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The recent effects of climate change and rising global warming levels have increased the need to transition towards clean energy. The use of multi-energy systems is one of the potential solutions to these issues, as validated in the literature. The production of hydrogen from cleaner sources has an integral role in decarbonizing the industrial, building, and transportation sectors. Hence, this study proposes novel multi-energy systems that can produce hydrogen from wind resources. The study is novel as it developed an innovative multi-energy system configuration and also considers hydrogen production as a means to utilize excess wind power production. The intermittency of wind resources has been a major drawback in using this renewable energy as the singular source for multi-generation systems. The multi-energy configuration developed and analyzed in this study proposed a solution for this by integrating a regenerative reheat biomass integrated power cycle as an auxiliary system for the multi-generation system (Wind-Bio-MGS). This system is modeled to produce electricity, heating, hot water, and hydrogen. The energy, exergy, and exergoeconomic approach is adopted in this study to evaluate the steady-state performance of the system, while the levelized cost of electricity (LCOE), levelized cost of heating (LCOh), and levelized cost of Hydrogen (LCOH) are also computed. A multi-objective optimization of the overall exergy efficiency and total product unit cost is presented. The parametric analysis of the energy systems is included to show the sensitivity of different parameters to changes and validate the robustness of the modeled system. The results show that the integration of hydrogen with wind-based multi-generation systems is a viable means of reducing carbon emissions and global warming. The overall energy and exergy efficiencies of the Wind-Bio-MGS system are 69.13% and 31.16%, respectively. The LCOE, LCOh, and LCOH for the system, respectively, are 0.02828 $ kWh−1, 0.004038 $ kWh−1, and 1.311 $ kg−1 s−1. [ABSTRACT FROM AUTHOR]

It is vital, following the Kyoto Protocol, to find environmentally benign and energy-efficient refrigerants, consequently boosting the coefficient of performance (COP). Refrigeration systems are used extensively in the industrial, home, and commercial sectors for cooling, heating, food preservation, and cryogenic purposes. Researchers have successfully employed the application of nanoparticles in cooling systems to achieve improved enhancement, reliability, and efficiency of refrigeration systems because of their higher heat transfer and thermophysical capabilities. The function of numerous variables, however, makes the experimental technique appear to be costly and time-consuming to carry out. This study was, therefore, designed to numerically simulate the performance assessment of a nanoparticle-enhanced Cascaded Vapor Compression Refrigeration Cycle (CVCRC). The focus of this paper is on four distinct SiO2 nanoparticle nanorefrigerants and their pure fluids: two HFCs as well as two fourth-generation refrigerants (HFOs), namely; R12, R134a, R1234yf, and R-1234ze (E). The results show that adding nanoparticles to the pure refrigerant improves COP, and the highest values were achieved with the R1234ze(E)/SiO2 mixture. Increasing the mass concentration of the nanoparticles leads to an increase in the refrigeration effect, an increase in COP, and a reduction in compressor work. Although R125 had the lowest compressor work of 47.12 kW when SiO2 nanoparticles are introduced, however, is not suitable for refrigeration because of its high GWP values. R1234ze has the second-lowest compressor work of 59.58 kW with the addition of SiO2, it is consequently more energy efficient and can be used in its place as it has a GWP of 6, among other benefits. [ABSTRACT FROM AUTHOR]

Cyprus continues to be one of the European Union's most energy import-dependent countries. It is of worthy note that Cyprus is also the only European Union member state whose electricity grid is not connected to the European power network, as it uses an independent network that relies on local production. The high cost of electricity has been identified as a top problem, and officials on the island are looking at several ways to lower electricity rates. Increasing the amount of renewable energy is one of the main options being looked at. Furthermore, in a bid to meet the European Union target of 40% renewable energy electricity generation, Cyprus needs to fully utilize the vast renewable energy potential in the region. In this study, the integration of dominant renewable energy sources (solar, wind, and concentrated solar power) to the thermal power run grid system is simulated. Also, a 100% renewable energy electricity generation for 2050 is also modelled. The analysis is done, for a projected 8.3TWh/year of electricity demand, in the ENERGYPLAN simulation environment. The deterministic factors considered in this study are the power production and critical excess electricity production. Eight (8) case scenarios were developed in this study for comparative discourse of most feasible electricity generation to cut down on carbon dioxide emission in Cyprus. The optimized analysis reveals that the best case scenario for electricity generation for 2050 is Photovoltaic system integrated with the oil powered plants. This system (Photovoltaic/Oil) would generate 1.68TWh/year of renewable energy electricity. For 100% renewable energy electricity generation, the most feasible option is the Photovoltaic/Wind/storage system. This system would have an installed 4000 MW PV capacity, 7500 MW wind capacity and 30GWh storage capacity. This study gains significance as the results will give valuable technical and economic parameters that can inform policy changes in the region. [ABSTRACT FROM AUTHOR]

It is commonly recommended to incorporate diesel generators into distributed hybrid renewable energy systems (HRESs) to lower the system's total cost and make the generated electricity affordable. Due to the environmental and economic issues associated with fossil fuel use, biomass power technologies (BPT) appear to be an attractive alternative to diesel generators. The HOMER software was used to model, simulate, and optimise two photovoltaic/wind/battery systems integrated with different BPT (anaerobic digestion or gasification) to satisfy the electrical needs of Babadam, a remote community in northern Cameroon. The results indicated that the anaerobic digester integrated system's overall optimal architecture included a 98.1 kW photovoltaic array, a 30 kW biogas generator, and 200 batteries, with a cost of energy (COE) of $0.347/kWh. On the other hand, the gasifier integrated option is made up of an 81.8 kW photovoltaic array, a 15 kW syngas generator, and 200 batteries and has a COE of $0.319/kW. Additionally, compared to the PV/Wind/Battery system, integrating the biogas (resp. syngas) generator showed a potential COE decrease of 29% (resp. 40%). The sensitivity analysis highlighted the validity of this COE reduction potential everywhere in sub‐Saharan Africa, leading to the conclusion that integrating BPT into HRESs can effectively contribute to Sustainable Development Goal 7. [ABSTRACT FROM AUTHOR]

A flat-plate collector is one of the most common solar collector systems due to its comparatively lower cost and maintenance. However, the performance of this type of collector is low; thus, research studies in the past decades have focused on improving its efficiency through various plate configurations and efficient working fluids. This study recognizes the research gap regarding the influence of nanoparticle shapes and their effects on improving the heat transfer properties in flat-plate collectors. In this study, fly ash nanofluid at 0.5% (with a range of nanoparticle sizes) was used as a working fluid to investigate the performance of a flat-plate collector. This study analyzed the behavior of the collector system via a range of Reynolds numbers in its laminar regime, between 800 and 2000. The results measured in this study showed that the maximum energy efficiency measured was 73.8%, which was recorded for the fly ash nanofluid at a nanoparticle size of 11.5 nm. At a Reynolds number of 2000, the fly ash nanofluid with a nanoparticle size of 11.5 nm showed a top heat loss coefficient of 4.78 W/m2K, while the top heat loss coefficient of a nanoparticle size (NPS) of 114 nm was 5.17 W/m2K. This study provides a framework for the significance of the nanoparticle size in the synthesis of nanofluids in both mono and hybrid composites and application in solar collector systems. [ABSTRACT FROM AUTHOR]

Solar energy technologies represent a viable alternative to fossil fuels for meeting increasing global energy demands. However, to increase the production of solar technologies in the global energy mix, the cost of production should be as competitive as other sources. This study focuses on the implementation of machine learning for estimating the thermophysical properties of nanofluids for nanofluid-based solar energy technologies as this would make the synthesis of nanofluids cost-effective. The prediction of thermal conductivity has gained a lot of research attention, whereas, the viscosity of nanofluids has less concentration of studies. The accurate prediction of the viscosity of hybrid nanofluids is important in estimating the heat transfer performance of nanofluids as regards their pump power requirements and convective heat transfer coefficient in several applications. The rigor of experimentations of hybrid nanofluids has necessitated the need for developing efficient and robust machine learning models for accurately estimating the viscosity of hybrid nanofluids for solar applications. Several studies were aimed at developing a predictive model for the viscosity of nanofluids; however, these models are limited to specific types of nanofluids. This study is aimed at developing a robust machine learning algorithm for predicting the viscosity of several hybrid nanofluids from reliable experimental data (700 datasets) culled from literature. This study implements a novel optimizable Gaussian process regression (O-GPR), which have not been previously used in this area, and compares the result with other commonly used machine learning algorithms like, Boosted tree regression (BTR), Artificial neural network (ANN), support vector regression (SVR), to accurately predict the viscosity of a wide range of Newtonian-based hybrid nanofluid. The input parameters used in training the machine learning models were temperature (T), volume fraction (VF), the acentric factor of the base fluid (ACF), nanoparticle size (NS), and nanoparticle density (ND). The prediction performance of the machine learning algorithms was tested using statistical metrics and was compared with theoretical models. The O-GPR model showed superior predictive performance with an R2 of 0.999998 and an MSE of 0.0002552. The study conclusively states that the high accuracy prediction of thermophysical properties of nanofluid using robust machine learning models makes the design of nanofluid-based solar energy technologies more cost-effective. [ABSTRACT FROM AUTHOR]

Ambitious energy efficiency goals constitute an important roadmap towards attaining a low-carbon society. Thus, various building-related stakeholders have introduced regulations targeting the energy efficiency of buildings. However, some countries still lack such policies. This paper is an effort to help bridge this gap for Northern Cyprus, a country devoid of building energy regulations that still experiences electrical energy production and distribution challenges, principally by establishing reference residential buildings which can be the cornerstone for prospective building regulations. Statistical analysis of available building stock data was performed to determine existing residential reference buildings. Five residential reference buildings with distinct configurations that constituted over 75% floor area share of the sampled data emerged, with floor areas varying from 191 to 1006 m2. EnergyPlus models were developed and calibrated for five residential reference buildings against yearly measured electricity consumption. Values of Mean Bias Error (MBE) and Cumulative Variation of Root Mean Squared Error CV(RMSE) between the models' energy consumption and real energy consumption on monthly based analysis varied within the following ranges: (MBE)monthly from –0.12% to 2.01% and CV(RMSE)monthly from 1.35% to 2.96%. Thermal energy required to maintain the models' setpoint temperatures for cooling and heating varied from 6,134 to 11,451 kWh/year. [ABSTRACT FROM AUTHOR]

Hybrid nanofluids have been known to provide perceptibly increased heat transfer characteristics over conventional fluid, and so have been experimentally applied to solar collector applications. Recently, attention has grown towards three-particle hybrid nanocomposites, to investigate their increased thermophysical properties for heat transfer applications. This study numerically investigates the practical application of CuO-MgO-TiO2 ternary nanofluids in a photovoltaic thermal (PV/T) collector. The proposed model explores the effect of volume fraction, solar irradiation, and mass flow rate on the performance of the collector system. The result showed an improved electrical efficiency of 13.54%. 58.38% and 15.68% thermal efficiency and energy efficiency respectively were also gotten, calculated at an optimum volume fraction of 0.01. The maximum cell temperature drop was 8.24 °C measured at a mass flow rate of 0.1 kg s−1. The study also concludes that a maximum increase of 11.14% of the total PV/T system was achieved by the use of ternary nanofluid. The study also investigated the pressure drop and pumping power of the PV/T collector with and without nanofluid. The result showed that a lower pressure drop and pumping power for the CuO–MgO–TiO2 ternary nanofluid which makes it more desirable as compared to the Al2O3–ZnO hybrid nanofluid. Finally, it is shown that the performance of the PV/T collector depends highly on the volume fraction of the ternary nanofluid. [ABSTRACT FROM AUTHOR]

Summary: Solar photovoltaic‐thermal (PV/T) collectors, are hybrid collectors used to convert solar radiation into usable thermal and electrical energy. Recently, the field of research on PV/T is has focused on improving the efficiency of the PV/T collector by replacing the conventional heat transfer fluids (HTFs) with nanofluids. This article investigates the effect of hybrid nanofluids mixture ratio on the useful energy and overall efficiency of a PV/T collector operating with Al2O3‐ZnO water nanofluid as the HTF. Experiments to measure the thermophysical properties of the hybrid nanofluids were conducted for various temperatures, volume concentrations, and mixture ratios, furthermore, accurate correlation models were proposed. Metrological data and energy output readings collected from the PV solar farm at Cyprus International University were used to validate our model. The study observed that at the optimum mixture ratio (0.47 of Al2O3 in the hybrid), the electrical, thermal, and exergy efficiencies of the PV/T collector are 13.8%, 55.9%, and 15.13% respectively. Also, the cell temperature drops by 21% when the mass flow rate is 0.1 kg/s as compared to when it is 0.01 kg/s. Finally, the study concludes that by using the Al2O3‐ZnO hybrid nanofluid an overall peak thermal efficiency of 91% can be attained, and this represents a 34% enhancement in the collector's performance when compared to water. [ABSTRACT FROM AUTHOR]

The main aim of this study is to review researches that have been carried out on solar assisted HVAC systems. The objective is to design a basic solar assisted air conditioning system that uses CO2 as a refrigerant. The performance analysis of the system is done with EES and Copeland Scroll software. Research about the solar-assisted HVAC system has advanced as some studies reveal solar-assisted system that can operate for 24 h. In this kind of system, the storage is important and takes a sizeable amount of space and cost in the design. Also, LiBr is one of the most commonly used efficient absorber in absorption refrigeration for HVAC. The details of all the findings and the performance of the system designed is given in the paper. [ABSTRACT FROM AUTHOR]

In this study, photovoltaic (PV) technology development over the years is reviewed. The use of PV power plants to solve inadequate power supply in Kurdistan is also analysed. PV power application is one of the most developed renewable energy applications but still not commercialized in somw countries. In this paper, three different locations will be evaluated in Kurdistan for PV plant installation. The research will investigate the best location for PV plant installation in Kurdistan, check the viability of the proposed plants and compare the performance of a fixed and a double axis tracking system. A 10 MW PV plant is developed and simulated based on economic terms. The results from the analysis shows that the simple payback period for a 10 MW PV plant in all the locations considered is between 6.8 and 7.2 years. Also, the installation with two-axis tracking system gave the lowest simple payback period (6.8 years). The PV plant is viable considering other economic indicators like; IRR, NPV, annual life cycle savings and BCR. The yearly savings of the system for one of the locations considered is US$1,573,327 with a dual axis tracking system. [ABSTRACT FROM AUTHOR]

Nigeria is one of most populated countries in the world. With a population of about 170 million people, the nation is enriched with diverse renewable and non-renewable energy sources. Despite this huge energy potential, only about 50% of her population have access to electricity. The main objective of this review is to present and analyze the renewable energy potentials of Nigeria with special attention and consideration to the past, present and future of solar energy development. The country aims to achieve electricity production of 9.74%, 18% and 20% of her electricity from renewables by 2015, 2020 and 2030, respectively. Solar energy is expected to produce 1.26%, 6.92% and 15.27% of the electricity consumed by 2015, 2020 and 2030, respectively. If these targets are met, the proportion of the population with access to electricity will increase drastically. Data collected from various reputable energy sources and Journals are reviewed. Nigeria has renewable energy resources including biomass, wind, hydropower and solar energy. These resources can sufficiently meet the country's energy demands, but statistics show that Nigeria still lacks adequate supplies to meet her electricity demands. The policies put in place to meet her energy targets and the current status of the country's supply and demand for electricity are discussed in detail. [ABSTRACT FROM AUTHOR]

The main aim of this article is to examine the feasibility of an energy audit program. LEDs are used to replace the sodium vapor lamps and high-pressured mercury vapor lamps that are currently used for the street lighting system in the Turkish Republic of Northern Cyprus. 44% of the fossil fuels imported into the Turkish Republic of Northern Cyprus is used for electricity generation, which makes the reduction in the consumption of electicity very important. This project will save as much as 36,880,410 kWh on site annually and 111,758,818 kWh from the source. The economic, environmental, and fossil fuels savings of this project are also evaluated. [ABSTRACT FROM AUTHOR]

The amelioration of photovoltaic (PV) and photovoltaic/thermal (PV/T) systems have garnered increased research interest lately, more so due to the discovery of the thermal property augmentation of nanofluids. The overarching goal of this study is to conduct a comparative analysis of mono, hybrid, and ternary hybrid nanofluids utilized as fluids for heat transfer applications and particularly as cooling mediums in PV/T applications. Al2O3, ZnO, Al2O3-ZnO, and Al2O3-ZnO-Fe3O4 nanofluids are synthesized at 1% volume concentration using the two-step method. The zeta potential tests carried out showed that the fluids have high stability. The numerical model developed in this study was validated using real data culled from Cyprus International University. The findings in this study showed that the Al2O3-ZnO-Fe3O4 ternary hybrid nanofluid and ZnO mono nanofluid were more efficient heat transfer fluids for the PV/T system. The optimum relative electrical PV/T efficiency against that of the PV is 8.13% while the electrical and thermal enhancement recorded in this study was 1.79% and 19.06%, respectively, measured for the ternary hybrid nanofluid based PV/T system. This present study shows that despite the limitation of pumping power and pressure drop associated with nanofluid in thermal systems, the close performance evaluation criterion values as compared with water is positive for practical utilization of nanofluid in PV/T systems. [ABSTRACT FROM AUTHOR]

The prediction accuracy of support vector regression (SVR) is highly influenced by a kernel function. However, its performance suffers on large datasets, and this could be attributed to the computational limitations of kernel learning. To tackle this problem, this paper combines SVR with the emerging Harris hawks optimization (HHO) and particle swarm optimization (PSO) algorithms to form two hybrid SVR algorithms, SVR-HHO and SVR-PSO. Both the two proposed algorithms and traditional SVR were applied to load forecasting in four different states of Nigeria. The correlation coefficient (R), coefficient of determination (R2), mean square error (MSE), root mean square error (RMSE), and mean absolute percentage error (MAPE) were used as indicators to evaluate the prediction accuracy of the algorithms. The results reveal that there is an increase in performance for both SVR-HHO and SVR-PSO over traditional SVR. SVR-HHO has the highest R2 values of 0.9951, 0.8963, 0.9951, and 0.9313, the lowest MSE values of 0.0002, 0.0070, 0.0002, and 0.0080, and the lowest MAPE values of 0.1311, 0.1452, 0.0599, and 0.1817, respectively, for Kano, Abuja, Niger, and Lagos State. The results of SVR-HHO also prove more advantageous over SVR-PSO in all the states concerning load forecasting skills. This paper also designed a hybrid renewable energy system (HRES) that consists of solar photovoltaic (PV) panels, wind turbines, and batteries. As inputs, the system used solar radiation, temperature, wind speed, and the predicted load demands by SVR-HHO in all the states. The system was optimized by using the PSO algorithm to obtain the optimal configuration of the HRES that will satisfy all constraints at the minimum cost. [ABSTRACT FROM AUTHOR]

The world has not been able to achieve minimum greenhouse gas emissions in buildings' energy consumptions because the energy and emissions optimization techniques have not been fully utilized. Thermal comfort is one of the most important issues for both residential and commercial buildings. Out of the 40% of global energy consumed by buildings, a large fraction is used to maintain their thermal comfort. In this study, a comprehensive review of the recent advancements in building energy conservation and efficiency application is presented based on existing high-quality research papers. Additionally, the retrofit of the heating/cooling and hot water system for an entire community in Cyprus is presented. This study aims to analyze the technical and environmental benefits of replacing existing electric heaters for hot water with heat pump water heating systems and the use of heat pump air conditioners for thermal comfort in place of the existing ordinary air conditioners for space heating and cooling. One administrative building, 86 apartments (including residential and commercial) buildings, and a restaurant building is retrofitted, and the feasibility of the project is determined based on three economic indicators, namely; simple payback period (SPP), internal rate of return (IRR), and net present value (NPV). The electrical energy required by the hot water systems and the heating/cooling system is reduced by 263,564 kWh/yr and 144,825 kWh/yr, respectively. Additionally, the retrofit project will reduce Cyprus' CO2 emission by 121,592.8 kg yearly. The SPP, IRR, and NPV for the project show that the retrofit is economically feasible. [ABSTRACT FROM AUTHOR]

Hybrid Renewable Energy Systems (HRESs) have been touted as an appropriate way for supplying electricity to remote and off-grid areas in developing countries, especially in sub-Saharan Africa (SSA), where rural electrification challenges are the most pronounced. This study proposes a two-step methodology for optimizing and analyzing a stand-alone photovoltaic/wind/battery/diesel hybrid system to meet the electricity needs of Fanisua, an off-grid and remote village of northern Nigeria. In the first step, the MATLAB environment was used to run simulations and optimize the system via the genetic algorithm. Then, techno-economic and emissions analysis was carried out in the second step to compare the proposed system to the existing traditional modes of rural electrification in sub-Saharan Africa, namely, the grid-extension and diesel generator. The break-even distance parameter was adopted in the comparison with grid-extension. Besides, the hypothetical project of replacing the diesel generator by the optimal system was analyzed using the Simple Payback Period (SPP) and Net Present Value (NPV) parameters. The resulting optimal design architecture included an 89.271-kW photovoltaic array, a 100.31-W diesel generator, and 148 batteries with a total annualized cost (TAC) and cost of energy (COE) of USD 43,807 and USD 0.25/kWh, respectively. The break-even distance found was 16.2 km, while the NPV and SPP of the hypothetical project were USD 572,382 and 2.8 years, respectively. The savings in carbon dioxide (CO2) emissions of the proposed system compared to the grid extension and the diesel generator were found to be 85,401.08 kg/year and 122,062.85 kg/year, respectively. This study highlighted the role that solar PV-based HRESs could play in the sustainable electricity supply in rural areas of sub-Saharan Africa. [ABSTRACT FROM AUTHOR]

In this research, a novel trigeneration powered by a renewable energy (RE) source is developed and analyzed. The trigeneration system is designed to produce electricity, hot water, and cooling using two steam cycles, a gas cycle, hot water chamber, and an absorption cycle. The RE source considered in the scope of this study is biogas generated from chicken manure and maize silage. The energy and exergy analysis of the trigeneration system is performed with the aim to achieve higher efficiencies. The efficiencies are presented based on power generation, cogeneration (electricity and cooling) and trigeneration. The overall trigeneration energy and exergy efficiency for the system developed is 64% and 34.51%. The exergy destruction within the system is greatest in the combustion chamber. [ABSTRACT FROM AUTHOR]

Unit Commitment (UC) requires the optimization of the operation of generation units with varying loads, at every hour, under different technical and environmental constraints. Many solution techniques were developed for the UC problem, and the researchers are still working on improving the efficiency of these techniques. Particle swarm optimization (PSO) is an effective and efficient technique used for solving the UC problems, and it has gotten a considerable amount of attention in recent years. This study provides a state-of-the-art literature review on UC studies utilizing PSO or PSO-variant algorithms, by focusing on research articles published in the last decade. In this study, these algorithms/methods, objectives, constraints are reviewed, with focus on the UC problems that include at least one of the wind and solar technologies, along with thermal unit(s). Although, conventional PSO is one of the most effective techniques used in solving UC problem, other methods were also developed in literature to improve the convergence. In this study, these methods are grouped as extended PSO, modified PSO, and PSO with other techniques. This study shows that PSO with other techniques are utilized more than any other methods. In terms of constraints, it was observed that there are only few studies that considered Transmission Line (TL), Fuel (F), Emission (E), Storage (St) and Crew (Cr) constraints, while Power Balance (PB), Generation limit (GL), Unit minimum Up or Down Time (U/DT), Ramp Up or Ramp Down Time (R-U/DT) and system Spinning Reserve (SR) were the most utilized constraints in UC problems considering wind/solar as a renewable source. In addition, most of the studies are based on a single objective function (cost minimization) and, few of them are multi-objective (cost and emission minimization) based studies. [ABSTRACT FROM AUTHOR]

Due to environmental and economic drawbacks of fossil fuels, global renewable energy (RE) capacity has increased significantly over the last decade. Solar photovoltaic (PV) is one of the fastest-growing RE technologies. Selecting an appropriate site is one of the most critical steps in utility-scale solar PV planning. This paper aims at proposing a rational multi-criteria decision-making (MCDM) approach based on the Brown–Gibson model for optimal site selection for utility-scale solar PV projects. The proposed model considers the project's net present value (NPV) along with seven suitability factors and six critical (constraint) factors. The RETScreen software was applied in calculating the NPV, the simple payback period and the carbon emission savings of the project at each alternative site. The weights of the suitability factors were determined using the analytical hierarchy process. Applied to the case study of finding the best location for a 5 MW solar PV project in northern Cameroon, the optimization results showed that Mokolo was the optimal location. The sensitivity analysis results revealed that the rankings of alternative sites based on the project's NPV and the proposed model are not consistent. Compared to the traditional MCDM approaches, the proposed model provides decision-makers with a more practical thinking method in the optimal location process of utility-scale solar projects. [ABSTRACT FROM AUTHOR]