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This research presents a new method for conditional monitoring based on the wind turbine power curve. The Kolmogorov-Smirnov (K-S) distribution test is employed in the assessment of turbine data and the detection of abnormality (faults) in wind turbines. The process begins with anomaly detection and filtration of faulty SCADA data by a quantile-based filtration approach. Suitable data comprising wind speed, air density, ambient temperature, and pitch angle are utilized in the development of wind turbine power curve models that represents actualities within wind farms. The radial basis function (RBF), multi-layer Perceptron (MLP), and gradient boosting (GBR) methods utilized for model development are compared for predictive accuracy using Mariano-Preve test. The null hypothesis assumes equal predictive ability (EPA); if rejected, an algorithm compares the coefficients of correlation of the models and selects the closest to one (unity). The most accurate model is utilized for the creation of a bin-wise distribution from past data, and bin-wise confidence levels from the plot of wind speed and output power. Cochran’s method was utilized to validate the minimum sample size that will possess a sampling distribution similar to that of the population, and a fault is detected if there is a reasonable difference between the sample distribution and population distribution. The K-S test, having a null hypothesis of equivalent distributions, signals a fault if the null hypothesis is rejected. Two wind turbine SCADA datasets associated with two fault events are used for the assessment of our method. The results indicate that our method effectively discovers abnormalities in power output relating to increased bearing temperature and reduced generator rpm, thereby aiding in the detection of faults long before they occur.

This work presents an adaptive neuro-fuzzy inference system (ANFIS) artificial intelligence methodology of predicting the 2nd law efficiency and total irreversibility of a refrigeration system running on LPG/TiO2–nano-refrigerants. For this purpose, substractive clustering and grid partition approaches were utilized to train the ANFIS models required in estimating the 2nd law efficiency and total irreversibility using some experimental data. Furthermore, predictions of ANFIS models with subtractive clustering approach was found to be more accurate than ANFIS models predictions with grid partition approach. The predictions of ANFIS models with subtractive clustering approach were also compared with experimental results that were not included in the model training and predictions of already existing ANN models of authors previous publication. The comparison of variance, root mean square error (RMSE), mean absolute percentage error (MAPE) were 0.996–0.999, 0.0296–0.1726 W and 0.108–0.176 % marginal variability values. These results indicate that the ANFIS model with subtractive clustering approach having cluster radii 0.7 and 0.5 can predict the 2nd law efficiency and total irreversibility respectively, with higher accuracy than authors’ previous publication ANN models.

One of the important optimization applications (minimization and maximization) is the power grid systems. National electricity grids should be interconnected to develop larger regional grids (supergrids), and further integrated to build up a worldwide grid (global grid) for minimizing consumption of natural resources and maximizing economical useful life, recycling rate, and effective usage of natural resources. These supergrids and global grid concepts can only be developed through detailed and organized supportive research studies. This research study aims to find, define, identify, describe and select location selection factors of very large photovoltaic solar power plant investments on a global grid and supergrid concepts. Grey systems theory, fuzzy (Type-1 and 2) theories, Mamdani’s type fuzzy rule-based system, Interpretive Structural Modelling (ISM), Impact Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) tool, and Political, Economic, Social and Technological (PEST) framework and its extensions (SLEPT, PESTEL, PESTLE, STEEPLE, STEEPLED, DESTEP, STEER) are concurrently used in this study. Eleven (11) criteria are presented for preliminary screening (i.e. C1: global horizontal irradiation (GHI), C2: governments supergrid integration policy, C3: supergrid business climate and conditions, C4: High Voltage Direct Current (HVDC) and High Voltage Alternating Current (HVAC) electrification grid infrastructure, C5: land use, allocation and availability, C6: geological conditions, C7: political, war, terror & security, C8: topographical conditions, C9: climatic conditions, C10: water availability conditions, C11: natural disaster/hazard conditions), and 191 factors are presented for pre-feasibility investment stages. Findings can directly be used or taken as a basis for further analysis by researchers and practitioners.

Relevant meteorological files are needed by simulation software to assess the energy performances of buildings or efficiency of renewable energy systems. This paper adopts the Sandia method to generate typical meteorological year (TMY), using a 35-year hourly measured meteorological dataset from four stations in the northern region of Nigeria. The cumulative distribution function (CDF) for each year was compared with that of the long-term composite of all the years in the period for the seven major weather indices made up of relative humidity, wind speed, minimum temperature, global solar radiation, precipitation, mean temperature and maximum temperature. The 12 typical meteorological months (TMMs) selected from the different years were used for formulation of a TMY for the zone. In addition, performance assessment of a 72-cell polycrystalline solar PV module using the generated TMY and long-term (LT) values was also conducted. Two statistical indicators, the mean percentage error and the root mean square error, were adopted to evaluate the performance of each TMY with the LT mean, and also that of the PV energy system. Findings show that the TMMs are evenly spread within the data periods across the sites while closest fit between the long-term mean and TMY are obtained with the global solar radiation followed by the mean temperature in all the sites especially in Bida and Minna. From the energy system analysis carried out, it was found that TMY data are able to predict the performance of the PV system to within 5% of the LT data.

This work studies the location selection of very large concentrated solar power plants (VLCSPPs) in Nigeria using five Multi-Criteria Decision Making (MCDM) methodologies including: Analytic Hierarchy Process (AHP), Consistency-Driven Pairwise Comparisons (CDPC), Decision Expert for Education (DEXi), Elimination and Choice Translating Reality (ELECTRE) III and IV. A comparative investigation is performed on only one unique model that is structured in four levels. This model has nine basic factors (Direct Normal Irradiance, grid infrastructure, climatic conditions, water availability conditions, natural disaster/hazard conditions, topographical conditions, geological conditions, land use, allocation and availability, war, terror & security conditions) taken from previous factors selection studies. There are 35 alternatives for the VLCSPP locations in Nigeria for the pre-development investment stage and are presented on Google Earth file (GE). The Super Decisions, JConcluder, DEXi and ELECTRE III-IV software are mainly used in this study. The findings show that the AHP and CDPC rankings are very close to each other. On the other hand, the DEXi, ELECTRE III and IV rankings spread very much amongst the methods. Hence, a small procedural rule is defined for the selection of candidate locations for detailed investigations. Several candidates’ VLCSPP locations were found to exist as alternatives, with approximate local central coordinates of 13°38′55.37″N, 13°20′41.41″E and 13°6′58.83″N, 13°26′53.63″E in Nigeria. These should be further investigated in the following investment stages.

The study presents the wind energy potential (WEP) for six locations in Cross River State, Nigeria. The objective of the study was to assess the WEP of the selected sites for electricity generation, using small size wind energy conversion systems (WECs). The wind data were measured at 10 m height and ranged from 4 to 10 years. Additionally, the data were evaluated using the two-parameter Weibull function. Results obtained show that annual mean wind speed, vm, and Weibull parameters kand crange from 3.21 to 4.55 m/s, 3.32 to 6.69 and 2.99 to 5.40 m/s, in that order. The cost per kWh of energy for the selected WECs fluctuated between 0.0626 ≤ COE ≤ 0.1375 USD/kWh, while the avoidable CO2emissions exist between 0.64 and 38.21 tons/year. However, the probable savings made from diesel was not greater than 14,524.94 litres/year for the locations with high WEP for small-scale stand-alone applications.

The objective of this study is to determine the effects of global warming and future afforestation on wind power potential in Nigeria. A series of multi-year simulations of a regional climate model (ICTP-RegCM3) for 1981–2000 (baseline) and 2031–2050 (future with elevated CO2under A1B emission scenario) periods, generated from a previous experimental study on the impacts of afforestation on the region’s climate, were used. In the study, land-use patterns produced from seven different hypothetical afforestation scenarios were then used as boundary conditions in RegCM3 to simulate various future climate scenarios. Four of these options assumed random (i.e. 100, 75, 50 and 25%) afforestation over the country, while the other three assumed zonal (i.e. North (RNZ), Middle-belt (RMZ), and South (RSZ)) afforestation. Wind power density varied with season across the country. The north-eastern regions had the highest potential for wind power harvesting with the peaks (120W/m2at 10m; 260W/m2at 100m hub heights) during the dry season. A rise (+10 to +30%) in wind power over most parts of the country during the wet season (May to July) and a decrease (−10 to −25%) in dry season (October to January) were projected. Random afforestation generally suggested negative significant impacts (25–100%) on future wind power over the country. However, zonal afforestation had positive (≤ +20%) impacts upwind the afforested zone but negative (≈ −100%) over the afforested zone. Future RSZ afforestation option was found to enhance the wind power harvesting potential of the north-eastern regions of Nigeria.

ABSTRACTThe wind characteristics of six locations in Niger Delta, Nigeria, and the economics of the application of wind energy for water pumping and possible avoidable CO2emissions through wind utilisation were examined. The wind data were measured at 10 m height and analysed using the two-parameter Weibull model. Small size wind turbines were accessed with Goulds 45J03 water pump series. The average power density, average energy density and annual energy across locations ranged between  W/m2,  kWh/m2and  kWh/m2/year, respectively. Bergey Excel-10 kW turbine had the lowest cost of energy and water pumping cost of $/kWh and $/m3, respectively. The annual capacity of water yield varies from 21,847 to 120,206 m3/year on a total dynamic head of 50 m. Furthermore, the annual diesel saved across the locations ranged from 1605 to 8696 l/year (17.47 to 94.67 GJ/year), while the annual averaged CO2saved was between 4.32 and 22.93 tons/year.

The potentials of major renewable energy sources (wind and solar) in selected locations across the six geo-political regions of Nigeria, based on long-term daily meteorological data spanning between 18 and 39years were reviewed in this study. In addition, the techno-economic feasibility of utilizing hybrid photovoltaic/wind/diesel with battery storage systems to meet the load of a typical rural healthcare facility at the selected sites were assessed. The optimum dimensions of the system are defined for the locations. Hybrid Optimization Model for Electric Renewable (HOMER) software developed by National Renewable Energy Laboratory’s (NREL) was employed to conduct the study. Findings from the study showed that Sokoto and Jos exist in the high wind potential regions, while the remain sites are only suitable for small wind applications. Values obtained for global, beam and diffuse radiation as well as clearness index, show that all the sites enjoy considerable solar energy potential suitable for varying degree of solar energy applications. Monthly optimum tilt angle for Iseyin, Sokoto, Maiduguri, Jos, Enugu and Port-Harcourt lies in the range of 0–39.8°, 0–44.5°, 0–44.1°, 0–43.2°, 0–38.5° and 0–36.3° respectively thereby having the optimum angle to be equal to 0° in all sites in April, May, June, July and August. The simulation results from HOMER indicate that the hybrid system is the best option for all the sites considered in this study. The PV/wind/diesel/battery hybrid system configuration is considered optimum for RHC applications at Sokoto, Maiduguri, Jos and Enugu, while hybrid systems involving PV/diesel/battery is considered ideal for RHC at remote locations within Iseyin and Port-Harcourt, due to the quality of renewable energy potential. The diesel-only system provides the highest COE ($0.911/kWh), and emits 9211kg of CO2per year in all the site considered.

Nigeria is rich in both conventional and renewable energy resources that empower the country with a large capacity to develop an effective national energy policy. The study aims at reviewing the current energy resource structure of Nigeria in terms of production and utilization, comparing sectoral performance and reviewing issues confronting energy growth, sustainability, policies and frameworks towards the actualization of energy efficiency. The total energy consumption in 2011 was 28.8 million tons of oil equivalent about 5.4 % of the world value in 2010. Nigeria share of world CO2emissions in 2011 was 0.32 % and a drop of 0.02 % in 2010. In addressing the country’s challenges of energy demand, production, consumption and related environmental problems, the government has initiated sustainable and effective energy conservation strategies to improve efficiency. These include: reduction of energy consumption at the household sector, reduction of gas flaring, adoption and maximum renewable energy technologies, reduction of energy intensity in industries by appropriate energy conservation and management system. In addition, the policies also include the development and integration of alternative energy resources such as nuclear, biomass, wind and solar into the total energy mix structure. For all these to be accomplished, the energy development strategy must follow a sustainable framework to balance economic growth, social expansion and eco-friendly protection.

Technical electricity generation assessment and economic analysis of six wind energy conversion systems in the categories small, medium, and large (with power ratings of 20, 35, 275, 500, 1,000, and 2,000 kW) were examined in this study. Electricity cost values were estimated based on the levelized cost of electricity (LCOE) and present value cost (PVC) methods for six locations selected across all the geopolitical zones of Nigeria. This was done using wind speed data that span between 25 and 37 years, measured at the height of 10 m. The result showed that the annual average energy output ranges from 2.242 MW h in Uyo with P10-20 turbine to 12,521.55 MW h in Kano using Vestas V80-2 MW wind turbine. Furthermore, of all the selected sites, Kano gave the least costs of electricity production per kilowatt hour with Vestas V80-2 MW model at 67-m hub heights, while the highest is obtained in Uyo with GEV-HP (1 MW) model at 70-m hub heights for the LCOE and PVC height for both the LCOE and PVC methods. In addition, sensitivity of the selected parameters to the levelized cost of electricity was also carried out.

In this study, an analysis of the wind energy potential in the southwest geo-political region of Nigeria was conducted. A 37-year (1971–2007) wind speed data set measured at 10 m height, obtained from eight meteorological stations within the region was analyzed using a 2-parameter Weibull function. Besides, a technoeconomic evaluation of large wind energy conversion systems with power ratings ranging from 0.6 to 2MW at different hub heights based on the levelized unit cost of electricity was made for the different sites considered. The result showed that electricity cost varied from 0.06997 and 0.11195 $/(kW·h) to 2.86611 and 4.58578 $/(kW·h) at limit values of turbine specific cost band intervals of 1000 and 1600 $/kW. It was further shown that Lagos, having the highest accumulated power outputs of 430.10 kW/a from DeWind D7 at 70m hub height, is the most preferred for economically usable power generation in terms of the levelized unit cost.

The study presents a power-cooling organic Rankine cycle with an ejector system (ORCPCES). The objective is to determine the thermodynamic, economic and sustainability of the ORCPCES from the manufacturing, commissioning and decommissioning phases. Component-wise modelling was first performed based on the exergy concept. The system simulation was carried out using a developed source code in Engineering Equation Solver (EES). The refrigerant leakages and the material component impact on the environment were evaluated at all phases of the plant life cycle. The results indicate that the evaporator cooling rate (ECR) and the power-cooling efficiency (PCE) varied from 120.8 to 153 kW and 28.87 to 34.43 % across the refrigerants with the highest PCE and exergy efficiency obtained using R1234ze. The maximum power output was obtained using R1234ze. The overall environmental impact due to the components occurred at5.1×105mPts, 5.24×105mPtsand 5.4×105mPtsfor R245fa, R1234yf, and R1234ze, respectively, while 4.01×105mPts7.81×104mPtsand9.33×105mPtswas due to the working fluids in that order. The unit cost of electricity (UCOE) across the refrigerants varies from 0.181$/kWh to 0.2291$/kWh with the least UCOE, 0.181$/kWh obtained using R1234ze. The highest exergetic sustainability index of 0.56 was achieved using R1234ze.