose the best solutions. In addition, the net present value (NPV) and payback period are evaluated to assess system profitability. The findings indicate that biomass-based systems can compete with wind and solar in green hydrogen production, although policy instruments—particularly biogenic CO 2 taxation—significantly influence system design and cost. The results show that wind-PHES and solar-PHES systems can produce hydrogen at costs of about $3.2/kg and $3.6/kg, respectively. PHES contributes roughly 11% of the total CAPEX in the wind-based system, compared to 31% in the solar-based configuration. The exclusive use of biomass coupled with a Rankine cycle to power the electrolyzer results in an LCOH of $7.3/kg under biogenic CO 2 taxation, compared to $3.6/kg in the absence of such a tax. The study highlights the importance of incorporating storage or complementary energy systems, such as PHES or biomass, to support configurations relying primarily on wind and solar resources. • Optimal sizing of renewables to steadily produce one tonne of hydrogen per day. • The system is modeled by Aspen Plus and MATLAB and assessed in seven scenarios. • Four multi-objective optimization problems based on the NSGA-II are carried out. • Carbon taxation heavily impacts the system design and hydrogen pricing. • Biomass can produce hydrogen at low LCOH and CAPEX.

Sensitivity‐guided PSO‐based PI controller tuning for grid‐connected PV–wind hybrid energy systems

Uncertainty-driven assessment of floating photovoltaic hydropower wind hybrid energy systems using a circular neutrosophic approach

The increasing development of ingestible medical devices for gastrointestinal diagnostics, drug delivery, and physiological monitoring has created a growing demand for reliable and long-lasting power sources. Conventional batteries limit device lifetime, increase capsule size, and raise safety concerns, making biomechanical energy harvesting from gastrointestinal motility a promising alternative for self-powered ingestible systems. This review aims to provide a comprehensive overview of biomechanical energy harvesting from gastrointestinal mechanical activity for powering ingestible biomedical devices, with emphasis on energy sources, transduction mechanisms, materials, system integration, limitations, and future research directions. Recent literature on gastrointestinal biomechanics and energy harvesting technologies was analyzed, focusing on major transduction mechanisms such as piezoelectric, triboelectric, and electromagnetic generators. The review also evaluates material selection, device architectures, encapsulation strategies, and power management circuits from a system-level integration perspective. Piezoelectric, triboelectric, and electromagnetic energy harvesters demonstrate the ability to convert low-frequency gastrointestinal mechanical energy into electrical energy suitable for ultra-low-power biomedical devices. Hybrid energy harvesting systems improve energy reliability and output performance. However, several challenges remain, including low energy density, variability in gastrointestinal mechanical forces, miniaturization constraints, material durability, electrical conversion losses, and lack of standardized testing protocols. Biomechanical energy harvesting has significant potential to enable battery-free ingestible biomedical devices. Future developments in hybrid energy systems, ultra-low-power electronics, biodegradable materials, and adaptive power management are expected to support the development of fully autonomous self-powered ingestible medical devices.

This study investigates the integration of artificial intelligence (AI) and machine learning (ML) technologies in solar-biomass hybrid energy systems for sustainable energy generation. Through a comprehensive empirical analysis of 250 hybrid energy installations across five regions, this research evaluates the performance optimization potential of AI/ML algorithms in renewable energy management. The study employed a mixed-methods approach with quantitative data collection from operational systems over 24 months (2023-2024). Results demonstrate that AI-enhanced solar-biomass systems achieved 34.7% higher energy efficiency compared to conventional systems, with ML-based predictive maintenance reducing operational costs by 28.3%. The study found significant correlations between AI implementation and system reliability (r=0.847, p<0.001), while deep learning models improved energy forecasting accuracy to 92.4%. Integration challenges were identified in 18.2% of installations, primarily related to data synchronization and algorithm compatibility. These findings contribute to advancing sustainable energy technologies through intelligent optimization frameworks, providing empirical evidence for the transformative potential of AI/ML in hybrid renewable energy systems.

Access to reliable and sustainable power generation in remote areas is a critical challenge faced by many regions worldwide. In such areas, hybrid energy systems integrating solar, wind, and battery components have emerged as a promising solution to overcome the lack of electricity infrastructure. This research primarily focuses on modeling the power supply for houses in remote areas of Iraq. It discusses a hybrid system to meet the electrical demand of a small area. The simulations and optimal sizing of the system are performed in MATLAB 2023a using a swarm-based artificial bee colony (ABC) algorithm. The findings have been compared with results from HOMER, a program commonly used to optimize combinations of electric and renewable energy sources, to confirm the effectiveness of the proposed approach. The main goals of this optimization project are to optimize the system component sizes and obtain the minimum cost of energy (LCOE). The results from the ABC algorithm show that the system exhibits good performance and convergence. This study also evaluates the proposed system's performance in the event of a failure from any source. The results confirm that the proposed method and optimal configuration can handle an efficient and reliable system.

This study explores a pathway to decarbonising biofuel production by comparing hybrid renewable configurations, incorporating solar and geothermal energy, with a grid electricity scenario to identify the most environmentally sustainable approach. Five biodiesel production methods— alkaline-catalysed, acid-catalysed, two-step transesterification, electrolysis, and supercritical transesterification—were assessed for producing biodiesel from 1 kg of Chlorella vulgaris oil using the Australian Life Cycle Assessment Society (ALCAS) method, validated through ReCiPe 2016 Midpoint and Endpoint approaches. Among all methods, hybrid supercritical transesterification demonstrated the lowest environmental impact, achieving a global warming potential of 0.49 kg CO 2 eq, marking a 98.4 % reduction compared to grid-powered acid transesterification, the most emission-intensive process. Single score results further confirmed these benefits, showing substantial improvements across human health, ecosystem, and resource impact categories. Uncertainty analysis validated the consistency of these findings, demonstrating that the hybrid energy system outperformed grid electricity across all production methods, emphasising the critical role of renewable energy integration in reducing emissions and environmental burdens. Moreover, full adoption of the hybrid biodiesel system could contribute 6.4 % toward Australia's 2030 climate target, avoiding 2.9 million tons CO 2 eq annually. If implemented from 2025 to 2050, cumulative reductions could reach 72.5 million tons CO 2 eq, significantly supporting Australia's net-zero goals. • Carbon hotspot assessment was performed for microalgae-based biodiesel pathways. • A new geothermal and solar energy setup was assessed for biodiesel production. • Hybrid supercritical transesterification achieved the lowest environmental impacts. • Findings indicate a 2.9 Mt CO 2 eq annual emission reduction potential.

Review of sizing methodologies for hydropower-based hybrid energy systems: a techno-economic perspective

Scaling net-zero carbon and firm power via co-optimizing power-to-gas and gas-to-power for seasonal storage and curtailment elimination in isolated microgrids