Cost implication of Line Voltage variation on Three Phase Induction Motor operation

Adekitan, Aderibigbe Israel; Adetokun, Bukola Babatunde; Shomefun, Tobi; Aligbe, Alex

doi:10.12928/telkomnika.v16i4.9628

Cited by 9 publications

(8 citation statements)

References 17 publications

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“…NERC has mandated all DISCOs to install prepaid meters for all their customers but this is yet to be fully complied with, as DISCOs complain of lack of funds to procure the needed prepaid meters [5] . The data captures the proportion of the sampled residents that are on prepaid meters, it also reflects the opinion of the customers of their current monthly energy charges, it reflects the average hours of power supply by the DISCO to the residents due to insufficient power generation and load shedding [6] , [7] , [8] , [9] , [10] , and also, it presents the profile of the commonly used electrical equipment, used within the community. According to [11] , [12] the type of electrical equipment used and the behavioral energy usage trend determines a customer׳s monthly electricity bill.…”

Section: Datamentioning

confidence: 99%

Data based investigation of the energy metering type, billing and usage of sampled residents of Ota Community in Nigeria

et al. 2018

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Accurate energy metering and billing is a challenge in some developing countries. In Nigeria, the issues of inadequate power generation, transmission and distribution infrastructure are recurrent problems, coupled with inefficient energy metering which is a major problem that results in residential energy consumers being billed unfair energy charges by the Electricity Distribution Companies (DISCOs) for unused energy, and this has been termed “crazy bill”. For the energy sector to be effective, energy bills should be based on the actual energy usage and likewise customers must pay for used energy. To achieve this, the Nigerian Electricity Regulatory Commission (NERC) recommended the installation of prepaid meters for all customers, but as at today, there is no full compliance with this regulation. Power supply is grossly unreliable, and this has affected power quality due to frequent load shedding and power outages. The dataset presented in this article captures the type of apartment, the type of electrical appliances used by occupant, the average monthly energy bill paid for electricity, the use or non-use of alternative energy sources, the type of alternative energy sources used, and the type of energy meter used by sampled residents of the Ota community in Ogun State, Nigeria. The dataset was acquired using an investigative questionnaire to survey the residential consumers within the sampled space.

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Section: Datamentioning

confidence: 99%

Data based investigation of the energy metering type, billing and usage of sampled residents of Ota Community in Nigeria

et al. 2018

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“…As at now, a more significant percentage of electricity is yet being generated using fossil fuels in Nigeria (Edomah, 2016). At present, the Nigeria electricity generation floats around 12.5GW This Journal is licensed under a Creative Commons Attribution 4.0 International License for all sources (thermal and hydro) with only 3.5GW to 5.0GW is typically available for onward transmission to the final consumer (Adekitan et al, 2018;Adesanya and Pearce, 2019;. This present generating capacity is highly inadequate for a country that has a population of over 200 million (World meter, 2020).…”

Section: Introductionmentioning

confidence: 99%

Techno-Economic Assessment of Wind Turbines in Nigeria

Okakwu¹,

Olabode²,

Alayande

et al. 2021

IJEEP

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Wind energy potentials of some selected high altitude and coastal areas in Nigeria are assessed for possible utilization for the generation of electricity. The main aim is to provide pragmatic insight that will enhance the investment in wind energy conversion systems in an optimal manner. The data used in this present study were obtained from the Nigeria Meteorological Agency, which includes average wind speeds per day of four locations across the country, measured at the anemometer height of 10 m over a period of 11 years. With the sites classified based on their wind power densities, the capacity factor estimation value was used to select the most suitable turbine for the selected sites, and the present value cost method was employed to estimate the unit cost of energy of the turbine at various hub-heights. The results obtained from this study reveal that Jos, Kano and Ikeja are economically viable as well as having excellent wind resources integration into the grid, while P/H is viable for a standalone application. The outcome of the study provides useful information that will aid renewable energy policymakers in Nigeria for wind energy development.

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“…Voltage unbalance stimulates increased motor losses which results in increased heat generation that may lead to early motor failure [7], [8]. Voltage unbalance reduces motor efficiency thereby increasing energy cost for the user [9], and by implication, the reduced efficiency increases the system load on the power plant which unnecessarily depletes the energy reserve of the power plant [10]. Voltage unbalance creates a magnetic flux that opposes the main flux, and this causes power and torque oscillation at twice the frequency of the supply.…”

Section: Introductionmentioning

confidence: 99%

Determining the operational status of a three phase induction motor using a predictive data mining model

Adekitan

Adewale

Alashiri

2019

IJPEDS

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<span lang="EN-GB">The operational performance of a three phase induction motor is impaired by unbalanced voltage supply due to the generation of negative sequence currents, and negative sequence torque which increase motor losses and also trigger torque pulsations. In this study, data mining approach was applied in developing a predictive model using the historical, simulated operational data of a motor for classifying sample motor data under the appropriate type of voltage supply i.e. balanced (BV) and unbalance voltage supply (UB = 1% to 5%). A dataset containing the values of a three phase induction motor’s performance parameter values was analysed using KNIME (Konstanz Information Miner) analytics platform. Three predictive models; the Naïve Bayes, Decision Tree and the Probabilistic Neural Network (PNN) Predictors were deployed for comparative analysis. The dataset was divided into two; 70% for model training and learning, and 30% for performance evaluation. The three predictors had accuracies of 98.649%, 100% and 98.649% respectively, and this confirms the suitability of data mining methods for predictive evaluation of a three phase induction motor’s performance using machine learning</span>

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Cost implication of Line Voltage variation on Three Phase Induction Motor operation

Cited by 9 publications

References 17 publications

Data based investigation of the energy metering type, billing and usage of sampled residents of Ota Community in Nigeria

Data based investigation of the energy metering type, billing and usage of sampled residents of Ota Community in Nigeria

Techno-Economic Assessment of Wind Turbines in Nigeria

Determining the operational status of a three phase induction motor using a predictive data mining model

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