Global Journal of Energy Technology Research Updates
The Global Journal of Energy Technology Research Updates (GJETRU) is an international, peer-reviewed journal that provides a forum for the dissemination of the latest research and advancements in the field of energy technology. The journal covers a wide range of topics related to the development and deployment of new and emerging energy technologies, including renewable energy, energy storage, energy efficiency, energy conservation, and more. The aim of GJETRU is to promote interdisciplinary collaboration and exchange of ideas among researchers, academics, and practitioners in the energy technology community. GJETRU publishes original research articles, review papers, and technical reports that advance our understanding of energy technology and its applications. The journal also provides a platform for the discussion of challenges and opportunities related to the transition to a more sustainable energy future. Whether you are a researcher, academic, or practitioner working in the field of energy technology, GJETRU provides a valuable resource for keeping up-to-date with the latest developments and advancements in this dynamic field. The journal is dedicated to promoting the development of sustainable energy solutions that can help to meet the growing global demand for energy, reduce dependence on finite fossil fuel resources, and enhance environmental sustainability.
All the published articles are licensed under the terms of the Creative Commons Attribution Non-Commercial License (CC BY-NC 4.0) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
Feasibility of Phase-Change Energy Harvesting in Cold Climates via Ice-Driven Latent Heat Recovery
This study investigates the feasibility of generating renewable energy by harnessing the latent heat released during the cyclical freezing of water. We propose a novel system wherein solar thermal energy is used to melt ice, and the resultant water is refrozen by exposure to the surrounding environment, acting as an environmental cold sink. The key innovation involves capturing the considerable latent heat released during the freezing phase via a working fluid and converting it into mechanical work using a low-temperature differential heat engine. Our thermodynamic modeling demonstrates that net energy production is theoretically achievable, contingent upon specific conditions of solar irradiance, ambient temperature, and heat engine efficiency. This work proposes a new pathway for energy generation in cold climates, potentially utilizing the extensive natural reservoirs of ice present in polar and alpine regions.
Renewable energy, Cryo-thermal cycle, Phase-change energy, Latent heat harvesting, Cold climate renewable.
Copyright (c) 2026 Yuan Li https://creativecommons.org/licenses/by-nc/4.0
Sustainable Industry 6.0 Manufacturing: Integrating Nanotechnology, Quantum Intelligence, and Autonomous Production Systems
The shift from Industry 5.0 to Industry 6.0 marks a significant change in manufacturing, with control transitioning from workflows to the materials themselves involved, while autonomous systems manage production at nanometer and quantum levels. Sustainable nanotechnology is at the heart of this evolution, combining environmental performance, process efficiency, and material precision as key governance factors. This chapter outlines a detailed framework for integrating sustainability into manufacturing choices, showing that environmental performance can shift from being an afterthought to a key factor in operational control. The discussion outlines mechanisms ranging from atomic-scale materials to fleet-level autonomy, positioning Industry 6.0 as a robust, energy-efficient, and scalable framework for future production systems.
Industry 6.0 manufacturing, Autonomous and smart factories, Quantum intelligent manufacturing, Sustainable manufacturing systems, Nanotechnology-enabled production.
Copyright (c) 2025 Dinesh K. Madheswaran, Ram Krishna, Suresh Gopi https://creativecommons.org/licenses/by-nc/4.0
Design and Simulation of an Electromagnetic Wave-based Electric Vehicle Charging Station
EVs are widely used, as they have become more popular due to sustainability and environmental factors; yet, traditional plug-in-charging infrastructure has numerous disadvantages, such as a long recharge time, poses a threat to user safety, and lacks ease of use. The paper is a modelling and simulation of an electromagnetic wave-based wireless charging station to be used in Electric vehicles. A Series-Series (S-S) inductive resonant coupling system using a topology of 85 kHz was modeled and designed. The mathematical modeling and simulation considered in MATLAB Simulink workspace allowed inclusion of an AC power source, rectifier circuit, transmitter and receiver coils, and a battery load. To determine the effect of circuit parameters on power transfer efficiency, a parametric sweep was carried out to assess the effects of the circuit parameters (inductance, compensation capacitance, mutual inductance, on-resistance diodes, and the distance between the coils) on the power transfer efficiency. The simulation findings indicate that the highest efficiency of 98.22 was achieved when the machine was operating under nominal conditions. Sensitivity and correlation analysis indicate that the primary-side inductance and capacitors of compensation have the most impact on the system performance. These results indicate the efficiency of the suggested model of wireless charging and the possible safety, efficiency, and convenience of EV charging infrastructure integration. Compared to standard research on infrastructure planning or inductive charging design, this paper is a comprehensive efficiency-based parametric and sensitivity analysis of an electromagnetic wave-based EV charging system.
MATLAB, Simulation, Electric vehicles, Wireless charging, Electromagnetic waves, Power transfer efficiency.
Copyright (c) 2025 Godwin O. Igbinosa, Nosagieagbon O. Imarhiagbe, Isaac-Great Atanda, Collins Fiemobebefa, Uwadiae Festus, Gbenga W. Bolarinwa https://creativecommons.org/licenses/by-nc/4.0
Exploring the Efficacy of Crab Shell-based Biochar for Adsorptive Uptake of Bromocresol Purple Dye in a Textile Wastewater: Kinetics and Mechanistic Studies
High-quality adsorbent derived from Crab Shell Activated Biochar (Fe₂O₃@BC) was effectively synthesised from discarded crab shells (CS) for the adsorptive elimination of Bromocresol purple colour (BCP) from textile wastewater. The structure of crab shell biochar (CSB) and crab shell activated biochar (CSAB) was looked at using SEM, and the light properties of the samples made from CSAB were checked with FTIR. The characterisation results suggested that the extracted chitin exhibited substantial properties necessary for surface phenomenon-driven matrices. This study looked at how well crab shell activated biochar and crab shell biochar can remove Bromocresol Purple (BCP) dye from water, finding that CSAB works better than CSB. The adsorption tests were conducted at varying pH levels, varied adsorbent doses, temperatures, and contact durations in batch trials. The kinetic analysis demonstrates that the removal efficiency was optimal according to the pseudo-second. The Weber–Morris intraparticle-diffusion analysis identified three operative adsorption sites. This low-cost crabshell-activated biochar, characterised by its advanced pore structure, distinctive surface properties, and superior adsorption capabilities, has the potential to function as an effective adsorbent for dye removal in textile effluent.
Biochar, Adsorption, Wastewater, FTIR and kinetics.
Copyright (c) 2025 Julius N. Ndive, Okechukwu D. Onukwuli, Ifeoma A. Obiora-okafo, Somtochukwu G. Nnabuife, Boyu Kuang https://creativecommons.org/licenses/by-nc/4.0
Techno-economic Analysis of a Small Hydropower Plant for Rural Electrification in Tanzania
This study assesses the feasibility of implementing a small-hydropower plant on the Ruhuhu River in Mavanga Village, Njombe Region, Tanzania, with a focus on both technical and economic performance. The technical analysis involved hydrological data (rainfall and flow rates) and field data collected via surveys and interviews. Key parameters included estimated hydropower capacity and civil works such as intake and penstock design. The findings indicate a water flow rate of 71.8 m³/s, power output of 98.67 kW, and a generator specific speed of 434.22 rpm, aligning with the use of a Kaplan turbine. The inlet structure showed a mean velocity of 1.162 m/s across a 3.68 m² trash rack flow area with a 4.28 m³/s flow rate. A penstock diameter of 20.8 cm and a wall thickness of 2.4 mm were determined to be appropriate for the design. In terms of economy, the investment cost was found to reach USD 200,000, with the net present value (NPV) of between USD 286,597.21 and USD 498,510.35 at a discount rate of 4 and 12%. The small hydropower plant demonstrates strong financial viability, with an internal rate of return (IRR) of 25.5%, far above typical discount rates, and a payback period of just 2.32 years, indicating rapid capital recovery. A return on investment (ROI) of 330.6% and a profitability index (PI) of 2.49 further confirm its high profitability and investment appeal. The proposed small-hydropower plant demonstrates both technical feasibility and high economic return, making it a viable solution for enhancing rural electrification in Tanzania. Its successful implementation can serve as a replicable model for other off-grid communities seeking sustainable and cost-effective energy access.
Copyright (c) 2025 Abasi Issa Milambo, Pius V. Chombo, Oscar A. Zongo, Ramadhani O. Kivugo, Gerutu B. Gerutu, Kenedy A. Greyson, Sosthenes F. Karugaba https://creativecommons.org/licenses/by-nc/4.0
Prediction of Offshore Photovoltaic Installed Capacity Driven by Both System Dynamics and Policy Factors
To address the impact of photovoltaic (PV) policies on the expansion of offshore PV installed capacity, this study proposes a prediction model based on system dynamics (SD) theory. This model quantifies policy types and practical situations, and the scoring results reflect the policy's influence effectiveness. The Grey Wolf Optimizer (GWO) is employed to optimize the influence coefficients of supportive, guiding, and developmental policy effectiveness within the model, thereby improving the model's precision and accuracy. First, a system dynamics model was constructed to analyze the relationships among PV power generation costs, revenues, installation willingness, and installed capacity. Then, the policy implementation effect was integrated into the SD model in the form of policy effectiveness, and a policy effectiveness evaluation system was established. Finally, simulation prediction and analysis were conducted. Predicted values of offshore PV installed capacity in Jiangsu Province from 2021 to 2024 were compared with actual data to verify the effectiveness of the model. Subsequently, offshore PV installed capacity and investment costs from 2025 to 2030 were simulated and analyzed. Case study results indicate that the predictions of the proposed model are consistent with industry development trends and provide valuable references.
Copyright (c) 2025 Xin Wang, Renjie Xiao, Wei Hu https://creativecommons.org/licenses/by-nc/4.0
Experimental Evaluation of a Simulated Geothermal Heat Pump System for Potential Large-Scale Space Heating Application at TBRHSC in Severe Cold Climate in Northwestern Ontario, Canada
Space heating for buildings and institutional complexes represents a dominant sector of energy consumption and greenhouse gas (GHG) emissions in Canada, a challenge exacerbated by the nation’s cold climate. This is particularly critical in regions like Thunder Bay, where harsh winters and significant heating demands make the building sector a major contributor to local emissions—the residential sector alone accounts for 27% of community GHG output. The geothermal heat pump (GHP), or ground-source heat pump, is a highly efficient technology that leverages the stable thermal energy of the subsurface to provide space conditioning. By using the ground as a heat source in winter and a heat sink in summer, GHPs can reduce heating and cooling energy use by 25–50% compared to conventional systems. This makes them a promising solution for large-scale space heating applications, such as at the Thunder Bay Regional Health Sciences Centre (TBRHSC), a major healthcare facility and one of the city’s largest energy consumers. Despite this potential, there remains a significant gap in region-specific performance data and operational understanding of GHPs in extreme cold climate in Northwestern Ontario. This study addresses that gap through experimental characterization of a lab-scale GHP system using actual subsurface temperature profiles. An extensively instrumented GHP simulator was employed to evaluate system performance across a key range of operating conditions. The experimental results showed that the supply air temperature from the GHP system rises rapidly following system start-up, with each tested condition achieving approximately 90% of its peak value within the first 4 to 5 minutes. A consistent thermal gain of the GHP was observed, where each 5°C increase in entering water temperature yielded an additional 3°C rise in the useful supply air temperature. The temperature gradients plateau after 10 min indicating that the system has achieved a thermal steady state. Progressively increasing the simulated ground-loop water temperature entering the GHP’s evaporator from 5°C to 10°C and then to 15°C resulted in a corresponding rise in supply hot air temperature and an improvement in the GHP system’s coefficient of performance (COP).
Copyright (c) 2025 Basel I. Ismail, Anjali Nagi https://creativecommons.org/licenses/by-nc/4.0
Optimization of Solar Photovoltaics Tilt Angle for Hybrid Solar-Geothermal Heat Pump Applications in Extreme Cold Climate Regions of Northwestern Ontario, Canada
The global imperative to mitigate greenhouse gas emissions, combat air pollution, and manage escalating energy costs and demand underscores the critical role of renewable energy technologies. Solar photovoltaic (PV) systems present a viable solution by directly converting sunlight into electricity, especially for energy-intensive facilities in regions with high solar potential, such as Northwestern Ontario, Canada. The tilt angle of a PV panel is a fundamental parameter that significantly influences the amount of incident solar radiation, thereby directly affecting the system's power output and overall economic efficiency. This study employs location-specific experimental data and validated numerical modeling to determine the optimal monthly and annual tilt angles for a PV array intended to potentially power a geothermal heat pump (GHP) at the Thunder Bay Regional Health Sciences Centre located in a severe cold climate region of Northwestern Ontario. Optimizing this angle enhances efficiency, reduces operating costs, and improves the commercial viability of the hybrid system. Analysis revealed that the monthly optimal tilt angle varies from 3° in June to a maximum of 69° in December and January. The annual fixed-angle optimum is approximately 39°. Solar irradiance peaks in June at roughly 5.14 kWh/m², falling to its annual minimum in December at about 49.2% of this peak. To specifically support the GHP during its peak heating demand, a winter-optimized tilt of 67° is recommended. This configuration captures an average maximum of 3.14 kWh/m²/day during the coldest months, aligning solar energy harvest with the facility's highest heating loads. Furthermore, the site experiences a substantial variation in available solar energy hours, with monthly average daily daylight hours ranging from a low of 8.2 hours (in December) to a high of 15.8 hours (in June). The estimated annual optimum tilt angle of 39° for TBRHSC aligns with the 31°–45° range reported for similar latitudes, and the corresponding predicted solar irradiance of 3.94 kWh/m²/day shows good agreement (<7% difference) with international benchmarks. The study's primary applied contribution is the proposal of a load-specific, winter-optimized tilt of 67°—a strategic adaptation designed to enhance the technical and economic feasibility of integrated solar-GHP systems operating under the harsh climatic constraints of Northwestern Ontario.
Techno-Economic Assessment and Sensitivity Analysis of Electricity Generation from Wind Energy in a Low-Wind-Speed Region of Egypt
This study conducts a detailed techno-economic evaluation and sensitivity analysis of wind energy generation in Egypt’s Fayoum Governorate, a region characterized by low wind speeds. It represents the first investigation of wind energy potential encompassing four key locations within the governorate: Qarun Lake, Rayan Valley, Kom Ushim, and Fayoum City. Statistical analysis of long-term wind data, based on the Weibull distribution, shows a consistent average wind speed of 6.02 m/s at a 50-meter hub height across all sites. Eight small- to medium-scale wind turbines were assessed for their annual energy output, capacity factor, and Levelized Cost of Electricity (LCOE) using the System Advisor Model (SAM). Among these, the Endurance E3120 50 kW turbine emerged as the most cost-effective, with the lowest LCOE of 4.85 ¢/kWh and the highest capacity factor. The sensitivity analysis identified capital cost as the dominant factor influencing LCOE, followed by the fixed charge rate. Overall, the findings confirm the technical and economic viability of small wind turbine deployment in low-wind-speed inland areas, encouraging broader adoption of decentralized renewable energy solutions in Egypt.
Copyright (c) 2024 Suzan Abdelhady https://creativecommons.org/licenses/by-nc/4.0
Assessment of User Preferences in Electric Vehicle Charge Billing System
Despite the advantages of electric vehicles (EVs), however, their adoption rate in Tanzania remains low. The growth and sustainability of EVs remain questionable due to several factors including an insufficient network of charging infrastructure coupled with billing systems. This study analyzes user preferences related to EV charge billing requirements based on the qualitative assessment of semi-structured interviews with EV users. A survey was conducted around Dar es Salaam city and around 81 sample surveys were administered. The targeted parameters are current EV charge types, daily charging frequency, charging duration, billing system, bill payment, and expectations on public charging infrastructure. The factors were selected to enable an understanding of the drivers for improving acceptance of EV charge billing systems and deduce their market potential. For electric two-wheelers (e2Ws), the findings indicated that 60% of e-bicycle riders charge once per day, 30% charge twice per day, and 10% charge 3 times per day. Moreover, 34% of e-bicycle batteries were charged with 50% of energy remaining in the battery, which took 2 to 3 hours. Contrary, 40.74% of electric three-wheelers (e3Ws) were charging 2 times per day, 33.33% were charging 3 times per day, and 25.93% were charging 1 time per day. In terms of billing, e-bicycles’ charging energy was metered but not billed while e3Ws’ charging energy was not metered but billed at a flat rate regardless of the energy consumed. The majority of EV drivers expected more public charging stations to be equipped with accurate energy measuring systems to enable them to pay-per-use.
Copyright (c) 2024 Eva Maeda, Georgia Rugumila, Kenedy A. Greyson, Gerutu B. Gerutu, Esebi A. Nyari, Ramadhani O. Kivugo, Frank Lujaji, Pius V. Chombo https://creativecommons.org/licenses/by-nc/4.0
Assessment of Electricity Consumption of Middle-income Households in Tanzania
Electricity is the foundation of modern society, powering a vast array of daily activities and technological advancements. Despite increased electricity access, the majority of Sub-Saharan African countries face the dilemma of energy consumption outpacing generation. Gaining a good grasp of behavioral drivers of energy use, especially among middle-income households (MIHs), is necessary to reduce energy consumption. This study assesses the electricity consumption from MIHs in a targeted area of Masaki, Dar es Salaam region, Tanzania. The study integrated the household characteristics and electrical load consumption patterns in the electricity consumption of MIHs. The 1-month data, between May 2024 and June 2024, were gathered from 99 respondents using an e-questionnaire. The household characteristics included the number of occupants per household, awareness of energy management programs, adoption rate, and interested features and expectations in energy management programs. The electrical load consumption patterns include types of electrical loads, hourly usage, average monthly bills, and fluctuations in monthly energy bills. Findings revealed that the average number of occupants per household was 6, but only two out of 6 occupants per household were aware of energy management programs. Appliance control was the most adopted energy management program (44.12%) followed by real-time energy monitoring (11.76%) and integration with renewable energy sources (8.82%). Contrary, about 96% of respondents were interested in engaging in energy management initiatives aiming at cost-saving (62%) and convenience (20.7%). Evening hours reported to use the most energy (68.7%), followed by night hours (50.5%). The average monthly energy bills were found to range between TZS 70,000 and TZS 300,000 with 48.5% of respondents reporting large swings in their electricity expenses. The findings of this study provide policymakers with evidence that awareness initiatives should be included when formulating energy consumption and efficiency strategies.
Copyright (c) 2024 Regina Mvungi, Respicius Kiiza, Pius Victor Chombo https://creativecommons.org/licenses/by-nc/4.0
An Assessment Tool for Energy Audit of Buildings in Jordan Using Simulation
In developed nations, there's a growing concern for sustainable energy management, particularly regarding enhancing energy efficiency in both existing and new buildings. The methodology presented considers the energy modelling and simulation of manufacturing buildings through thermal and electrical loads calculations using Dymola/Modelica software. The thermal model is built with the primary components of Dymola along with available models to calculate the heating and cooling loads, whereas the electrical model was calculated using consumption patterns, then the total model was validated against real measurements where the error percentage was 9.96 %. The yearly heating load baseline was 6295 kWh/y and for cooling 46276 kWh/y., the exciting potential for energy- savings and load flexibility, and some suggestions for improving consumption were pointed out and identified. It found that the highest influence on the thermal load reduction was using the double glaze with shading with 61% of the energy-saving options, then replacing the fluorescent with LED with 30%, and finally, the roof insulation was the least influence with 9.5%. For the total consumption, the highest percentage was for replacing the fluorescent with LED with 78% of energy-saving options, then double glaze with shading, and finally the lowest is for the roof insulation.
Copyright (c) 2024 Abeer Al-Jbour, Heba Abutayeh, Bashar R. Qawasmeh https://creativecommons.org/licenses/by-nc/4.0
Renewable Energy Sourcing to Enhance Sustainable Manufacturing by Using Madhab’s EEE Impact Analysis Model
The world's increasing energy demand, coupled with the depletion of finite energy resources, necessitates a shift towards sustainable energy solutions. This research explores the multifaceted benefits of substituting conventional fossil fuel-based energy sources with renewable energy in industrial settings, with a focus on sustainable manufacturing. A case study was conducted at a printing and packaging factory in Bhubaneswar, Odisha, to analyze economic, environmental, health, safety, and efficiency factors associated with various energy options based on the Madhab’s EEE (Environmental, Efficiency, Economic) impact analysis method. The study identified solar power generation as the optimal energy source, boasting the lowest EEE impact index of 1.90. Wind energy ranked second, followed by conventional GRID power and DG (Diesel Generator) power sources, which were found to be less favorable due to their higher EEE impact indices. Feasibility assessments revealed that the factory had ample rooftop and vacant land space for solar power plant installation, making it self-sufficient in power generation. The return on investment (ROI) for the solar power project was calculated to be 5.54 years, making it a viable option from a sustainability perspective. Moreover, the solar system could be integrated with the GRID through a reverse metering system, enabling excess energy to be sold back to the GRID. This research underscores the significance of transitioning to renewable energy sources in industries for environmental sustainability, energy security, and economic benefits. It emphasizes the need for similar studies in diverse industrial settings to identify the most suitable energy sources, considering all relevant factors.
Copyright (c) 2023 Madhab C. Jena, Sarat K. Mishra, Himanshu S. Moharana https://creativecommons.org/licenses/by-nc/4.0
Research on Industrial Economic Development and Electricity Price Adjustment Strategy Based on Multi-Agent Game
With the deepening of the electricity market reform and the accelerating transformation of the new power system, the number of new electricity customers in the market with local development characteristics has increased. The local industrial and economic development have been affected by the ability to guide electricity prices. In this paper, using the multi-agent game based on exploring the impact of electricity price on the industrial economy, the specific optimization scheme of electricity price adjustment is proposed with the aim of improving the overall efficiency of the power grid and reducing the cost of electricity for industrial users. After the game, the overall efficiency of the electricity supplier will be increased by about 3.06 percent, and the cost of electricity used by various special industries will be reduced by about 6.86 percent to 4.48 percent. The win-win situation of the electricity suppliers’ income and the featured industries’ development can be achieved by the optimization results. As well as the cost of electricity consumption in featured industries can be reduced, and the comprehensive benefits of electricity suppliers can be improved by using the electricity price adjustment scheme after game interaction, which promotes the rational use of energy and meets the current social requirements for the green and sustainable development of the electricity industry.
Copyright (c) 2023 Qianhui Cai, Xue Han, Wei Wang https://creativecommons.org/licenses/by-nc/4.0
Visualization Experiments of Radial-Rotating Oscillating Heat Pipe Filled with Methanol
Oscillating heat pipes (OHP) have highly efficient heat transfer capability. Some researchers have applied OHPs to cutting tools and rotating machines by embedding tubular OHPs in machines or by making flow channels on metal plates. Most studies are on heat transfer performance, and there are few studies on the heat transfer behavior of radial-rotating oscillating heat pipes (RR-OHP) under operating conditions. This paper conducted the visualization test of an RR-OHP filled with methanol by studying the flow patterns and motion modes at rotation speed (0-860 rpm) and heat flux (20000-40000 W/m2). When the heat flux is increased from 20000 W/m2 to 40000 W/m2, the flow patterns include flowless, slug flow, annular flow, and churn flow, and the motion modes contain oscillatory motion, cyclic motion, unilateral boiling, and bilateral boiling. The distribution map of the flow patterns and motion modes with the centrifugal acceleration and the heat flux was plotted, which shows the evolution of the flow patterns and the transformation of the motion modes of the RR-OHP, and elucidates the effect of the centrifugal acceleration and the heat flux on the flow patterns and motion modes.
Copyright (c) 2023 Jiaren Wang, Ning Qian, Yucan Fu https://creativecommons.org/licenses/by-nc/4.0
Thermo-Economic Performance of Organic Rankine Cycle-Based Waste Heat Recovery for Power Generation at a Wide Range of Operating Conditions
This study assesses the performance of organic Rankine cycle-based waste heat recovery systems under different working fluids and operating conditions. The basic ORC (BORC) and ORC with recuperator (RORC) are investigated for power generation and economy using toluene and benzene. Thermodynamic and economic indicators are studied at various expander inlet temperatures, expander inlet pressure, evaporation temperature, and condensation temperature. RORC achieves higher ηth by reducing heat source in the evaporator whereas BORC recovers more waste heat and improves Pnet. With toluene, BORC improves Pnet when increasing the expander inlet temperature and pressure. The lowest LCOE of 0.0532 US$/kWh is from BORC operated with toluene at a Pnet of 349 kW and decreases with an increase in expander inlet temperature. The addition of a recuperator adds to the costs of initial investment and LCOE and slightly improves the performance of the ORCs for waste heat recovery.
Copyright (c) 2023 Gerutu B. Gerutu, Ramadhani O. Kivugo, Frank Lujaji, Pius V. Chombo https://creativecommons.org/licenses/by-nc/4.0
Grid Search for SARIMAX Parameters for Photovoltaic Time Series Modeling
The SARIMAX (Seasonal Autoregressive Integrated Moving Average with eXogenous regressors) model is a time series model that can be used to forecast future values of a time series, given its past values. It is beneficial for modeling time series data that exhibits seasonality and incorporating additional exogenous variables (variables that are not part of the time series itself but may affect it). One way to optimize the performance of a SARIMAX model is to use a grid search approach to find the best combination of hyperparameters for the model. A grid search involves specifying a set of possible values for each hyperparameter and then training and evaluating the model using all possible combinations of these values. The combination of hyperparameters that results in the best model performance can then be chosen as the final model. To perform a grid search for a SARIMAX model, you must define the grid of hyperparameters you want to search over. This will typically include the values of the autoregressive (AR) and moving average (MA) terms and the values of any exogenous variables you want to include in the model. We will also need to define a metric to evaluate the model's performance, such as mean absolute or root mean squared error. Once we have defined the grid of hyperparameters and the evaluation metric, you can use a grid search algorithm (such as a brute force search or a more efficient method such as random search or Bayesian optimization) to evaluate the performance of the model using all possible combinations of hyperparameters. The combination of hyperparameters that results in the best model performance can then be chosen as the final model. In this article, we will explore the potential of SARIMAX for PV time series modeling. The objective is to find the optimal set of hyperparameters. Grid Search passes all hyperparameter combinations through the model individually and checks the results. Overall, it returns the collection of hyperparameters that yield the most outstanding results after running the model. One of the most optimal SARIMAX (p,d,q) x (P, D, Q,s) combinations is SARIMAX (0,0,1) x (0,0,0,4).
Copyright (c) 2022 Todizara Andrianajaina, David Tsivalalaina Razafimahefa, Raonirivo Rakotoarijaina, Cristian Goyozo Haba https://creativecommons.org/licenses/by-nc/4.0
Design and Performance Characteristics of a Hybrid Photovoltaic-Thermal Regeneration System under Indoor and Outdoor Solar Radiation Conditions of Thunder Bay, Ontario
Numerous energy sources continuously emit large amounts of waste energy into the earth's atmosphere. Significant losses, nearly 85% of the incident light on a PV panel, are either reflected from the PV surface, accounting for up to 20%, or dissipated as heat. In this work, a novel lab-scale hybrid photovoltaic-thermal regeneration (HPVT-R) system is designed, constructed, and tested to restore some of the reflection losses in the PV system. The new HPVT-R system design permits the PV and thermal co-systems to perform autonomously while revitalizing some of the reflection losses by hybridization. Thorough testing of the HPVT-R system was performed under lab-scale indoor simulated light and outdoor solar radiation conditions in Thunder Bay, Ontario. The HPVT-R system regenerated approximately 14 % of the reflected light in these tests, transforming it into electrical power and heat. Under the solar-simulated lights, the indoor test setup regenerated around 17 mW of electric power from the reflected light accounting for slightly less than 1% of more electric power per unit PV surface area. However, the outdoor solar radiation tests rejuvenated nearly 137 mW of electric power, accounting for approximately 3% more electric power per unit PV surface area, with a conversion efficiency of nearly 7%. Regarding heat energy, the HPVT-R system regenerated approximately 34% more in indoor and outdoor performances entirely from the reflected light. This research investigates the performance aspects of the HPVT-R system operated under different working conditions.
Copyright (c) 2022 Basel I. Ismail, Amos Jose https://creativecommons.org/licenses/by-nc/4.0
Review on Performance Analysis of Desiccant-Assisted Hybrid Cooling Systems
Due to the growing expense of fossil fuels and other environmental issues, it is crucial to reduce the energy cost of built environment cooling systems without sacrificing indoor air quality and comfort levels. One option in this area is solid desiccant dehumidification-assisted cooling systems, which employ alternative energy sources like solar and biomass and are also environmentally beneficial by the minimal requirement of refrigerants. The present review discusses the performance analysis of different solid desiccants readily accessible on the market and their composites. Better moisture absorption and a lower regeneration temperature are qualities of a better desiccant. The review also discusses the various solid desiccant dehumidifier designs, their benefits, and their disadvantages. Solid desiccant dehumidifiers now come in various combinations, considerably enhancing system performance. The exergy efficiency of desiccant-integrated evaporative cooling is up to 21.5%, comparable with another HVAC system. A summary of the performance parameters has also been created to assess system performance further. This study will benefit innovation and advancement in solid desiccant materials in the air conditioning market.
Copyright (c) 2022 D.B. Jani https://creativecommons.org/licenses/by-nc/4.0
Smart Switching Power Supply System for Evaporative Air Coolers
The energy consumption by residential air conditioners could cost about half of the total energy consumption of the building. A combination of conventional and renewable energy is still an emerging technology. Therefore, using solar photovoltaic panels to provide electricity to the air conditioner is a substantial application. This research shows the possibility of using photovoltaic panels as a power source for air conditioners in a sequence exchange with the conventional grid. A smart switching system has been offered to organize the power supply between the grid and solar panels. The photovoltaic panels have been connected to the conditioner across a power inverter module for adopting a reliable and accurate quantity of power supply to the conditioner unit. The smart switching system provides an intelligent connection between the solar power source and the grid, ensuring an uninterrupted electricity supply between the two power sources.
Copyright (c) 2022 Mohammed Almarzouq, Ahmed Al-Somali, Saud Al-Abdulkarim , Amr Owes https://creativecommons.org/licenses/by-nc/4.0
Stakeholders' Perception of Bioenergy Projects in Marginal and Underutilized Lands in Italy
Large land areas in European countries can be considered marginal, underutilized, and contaminated (MUC). Many recent studies have shown that bioenergy crop cultivation can make this land profitable, creating new income opportunities for local citizens without interfering with food production. However, farmers, landowners, and local communities must become more familiar with bioenergy systems, potential value chains, and markets. This paper aims to present the results of stakeholder consultations implemented in two case study areas in Italy, i.e., Basilicata and Sardinia, about the possible establishment of bioenergy systems in the MUC land available at the local level. Stakeholders' perceptions were collected through interviews conducted on a one-to-one basis and through multi-stakeholder working group meetings organized in the context of BIOPLAT-EU, an H2020 project aimed at promoting the efficacy and profitability of using MUC land for sustainable bioenergy production. By and large, the findings of the consultations indicate that local stakeholders are prone to accept the establishment of innovative bioenergy value chains based on the cultivation of MUC lands in their regions. The majority of them recognized that bioenergy could bring a wide range of benefits at the local level, not only in terms of environmental externalities but also of economic and social development, such as through the creation of new business and job opportunities, therefore serving to alleviate or prevent the land abandonment and population decline currently on-going in these areas.
Copyright (c) 2022 Tiziana Pirelli, Giuseppe Pulighe https://creativecommons.org/licenses/by-nc/4.0
Photovoltaic Power Generation Forecasting Based on the ARIMA-BPNN-SVR Model
With the continuous expansion of the capacity of photovoltaic power generation systems, accurate power generation load forecasting can make grid dispatching more reasonable and optimize load distribution. This paper proposes a combined forecasting model based on Auto Regression Integrate Moving Average (ARIMA), back propagation neural network (BPNN), and support vector regression (SVR), namely ARIMA-BPNN-SVR model, aiming at the problem of low accuracy of a single model and traditional forecasting model. Through the complementary advantages of ARIMA, BPNN, and SVR models, the model has good anti-noise ability, nonlinear mapping, and adaptive ability when processing photovoltaic power generation data. Data experiments are carried out on solar photovoltaic power generation in the United States, and the accuracy of model forecasting is evaluated according to MAE, MSE, RMSE, and MAPE. The experimental results show that the proposed ARIMA-BPNN-SVR outperforms the forecasting performance of the single models ARIMA, BPNN, and SVR. Its MAE, MSE, RMSE and MAPE are 0.53, 0.41, 0.64 and 0.84 respectively. In the Wilcoxon sign-rank test, the p-value of the proposed model reached 0.98, indicating the effectiveness of the ARIMA-BPNN-SVR model.
Auto regression integrate moving average (ARIMA)
Copyright (c) 2022 Guo-Feng Fan, Hui-Zhen Wei, Meng-Yao Chen, Wei-Chiang Hong https://creativecommons.org/licenses/by-nc/4.0
The Effect of Storing Produced PV Power on the National Grid
The dramatic increase in renewable sources employment and the new trend to eliminate carbon emissions are the main reasons for using energy storage to overcome the fluctuation of Photovoltaic (PV) output. This paper aims to study the ability of PV solar system, to provide a significant fraction of utility systems energy demand in Jordan. MATLAB software was used to simulate algorithms in order to estimate the storage properties of Energy Capacity (EC), Power Capacity (PC), and Capacity Ratio (CR). These properties are mainly affected by the size of the PV system and the flexibility (ff) of the grid. The hourly generation data from the National Electric Power Company (NEPCO) were investigated to determine the most efficient way to feed PV-generated power into the grid. It was found that for flexibilities (ff) values of 0.7, 0.8, and 1, the No-Dump (ND) PV system, which is the largest PV system that could deliver all its annual production to the grid without any need of spillage of the PV system size were 566.3MW, 998.4MW and 1.6 GW respectively. Also, the relation between Energy Capacity of storage (EC) and Power Capacity (PC) was investigated, it was found that if storage installed with EC and PC equal to 24 GWh (almost 45% of average daily demand) and 3 GW (which is less than the peak hour demand) at ff=0.8, the penetration of PV energy will increase by 42% of annual demand compared with almost 10% without storage. Furthermore, if ff is increased to 1 in parallel to installing storage with energy capacity and power capacity equal to 52.7 GWh and 4.7GW, respectively, the PV penetration will increase to reach 68% of the annual demand compared to 16% without storage.
Copyright (c) 2022 Heba Abutayeh, Mohammad Hamdan, Eman Abdelhafez https://creativecommons.org/licenses/by-nc/4.0
Energy, Exergy and Exergo-Economic Analysis of an OTEC Power Plant Utilizing Kalina Cycle
This study aims to analyse an Ocean Thermal Energy Conversion (OTEC) system through the use of a Kalina Cycle (KC), having a water-ammonia mixture as a working fluid. KC represents a technology capable of exploiting the thermal gap of ocean water. This system was then compared with OTEC systems, which exploit ammonia, R134A and butane-pentane mixture as working fluid. The comparison was carried on through energy analysis, exergetic analysis, and exergo-economic analysis using the EES (Engineering Equation Solver) software. For each case study, cost rates and auxiliary equations were evaluated for all components and the mass flow rate and unit exergy cost for each stream. The results showed that the KC with water-ammonia as working fluid achieves the best exergo-economic performance among the examined cycles. The cost of electricity produced through KC using water - ammonia mixture was found to be 26,66 c€/kWh. The thermal efficiency and the exergetic efficiency were calculated and the withdrawal depth of ocean water was considered. The efficiencies resulted to be 3.68% for the thermal efficiency and 95.96% for the exergetic efficiency.
Special Issue: Sustainable Optimization of Energy Systems
Copyright (c) 2021 Giuseppe Basta, Nicoletta Meloni, Francesco Poli, Lorenzo Talluri, Giampaolo Manfrida https://creativecommons.org/licenses/by-nc/4.0
Thermodynamic and Exergetic Analysis of the Allam Cycle
This paper presents the study on the current developments of oxy-combustion thermodynamic cycles, which use the CO2 produced by combustion within the cycle itself without releases into the atmosphere. This is the cause of the attention paid to this type of technology and which makes these cycles one of the avant-gardes of power plants. In particular, this study focuses on the analysis of the Allam cycle with the aim of evaluating its performance and therefore investigating whether it may be an alternative to the series of CO2 control technologies. In this paper, a first principle efficiency of 54.6% and a second principle efficiency of 55.7% are estimated, confirming the outstanding prospect of the NET Power cycle.
Copyright (c) 2021 Elisa Mariani, Lorenzo Talluri, Giampaolo Manfrida https://creativecommons.org/licenses/by-nc/4.0
Evaluation of the Energy Transition in the Process of Renewable Sources Expansion
Considering the risks related to energy security and the challenges posed by climate change, this work presents a methodology to investigate energy alternatives to promote an adequate energy transition. Such methodology was applied to a case study, modelling the energy system of the Brazilian State of Minas Gerais to subsidize an energy transition with a view to expanding renewable energies and promoting energy efficiency at the state and municipal levels, as well as combating climate change. Projections, in the 2030-2050 horizon, were made using the tool Long-range Energy Alternatives Planning System (LEAP) to establish a model of energy transition policy for Minas Gerais State. The modelling considered key assumptions based on historical data of demographic and economic origin, which subsidized the elaboration of three scenarios, being a Reference Scenario (REF), a Moderate Energy Transition Scenario (ETM) that aims to contribute to the energy sector goals of the Brazilian Nationally-Determined Contributions – NDC, and an Advanced Energy Transition Scenario (ETA) that goes beyond of NDC's goals. The analysis has shown that current policies are not sufficient to promote the state transition to sustainable energy systems and that this process will depend on the energy policies initiated and implemented in the near future.
Long-range Energy Alternatives Planning System
Copyright (c) 2021 Morjana M. dos Anjos, Antonella L. Costa, Elizabeth M.D. Pereira, Gustavo N.P. de Moura https://creativecommons.org/licenses/by-nc/4.0
Identification of Faulty Operation in Photovoltaic Panels
Increasing the efficiency of photovoltaic panels (PV) is one of the important goals of researchers worldwide in the field of renewable resources. The important results obtained in the case of finding new materials for the manufacturing of the panels to obtain the highest possible conversion efficiency must be doubled by research for developing methods for efficient real-time monitoring of PV operation in order to rapidly or in advance identify possible failures. This paper looks for some types of failures and how they can be identified as quickly as possible from the information coming from different sources, the most important being the PV monitored parameters, the PV control system parameters, and from different cloud services. One way to identify different types of failures is to use machine learning (ML) methods. In applying these methods, an important thing is the availability of a great number of good training data sets. In order to obtain such data sets, this paper aims to create a model of PV using Matlab, which is fed with both real data and data synthesized using fault models. A number of four simulation cases were considered which take into account the normal operation of the photovoltaic panels, their malfunction due to a failure (two different types of failures were considered), and the malfunction of the panels due to the appearance of the two types of failures simultaneously, using input data that was partially measured and partially generated in Matlab. The outputs of these model simulations will be used for training the ML model.
Copyright (c) 2021 Cristian-Gyozo Haba https://creativecommons.org/licenses/by-nc/4.0
Seamless Switching Technology of UPQC Based on Improved Power Angle Control
This paper presents a novel seamless switching technology between different operating conditions of the Unified Power Quality Conditioner (UPQC) with the energy storage system. Frequent start and stop of the series inverter will cause shock and loss under the conventional control method. Moreover, it is a key issue to achieve seamless switching when the UPQC operating condition changes. This paper proposes an improved power angle control (PAC) method to solve these problems. An agile power angle is calculated by this method under stable operating conditions. This feature enables the series inverter to share the load reactive power with the shunt inverter. On the other hand, both the series and shunt inverters are in an easy-to-switch operating state which can help achieve better seamless switching between different operating conditions. Simulation results show the shunt inverter capacity can be reduced up to 47% due to the reactive power sharing by both the inverters which means the reactive power burden of the shunt inverter is great lightened. It is also found that the switching time is about 300μs faster and the maximum voltage fluctuation amplitude is about 90V smaller under improved PAC than the conventional control method.
Copyright (c) 2021 Zhengwei Qu, Zhe Shi, Yunjing Wang, Ahmed Abu-Siada, Baona Wang, Haiyan Dong https://creativecommons.org/licenses/by-nc/4.0
Research on Investment Strategy and Evaluation Mechanism of Power Enterprises Considering Local Development Characteristics
The investment in developing industries with local characteristics is an essential link in the industrial investment chain of power enterprises. Reasonably selecting industries worthy of investment will significantly improve the income of power enterprises. Firstly, this paper constructs an investment project benefit evaluation system including economic benefit indicators and social environment indicators. Secondly, the combination of the analytic hierarchy process and grey correlation method is used to determine the index weight, and the comprehensive evaluation method is used to calculate the score of each index. Finally, the corresponding investment proportion allocation model is established to calculate the relevant industries worthy of investment.
Copyright (c) 2021 Jiahui Yang, Wei Wang, Ke Duan, Yifan Yang https://creativecommons.org/licenses/by-nc/4.0
Analytical and Comparative Study of a Mini Solar-Powered Cogeneration Unit Based on Organic Rankine cycle for Low-Temperature Applications
In this paper, we analyze characteristics of a small Combined Heat and Power (CHP) system based mainly on Organic Rankine Cycle (ORC) and heating plant in actual series connection regarding the low-temperature heat carrier heated by purely solar flat collector field. Simultaneously and for specific power production, comparison of this layout with stand-alone ORC, and with the traditional ORC-CHP imposing gain of condenser heat for heating aims, in second step, has been conducted. For evaluation, energetic and design criteria have been determined opposite the heating effects and also temperatures of the heat source and sink. The simulations addressed interesting optimization ratios till 24 % for the power unit throughout this series CHP utility versus single power generation at the same conditions tested. Moreover, the high heat source temperatures and CHP ratios improve the performance of the overall series plant, while the high supply and return temperatures have negative effects. Finally, the ORC-CHP scheme handled here highlights distinctive exploitation aspects and more suitability in wide range of application in comparison to yielding the high-temperature condensation heat of ORC, especially at low ambient temperatures, high supply and heat source temperatures. So, it can be advised to be adopted instead of the two other strategies.
Copyright (c) 2014 Muhsen Habka, Salman Ajib https://creativecommons.org/licenses/by-nc/4.0