Techno-economic analysis of an integrated desalination-renewable-hydrogen system for zero-emission freshwater and electricity production

Purpose: The study investigated the effect of energy consumption and economic development in Nigeria. Methodology: The data for the study were sourced from the World Bank Database from 1990 to 2023. Following the unit root test, the Toda-Yamamoto Granger Causality or Block Exogeneity Wald was carried out. Results and conclusion: Principally, no causality exists from access to electricity for the urban population (UPEt), electricity availability to rural populations (RPEt), energy production through renewable sources (EPRt) (hydro), electricity production through non-renewable sources (EPNt), and electric power transmission and distribution losses (EDLt) to per capita income in Nigeria. The findings suggested that enhancements in electricity access and production did not significantly contribute to economic development, as measured by per capita income during the period analyzed. Implication of findings: The study, among others, recommended that stakeholders in the energy industry in Nigeria should synergize to enhance the provision of a reliable and quality electricity supply instead of merely increasing access. The implication of this finding is that making energy utilization and affordability better will improve the economy.

To enhance the accommodation capability and operational flexibility of renewable energy systems, address the insufficient architectural integration of existing ammonia-based energy systems, and overcome the limitations of current optimization algorithms in tackling complex nonlinear multi-objective problems, this paper proposes a synergistic integrated energy system with liquid ammonia as the central hub. The system integrates multi-energy flows encompassing electricity, hydrogen, ammonia, and heat, leveraging ammonia fuel cell power generation, ammonia cracking, and ammonia-blended gas turbines for both electricity and heat production. A bi-level optimization model is formulated, coupling upper-layer multi-objective capacity planning with lower-layer stochastic chance-constrained scheduling. To solve this model, a hybrid algorithm, designated as LSDBO-WOA, is developed by integrating an improved dung beetle optimizer (LSDBO) with the whale optimization algorithm (WOA). Case study results demonstrate that the proposed algorithm achieves markedly superior convergence performance compared to benchmark algorithms such as non-dominated sorting genetic algorithm II (NSGA-II), with an improvement of approximately 18.6% in comprehensive performance metrics. Furthermore, the proposed electricity-hydrogen-ammonia-heat system attains an overall energy efficiency exceeding 97.66% and reduces carbon emissions by 7.3% relative to the original system without ammonia integration.

In response to the growing need for accurate forecasting of electricity generation from PV installations, which is crucial both for enhancing self-consumption and for balancing the power grid, this study presents a comparative analysis of selected machine learning models. The research focuses on the XGBoost algorithm and LSTM neural networks, applied to predict PV energy production based on meteorological data and historical generation records from four medium-sized PV installations (30–50 kWp) located in Poland. Meteorological data were retrieved from open sources and combined with actual production measurements to build the training dataset. This paper discusses the challenges posed by these data at the given latitude, as well as issues related to processing data from newly launched installations. The performance of both approaches was evaluated in short- and medium-term forecasting, with particular attention to prediction accuracy, robustness to noisy data, and the ability to capture nonlinear relationships.

The use of renewable energy sources on board ships is one solution to reduce pollution from maritime transport. Considering it one of the many solutions for the transition to "zero" emission ships, we studied the possibility of installing a new type of power plant on ships already in operation that uses solar/photovoltaic and wind energy conversion systems. The current electricity production system is transformed into a hybrid system, and by improving the available electrical power management algorithms, clean energy consumption will be prioritized. Monitoring daily electricity consumption and recording values for renewable energy source parameters during ship periods and voyages enabled calculations to determine the potential for electricity production from renewable sources and demonstrated the viability of the chosen solution. The results obtained highlight that installing the ecological marine power plant (ENPP) can achieve significant reductions in fuel consumption for producing electricity on board the ship.

Hydropower supports the energy transition by providing flexible, low-carbon generation, yet its performance is increasingly constrained by climate-driven variability in water availability. This study quantifies long-term hydroclimatic changes in the Warta River–Jeziorsko reservoir system (central Poland) and assess their implications for water resources, hydropower generation, and reservoir operation. The analysis combines multi-decadal meteorological observations, daily river flows at the Sieradz gauge (1951–2022), and reservoir and plant operational records, with electricity production evaluated for 1995–2022. The results indicate significant warming and shorter snow-cover duration, while annual precipitation shows no consistent long-term trend. Hydrological drought has intensified, reflected by lower mean flows in recent decades and a strong increase in days with discharge below SNQ, particularly after 2015. Electricity production is highly variable and shows a significant downward trend, amplified by reduced usable storage following operating-rule changes. By linking long-term hydroclimatic indicators with site-specific operational and production data for a lowland multi-purpose reservoir under environmental constraints, this study provides evidence to support adaptive reservoir management balancing water security and hydropower reliability.

Türkiye's strategic location in the Earth's sunbelt, along with its diverse geographical features, makes it a great place to harness renewable energy sources like hydropower, wind, solar, geothermal, and biomass energy. At the end of 2024, Türkiye's renewable energy capacity reached approximately 68.5 GW, accounting for 59.4% of total capacity, reflecting an 8.5% growth compared to the previous year. During the same period, electricity production from renewable energy sources increased by 15.8% compared to the previous year, reaching 159.7 TWh, and accounted for 45.8% of total production. According to Türkiye's National Energy Plan, it is expected that by 2035, the share of renewable energy sources in total installed capacity will rise to 64.7%, reaching 122.7 GW, while the share of renewable energy in electricity generation will increase to 54.8%, accounting for 279.7 TWh. This paper explains the current state and future prospects of Türkiye’s renewable energy sector, employing SWOT and PESTLE analyses to provide a comprehensive assessment. With its abundant renewable resources, Türkiye has the potential to enhance energy security and sustainability by increasing the share of renewables in electricity production and reducing fossil fuel dependence.

Soil-based microbial fuel cells for the detection of DDT and its derivatives: a potential bioelectrochemical sensor.

• High-resolution model optimizes the siting of renewable energy in the Nordic region. • Detailed representation of the grid and local production conditions for renewables. • Proximity to demand and full-load hours are key factors in optimal siting. • Grid capacity assumptions have strong impacts on model output. Renewable electricity generation is expected to play a pivotal role in the global shift toward electrification. However, the inherent variability of renewable energy sources, in addition to factors such as local weather patterns and grid limitations, poses a significant challenge in terms of determining the optimal size and placement of distributed generation units. This study tackles this issue by applying a novel, high-resolution energy systems model that is tailored to the Nordic region. The model is designed to capture with high accuracy local nuances in relation to grid infrastructure, weather patterns, and demand profiles. The model minimizes the total system costs, accounting for both investment and operational expenditures, through the optimal integration of variable renewable energy sources and dispatchable generation units. The findings indicate that the siting of renewable generation is primarily influenced by a combination of a high number of full-load hours and proximity to the electricity demand, with the latter becoming increasingly important under high-demand conditions. Among renewable technologies, solar photovoltaic systems exhibit the strongest correlation with demand center proximity, whereas offshore wind is mainly constrained by a high potential annual production capacity. In addition, assumptions regarding the availability of electricity grid capacity are shown to have a significant impact on the results, with up to 26% of production being relocated when 100 % thermal grid capacity is available, as compared to when 30% of grid capacity is reserved for contingency events.

Electron transfer performance and mechanism in twin microbial fuel cell powered electro-Fenton system with waste activated sludge as substrate.

Data-driven multi-objective optimization of a novel waste-fueled polygeneration system for simultaneous production of hydrogen, freshwater, hot water, chilled water, cooling power, and electricity

The impact of solar panel installation on electricity consumption and production: A firm’s perspective

Solar energy has seen the most significant development in the past decade. Electricity and hot water production are the two most common uses of solar energy. A photovoltaic (PV) system is a popular method for generating electricity from solar energy. However, PV systems are known for their low efficiency, which reduces further as the PV cell temperature rises. The photovoltaic-thermal (PVT) system combines a PV system with a thermal collector to provide dual benefits, namely power generation and hot water production. However, PVT system research often employs a constant flow (CF) strategy in which water is continually cycled throughout the experiment, making it inapplicable. In comparison, the constant collection temperature (CCT) scheme is a more feasible approach, but its impact on PVT system performance has received less attention. This study compares a flow channel PVT system using both CF and CCT strategies. The results show that the CF scheme achieved a higher maximum thermal efficiency of 35.05%, while the CCT scheme reached 17.89%. The CCT method can also maintain the optimum water temperature despite changing radiation circumstances. The PVT system outperforms traditional PV panels regarding electricity efficiency, with a maximum improvement of 0.89% and 0.96% utilizing the CF and CCT schemes, respectively. These results show that PVT systems with CCT schemes that use less energy for pumping outperform PV panels in terms of power production and electricity efficiency.

Electrochemical CO 2 reduction reaction (eCO 2 RR) offers a promising pathway toward a circular economy by converting CO 2 into value-added products such as formate, carbon monoxide, and ethanol. Among the products, formate has gained particular attention as a versatile C 1 building block. Pilot-scale demonstrations have reached kilogram-scale CO 2 conversion per day using large-area electrodes. Thus, the sustainability of this highly electricity-intensive process critically depends on its integration into the renewable energy landscape. Foremost battery storage is required to ensure continuous operation of eCO 2 RR while utilizing solar power and addressing its variability. In this study, we developed and applied a tailored photovoltaic (PV) system with battery storage to evaluate long-term renewable energy supply for eCO 2 RR at different scales (10 cm 2 –300 cm 2 Sn–GDE setups), using the UFZ location in Leipzig, Germany, as a reference site. For developing such a stand-alone power supply at the reference site, PV power generation data obtained using the Renewable Spatial–Temporal Electricity Production (ReSTEP) simulation model, which is based on real weather data, were combined with experimentally derived energy demands of the eCO 2 RR setups at different scales. As a result, the required number of PV panels and batteries for reliable year-round operation was determined. The results show that the number of solar modules scales proportionally with the electrode size, while sufficient battery storage is essential to buffer up to three consecutive days without sunlight and maintain safe discharge limits. For the 100 cm 2 setup, additional off-grid simulations demonstrate that increasing the battery capacity improves both system reliability and battery lifespan. Overall, this study demonstrates that tailored PV systems with battery buffering can enable sustainable operation of eCO 2 RR from laboratory to pilot scales, highlighting a practical route for integrating this technology into future electrobiorefineries and advancing its readiness toward industrial deployment.

ABSTRACT Microbial fuel cells (MFCs) have attracted increasing amounts of interest in polluted soils remediation, since they are simultaneously capable of generating renewable energy. In this study, an experimental MFC device was employed to treat Cr(VI) polluted soils sampled from the actual sites. We explored the effect of soil physical heterogeneity on the generated voltages, soil pH, changes of Cr(VI) concentrations, forms of chromium and the microbial communities at anode during the MFC treatment. After the 50 days of MFC treatment, the concentrations of Cr(VI) in soils at anode were decreased from 16.5–17.7 mg/kg to 4.34 mg/kg below, and the highest removal efficiency of Cr(VI) approximately reached 100%. Due to the increased permeability of soil water, sand addition increased the generated voltages by four times, and raised the biological effectiveness of chromium in soils with the significant decreases of residue state chromium. The anaerobic bacteria enriched around the anode favored to electricity production, while a part of the produced electrons was used for the reduction of metal ions around the anode, which inhibited the current produced by MFC. This study emphasized on a significant physical factor which affected the bioelectrochemistry of MFC in soil, and provided a promising and green method in the remediation of heavy metal polluted soil.

Societal Impact Statement Climate change and the growing demand for renewable energy are putting increasing pressure on land, as food production and solar power generation often compete for the same areas. In this study, we assessed which temperate‐region crops are best suited for agrivoltaics, a technology combining farming and solar electricity production on the same land. We found that crops such as fruits and berries benefit most from agrivoltaics, while others, including some cereals and legumes, are less suitable. These results can help farmers, planners and policymakers make informed decisions, supporting climate‐resilient agriculture, efficient land use and wider adoption of sustainable agrivoltaics. Summary Agrivoltaics, a dual land use approach, combines agricultural and solar electricity production on the same land. Despite the increasing global adoption of agrivoltaics, systematic assessments of crop suitability remain limited. We address this gap by combining qualitative and quantitative analyses (mixed‐methods approach) first to identify key criteria of stakeholders to evaluate crop suitability in agrivoltaics and second to systematically evaluate nine major crop groups based on those criteria. We interviewed 17 stakeholders to identify four major criteria to assess crop suitability in agrivoltaics: need for protection (35%), shade tolerance (30%), economic efficiency (19%) and system design (16%). Crop groups were rated for shade tolerance and need for protection on a suitability scale from 1 ( low ) to 5 ( high ). Shade tolerance was quantified using data from a systematic literature review (65 studies, 342 data points). Need for protection against climatic extreme weather events (late frost, heat, drought, heavy rain and hail) was evaluated by 26 farmers and experts. As proxies for need for protection , we further analysed water footprints and contribution margins available from crop databases. The analysis identified fruits and berries as highly suitable (5), whereas C4‐cereals and grain legumes' suitability is below average (2). Our findings emphasise the importance of synergy effects unique to dual land use systems such as agrivoltaics. The suitability of crop groups for agrivoltaics increases with their ability to leverage the synergy effects arising from physical protection against extreme weather events and microclimatic amelioration from shading. The suitability ranking of major temperate crop groups presented in this study can support future agronomic and policy decisions.

This study examines the relationship between carbon tax payments, electricity production costs, and carbon emission indicators in coal-fired power plants (PLTU) in Indonesia following the implementation of the carbon tax policy in 2022. Using post-implementation operational data, this study applies a descriptive and associative quantitative approach, acknowledging the potential endogeneity and mechanical relationships embedded in emission-based fiscal variables. The results indicate that carbon tax payments are not significantly associated with electricity production costs, suggesting that cost structures remain dominated by coal prices and operational efficiency. In contrast, a strong positive association is observed between carbon tax payments and carbon emission intensity, reflecting the mechanical linkage between emission-based taxes and emission indicators rather than policy effectiveness. These findings imply that the current carbon tax in Indonesia functions primarily as a fiscal and emission-reporting instrument, rather than an effective environmental control mechanism. The study highlights the need for complementary policies, technological upgrades, and more robust empirical designs to properly evaluate the environmental effectiveness of carbon taxation

The current research designs a biofuel supply chain network based on uncertain demand. This network combines economic, environmental, social, and transportation risk goals. A new multi-objective mixed-integer linear programming model has been developed. It includes three biomass types: second-generation Jatropha, livestock and agricultural waste, and third-generation microalgae. The model optimizes biodiesel and electricity production using transesterification and anaerobic digestion. It considers supplier discounts and uncertain demand using chance-constrained programming. According to the results, the least amount of energy is produced when the environmental goal is given the most importance. It will be less expensive to invest in social dimensions than in other goals, except for the economic one. The situation where energy production is prioritized has the highest costs and the biggest carbon emissions. The smallest social effects happen when reducing the risk of carrying hazardous materials is preferred. Overall, the largest deviation from all objectives occurs when the first objective function (energy) is prioritized, and the lowest distance to the optimal value of all objective functions occurs when reducing the transportation risk of hazardous materials has a higher weight and importance. Therefore, managers can get more advantages by focusing on reducing transportation risks and investing in it.

This article analyses shifts in Hungary's foreign direct investment (FDI) patterns under Viktor Orbán's government (2010–2023), highlighting a strategic reorientation from US to Chinese investors. Employing network centrality theory within global power competition, the study finds that US FDI stock declined from €15.4 billion in 2014 to €8.8 billion in 2022, while Chinese FDI tripled to €3.5 billion, increasingly targeting strategic sectors such as electric vehicles and battery production. Strategic partnership agreements disproportionately favoured Asian firms relative to their FDI share. Hungary's ‘Eastern opening’ strategy thus coincided with a pivot away from US investment, leveraging US–China rivalry to pursue autonomous economic strategies despite continued Western institutional integration.

Researchers and engineers are creating pertinent solutions to deal with water stress and rising energy demand.A very effective method is the cogeneration of thermal and electrical energy from a single primary source. The integration of gas turbines with a multieffect distillation (MED) desalination unit is described in this article. This synergy dramatically increases overall fuel efficiency to approximately 67%, lowers specific greenhouse gas emissions per unit of water and power produced, and lowers operating costs by using the high temperature exhaust from a gas turbine in a Heat Recovery Steam Generator (HRSG) to produce steam for thermal desalination. This study presents a technological scenario, analyzes the energy of each component, and looks at the benefits and drawbacks from an economic and environmental perspective. This article shows that combining a MED with a gas turbine presents a viable and sustainable alternative for the joint production of energy and drinking water. This work further emphasizes the applicability of integrated GT–MED cogeneration systems in arid coastal regions, where water scarcity and growing energy demand coexist. By improving fuel utilization and reducing specific emissions, this configuration provides a reliable, efficient, and environmentally sustainable solution for the simultaneous production of electricity and potable water.