Electric Pump Research Articles

Pseudo-optimal discharge pressure analysis of different CO2 electric vehicle heat pumps based on cabin thermal model

The discharge pressure of electric vehicle heat pumps, aiming for peak COP values, is termed the pseudo-optimal discharge pressure for dynamic regulation, distinguishing it from the optimal discharge pressure at a constant compressor speed. A theoretical model was presented to analyze the impacts of operational parameters considering the variation of cabin loads with operating conditions. Based on simulation results, the effects of ambient temperature, cabin temperature, drive speed, and supply air flow rate on the pseudo-optimal discharge pressure were investigated for single-stage and two-stage compression systems, respectively. Among them, the ambient temperature had the highest degree of influence, more than 45 % in different systems. Heat recovery in electrical systems introduced slight variations, less than 1 bar, to the pseudo-optimal discharge pressure by affecting the evaporation temperature. While the trend remains consistent across the different systems, the values of pseudo-optimal discharge pressure are higher for the two-stage compression. At −10/20 °C, two-stage compression provides a 49.42 % higher COP compared to single-stage while maintaining a safe discharge temperature. In addition, the heating efficiency under the improved prediction can be increased by 18.49 % compared to the existing research. Predictions for the pseudo-optimal discharge pressure provide a basis for effective and cleaner control of electric vehicle heat pumps.

Analysis of two-phase gas-liquid flow in an Electric Submersible Pump using A CFD approach

This study comprehensively analyzes a mixed-flow Electric Submersible Pump's (ESP) performance under challenging conditions of low flow rates and high gas fractions. The research leverages a computational model built on the Eulerian-Eulerian methodology, adeptly solving the 3D incompressible Navier-Stokes equations for each phase. To ensure an encompassing depiction of the flow dynamics within the ESP, the model considers critical parameters such as the bubble diameter and interphase forces, including drag, lift, and virtual mass force.Key findings reveal that the ESP's performance deteriorates markedly under the studied conditions. One of the primary influencers is the phenomenon of gas locking, where gas accumulation within the impeller hampers the consistent flow of liquid, thereby degrading the pump's efficiency. In addition, the model delineated the occurrence of the surging phenomenon across diverse gas volume fractions and rotational speeds, which further exacerbates the reduction in the ESP's performance. Intriguingly, the bubble diameter was identified as a decisive factor, especially at minuscule flow rates. Large bubble diameters instigate the formation of gas pockets on the suction side of the vane, culminating in a segregated flow pattern and further declining pump efficiency.On the other hand, the drag force is the primary interaction force between phases of gas-liquid flow. Other interfacial forces, such as lift and virtual mass force, change the pump's performance but do not affect the gas flow and distribution patterns for a one-stage configuration. Results show that the Schiller-Neuman drag coefficient offers a better fit than the Bozano-Dente coefficient.Conclusively, the study underscores the indispensable role of nuanced computational models in elucidating the intricate flow dynamics within ESPs, especially under conditions fraught with operational challenges. The insights gleaned enrich our understanding of ESP performance dynamics and provide a roadmap for designing more resilient and efficient pumping systems in the future.

Research on early warning model of electric submersible pump wells failure based on the fusion of physical constraints and data-driven approach

At present, there are too few characteristic parameters for early identification of electric submersible pump (ESP) wells failures. In addition, existing predictive models rely only on data-driven techniques, which do not provide a comprehensive understanding of the intrinsic mechanisms behind the occurrence of failures. This article presents the development of a health index calculation approach for evaluating the operational status of the ESP wells. The wellbore energy conservation equation and the health index calculation formula were employed to develop a physical constraints (PC) for the loss function in the network model of Long Short-Term Memory (LSTM). This constraint was then utilized to construct the PC-LSTM ESP health warning model. The study examines the health index trends associated with three types of faults: ESP clogging, sand production in oil wells, and reservoir pressure rise. The results indicate that the PC-LSTM network structure exhibits faster convergence during training. In relation to the accuracy of prediction, PC-LSTM demonstrates a notable enhancement. Specifically, when the ESP clogging fault, the traditional LSTM achieves a mean relative error (MRE) of 211.15%, whereas the PC-LSTM achieves a reduced MRE of 12.74%. Similarly, for sand production in oil wells, the traditional LSTM yields an MRE of 19.07%, while the PC-LSTM achieves a reduced MRE of 9.62%. Lastly, in the scenario of reservoir pressure rise, the traditional LSTM exhibits an MRE of 41.07%, whereas the PC-LSTM achieves a reduced MRE of 12.74%. In the meantime, the model demonstrates a high level of accuracy in capturing the pre- and post-trends of the health status of the ESP wells. This improved prediction accuracy and interpretability of the underlying mechanisms serve as valuable tools for analyzing the lift performance of ESP wells and providing early warning signals for potential failures.

Predictive Maintenance System for Rotating Machinery Onboard Ships for Detecting Performance Degradation

Maintenance of rotating machinery is crucial for extending the lifespan and increasing the reliability of equipment onboard ships. Presently, breakdown and preventive methodologies are used for the maintenance of equipment. Further, dataloggers collect critical machinery parameters, and parameter data is used for real-time parameter monitoring. The availability of such extensive monitoring data has also led to the adoption predictive maintenance methodologies in the industry, wherein machine learning-based analysis of recorded data is used to predict impending defects and prompt required maintenance. In this paper, we propose a predictive maintenance system that records data through a network of sensors installed over multiple electrical motor pump sets onboard the ship and uses statistical analysis to detect equipment degradation. Our system has been deployed onboard a ship to undertake real-time predictive maintenance of electrical motor pump sets used in firemain, AC plants, stabilizers, steering pumps and other auxiliary engine room machinery.

Data-based, high spatiotemporal resolution heat pump demand for power system planning

Decarbonizing the residential building sector by replacing gas boilers with electric heat pumps will dramatically increase electricity demand. Existing models of future heat pump demand either use daily heating demand profiles that do not capture heat pump use or do not represent sub-national heating demand variation. This work presents a novel method to generate high spatiotemporal resolution residential heat pump demand profiles based on heat pump field trial data. These spatially varied demand profiles are integrated into a generation, storage, and transmission expansion planning model to assess the impact of spatiotemporal variations in heat pump demand. This method is demonstrated and validated using the British power system in the United Kingdom (UK), and the results are compared with those obtained using spatially uniform demand profiles. The results show that while spatially uniform heating demand can be used to estimate peak and total annual heating demand and grid-wide systems cost, high spatiotemporal resolution heating demand data is crucial for spatial power system planning. Using spatially uniform heating demand profiles leads to 15.1 GW of misplaced generation and storage capacity for a 90% carbon emission reduction from 2019. For a 99% reduction in carbon emissions, the misallocated capacity increases to 16.9-23.9 GW. Meeting spatially varied heating load with the system planned for uniform national heating demand leads to 5% higher operational costs for a 90% carbon emission reduction. These results suggest that high spatiotemporal resolution heating demand data is especially important for planning bulk power systems with high shares of renewable generation.

Pseudo electric field and pumping valley current in graphene nanobubbles

Pseudo electric field and pumping valley current in graphene nanobubbles

Optically Reconfigurable THz Metamaterial with Switchable Wideband Absorption and Transmission

We present an optically reconfigurable multifunctional metamaterial with switchable wideband absorption and transmission across the THz frequency range. The reconfigurability is achieved by introducing optically active silicon into the resonator of the metamaterial unit which could be effectively modulated through external electrical pumping. When the silicon conductivity reaches 50,000 S/m, the metamaterial shows significant absorption of electromagnetic waves ranging from 3.1 to 10 THz. By reducing the applied external pump power and decreasing the silicon conductivity to 150 S/m, the proposed metamaterial exhibits transmission of the incident waves at 5.12 THz with a transmission coefficient of 61%. The proposed optically reconfigurable metamaterial has the advantages of simple structure, wideband absorption, and switchable between absorption and transmission modes, showing potential applications in stealth, communication, or radar systems.

Mothers' Willingness to Use Workplace Lactation Supports: Evidence from Formally Employed Mothers in Central Kenya

BackgroundFormally employed mothers are vulnerable to early cessation of exclusive breastfeeding. Kenyan national policy requires employer-provided maternity benefits and workplace lactation supports. ObjectiveThe objective of this study was to evaluate willingness to use nationally mandated workplace lactation supports among formally employed women in Kenya. MethodsWe conducted a cross-sectional survey among 304 mothers of children ages ≤12 mo in Naivasha, Kenya, who were currently formally employed and employed before delivery of the most recent child to assess availability of and willingness to use current and potential future workplace lactation supports. ResultsThe most available reported workplace lactation supports were schedule flexibility to arrive late or leave early (87.8%) or visit a child to nurse during lunch (24.7%), followed by company-funded community-based daycare (7.6%). Few (<4.0%) reported the availability of lactation rooms, on-site daycares, transportation to breastfeed during lunch, refrigerators for expressed milk, or manual or electric breastmilk pumps. If made available, >80% of mothers reported moderate or strong willingness to use flexible schedules to arrive late or leave early, break during lunch, and transportation to visit a child to nurse. A moderate proportion reported strong willingness to use on-site daycares (63.8%), company-funded community-based daycare (56.9%), on-site lactation rooms (60.5%), refrigeration for expressed milk (49.3%), manual (40.5%), and electric pumps (27.6%). Mothers expressed fear of missing production targets and reported more willingness to use on-site compared with off-site daycare to save transportation time but noted concerns about chemical exposures and early arrival times with young infants. Hesitations regarding the use of on-site lactation rooms included concerns about privacy, milk identification and storage, and use and sharing of pumps. ConclusionsFlexible schedules were the workplace lactation supports in highest demand among formally employed mothers. Maternal willingness to use lactation rooms, refrigeration, and pumping equipment was moderate to low, suggesting sensitization may help to increase demand as the implementation of Kenyan policies moves forward.

Achievable load shifting potentials for the European residential sector from 2022–2050

This paper develops quantitative predictions for residential electricity demand and the potential for load shifting for Europe at a fine spatial scale for years 2022–2050. To date only theoretical and spatially coarse measurements of this potential exist for a subset of technologies used in the residential sector. As the EU moves towards an ‘Energy Union’, it will be increasingly necessary to consider the whole integrated energy system across the EU and thereby databases with large spatial coverage are needed. To fill this need, we generate hourly load profiles for the residential sector for key electricity consuming devices that take into account the most recent empirical studies of usage patterns, and of the cost and willingness of households to participate in load shifting programs. Additionally, we extend the list of investigated technologies by the important classes of electric mobility and heat pumps for electric space heating. Predictions and insights provided in our article serve multiple use cases, i. they can be used in energy system models to assess the value of load shifting for the future energy system including system costs, ii. they enable infrastructure planners and grid operators to calibrate their expectations of the future role of load shifting in the electricity systems and iii. enable policy makers and to include load shifting in their considerations of future market designs.

IMPROVEMENT OF MOTHER'S BREAST MILK PRODUCTION THROUGH PAPAYA FRUIT DESSERT

Breast milk (ASI) is the primary source of nutrition for infants as it can fulfill all their needs. However, the current rate of exclusive breastfeeding is still low. In Kutai Kartanegara Regency, the coverage of exclusive breastfeeding is only 47.5%. One of the reasons is insufficient breast milk production. Various efforts have been made to enhance breast milk production, such as providing papaya fruit dessert, as it contains lactagogue compounds that have the potential to stimulate hormones like oxytocin and prolactin. Compounds such as alkaloids, polyphenols, steroids, flavonoids, and other substances are believed to be most effective in increasing and facilitating breast milk production. To analyze the influence of papaya fruit dessert consumption on the enhancement of breast milk production among postpartum mothers in the working area of Sungai Merdeka Community Health Center in 2023. This study employs a quasi-experimental design with a "Pretest-Posttest, Control Group Design." The population includes all postpartum mothers who have given birth normally in the working area of Sungai Merdeka Community Health Center, with an average of 30 deliveries per month. The sample size was determined using the minimal sample size formula by Lemeshow, resulting in 26 participants. The measurement tools consist of observation sheets and a real bubee electric breast pump. Data analysis involves an independent t-test. There is an influence of papaya fruit dessert consumption on the enhancement of breast milk production among postpartum mothers in the working area of Sungai Merdeka Community Health Center, with a p-value of 0.000. The breast milk production in the group provided with papaya fruit dessert was significantly higher, with a difference of 39,231 ml compared to the group without papaya fruit dessert. The presence of compounds like alkaloids, polyphenols, steroids, and flavonoids in papaya fruit can enhance breast milk production.

Inter-stage performance and energy characteristics analysis of electric submersible pump based on entropy production theory

The electric submersible pump (ESP) is a crucial apparatus utilized for lifting in the oil extraction process. Its lifting capacity is enhanced by the multi-stage tandem structure, but variations in energy characteristics and internal flow across stages are also introduced. In this study, the inter-stage variability of energy characteristics in ESP hydraulic systems is investigated through entropy production (EP) analysis, which incorporates numerical simulations and experimental validation. The EP theory facilitates the quantification of energy loss in each computational subdomain at all ESP stages, establishing a correlation between microscopic flow structure and energy dissipation within the system. Furthermore, the underlying causes of inter-stage variability in ESP hydraulic systems are examined, and the advantages and disadvantages of applying the EP theory in this context are evaluated. Consistent energy characteristics within the ESP, aligned with the distribution of internal flow structure, are provided by the EP theory, as demonstrated by our results. The EP theory also enables the quantitative analysis of internal flow losses and complements existing performance analysis methods to map the internal flow structure to hydraulic losses. Nonetheless, an inconsistency between the energy characterization based on EP theory and the traditional efficiency index when reflecting inter-stage differences is identified. This inconsistency arises from the exclusive focus of the EP theory on flow losses within the flow field, disregarding the quantification of external energy input to the flow field. This study provides a reference for the optimization of EP theory in rotating machinery while deeply investigating the energy dissipation characteristics of multistage hydraulic system, which has certain theoretical and practical significance.

Research on fault diagnosis of electric submersible pump based on improved convolutional neural network with Bayesian optimization

A conventional intelligent fault diagnosis approach for electric submersible pumps (ESPs) is heavily dependent on manual expertise for feature extraction. Meanwhile, a conventional convolutional neural network (CNN) exhibits an excess of parameters and requires a substantial volume of training samples. In this paper, a fault diagnosis algorithm of ESPs based on a Bayesian optimization-one-dimensional convolutional neural network-support vector machine (BO-1DCNN-SVM) is proposed by combining a 1DCNN with a SVM and using the algorithm BO to tune the improved 1DCNN. First, the method uses the self-extracting feature capability of the 1DCNN to solve the problem that traditional diagnosis methods over-rely on manual experience extraction. Meanwhile, the last layer of the convolutional neural network Softmax layer is replaced by the SVM to effectively process a few sample data. The accuracy and generalization ability of the fault classification of the electric submersible pump are improved. Then, the Bayesian optimization algorithm is used to find the optimal combination of hyperparameters for the improved 1DCNN-SVM model to further improve the prediction performance of the fault diagnosis model. Finally, the experimental results achieved a classification accuracy of 96.64%, which is 5% higher than existing CNN approaches with data samples of similar scale in this paper. The proposed method also proved to be highly accurate and robust in fault diagnosis.

Risk-aware day-ahead planning of a zero energy hub integrated with green power-to-hydrogen technology using information gap decision theory and stochastic approach and considering demand side elasticity

Environmental issues and rapid load growth have led to increasing renewable resources infiltration toward achieving zero energy infrastructures; however, the uncertainty of such components increases the interactions between the local grid and energy markets for sustainable operation. In this study, day-ahead planning of a zero energy hub composed of wind turbine, photovoltaic, electric heat pump, boiler, chiller and storage units is optimized under the uncertainty of wind and solar units and energy market trading. In the designed structure, the required fuel for the local network is supplied through a power-to-hydrogen system to manage carbon emissions. In order to model the uncertainties and analyze the risk of decisions, a hybrid method consisting of the stochastic approach and information gap decision theory is applied. Furthermore, the impact of demand side elasticity for electrical, heating and cooling loads is evaluated. The results show that 10% of load participation significantly improves energy management actions and decreases operation costs by about 15.6%. The simulations also approve that the hybrid method handles the uncertainties under different conditions, where the risk-based cost functions change according to the operator attitude by about 522.44 $ for the ancillary parameter and scenario deviation equal to 10% and 20%, respectively.

Degradation-aware data-enabled predictive control of energy hubs

Mitigating the energy use in buildings, together with satisfaction of comfort requirements are the main objectives of efficient building control systems. Augmenting building energy systems with batteries can improve the energy use of a building, while posing the challenge of considering battery degradation during control operation. We demonstrate the performance of a data-enabled predictive control (DeePC) approach applied to a single multi-zone building and an energy hub comprising an electric heat pump and a battery. In a comparison with a standard rule-based controller, results demonstrate that the performance of DeePC is superior in terms of satisfaction of comfort constraints without increasing grid power consumption. Moreover, DeePC achieved two-fold decrease in battery degradation over one year, as compared to a rule-based controller.

Economic and performance analysis of ground source heat pump system for high-rise residential buildings considering practical applications

Ground source heat pump (GSHP) systems are being applied in various buildings to achieve carbon neutrality and zero energy building. Large-scale residential buildings have seen limited use of GSHP systems due to the absence of design guidelines and established operation methods. While design guides for general buildings are available from associations or institutes, there is a scarcity of designs and operation guides that consider dynamic simulations with occupant conditions and detailed load conditions. Generally, it is crucial for the economic analysis to optimally design suitable system capacity and accurately predict the performance. Therefore, in this study, the dynamic energy simulation model was constructed by considering the condition of the occupants and system operation and quantitively analyzed economic feasibility and system performance. Furthermore, the sensitive analysis based on the practical range of operation was conducted for comparison with conventional systems, district heating (DH) and electric heat pump (EHP) system. The heat pump's performance improved by up to 12.6% based on GSHP system design factors. Although the initial investment cost of the GSHP system was 51.5–84.7% higher than DH and EHP systems, its annual operating cost was 20.8–33.1% lower. The ground source heat exchanger had the most significant impact on performance, while the thermal storage tank's capacity had the largest impact on annual operating costs, aligning with previous research findings. In terms of carbon emissions, the annual CO2 emissions of the GSHP system were 49.1% lower than those of the existing system. The study highlights that GSHP systems can achieve high performance, economic efficiency, and low CO2 emissions based on the design approach. Additionally, the study provides valuable insights into GSHP system design, offers quantitative feasibility data, and compares them to traditional heating and cooling systems, taking practical cost considerations into account.

DEVELOPMENT AND CONFIGURATION OF A FULL-ORDER OBSERVER FOR «CABLE LINE – INDUCTION MOTOR» ELECTRICAL COMPLEX

Link for citation: Rakov I.V., Glazyrin A.S., Kladiev S.N. Development and configuration of a full-order observer for «cable line – induction motor» electrical complex. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 10, рр. 219-231. In Rus. The relevance. The task of oil production specialists is to minimize all types of energy consumption, ensuring an increase in oil production profitability because of the following reasons. First of all, availability of oil reserves with low energy consumption decreases, and the number of gushing wells reduces, along with increase in water content in the extracted liquid. One of the methods of reducing energy consumption in wells with low and moderate flow rate, equipped with electric submersible pumps, is a well transfer from continuous to periodic operation mode, namely cyclic well operation. This involves alternating short periods of oil production (up to 15 minutes) with liquid accumulation (up to 30 minutes) in the wellbore. Well switching to a cyclic operation mode leads to a 40 % reduction in electric power consumption by the submersible electric motor, as well as increase in oil production up to 3 %. This can be achieved by partial gravitational separation of the extracted liquid at the accumulation stage. However, a negative consequence of switching to a cyclic operation mode is a reduction in an average time between failures. This is due to increase in current surges and torque during rapid acceleration of the submersible electric motor to the rated speed. Transition from a scalar control system with an open loop to a vector control system without sensors can settle these problems. To implement a vector control system, it is necessary to obtain information about the state variables of a submersible electric motor. Construction of a full-order observer based on explicit mathematical models is considered as a promising method of obtaining information, taking into account the main advantages and disadvantages of direct measurement and indirect estimation of state variables. Based on the above, the urgent task is to develop a full-cycle observer for the electromechanical complex «cable line – induction motor» and a methodology for its configuration. The settlement of this issue will create prerequisites for implementation of a vector control system by a submersible electric motor. The main aim: to develop and experimentally validate the effectiveness of a full-order observer for the electrical complex «cable line – induction motor» using voltage and current measurements at a cable line input. Methods: literature analysis, system analysis, mathematical modeling, experimental research. Results. The authors have developed and tested a full-order observer for the «cable line – induction motor» electrical complex. The results of this study confirm the efficiency of the developed observer and its potential applicability for implementing a vector control system for electric submersible pumps. Ultimately, this will enable the transition of low- and medium-flow-rate oil wells to a cyclically operated mode without a significant reduction of the mean time between failures.

The changing impact of rural electrification on Indian agriculture

Rural electrification policies in the developing world primarily focus on household power, often at the cost of electricity supply to other productive sectors of the economy. We examine the consequences of this imbalance in rural electrification policy priority on agricultural development in India. Electric pumping of groundwater for irrigation is a major driver of India’s agricultural growth. However, the government of India shifted its rural electrification focus towards universal household electrification starting early 2000s. Using a newly constructed panel-dataset spanning three decades, we find that districts electrifying after the policy change experience much lower gains in electrified groundwater irrigation. On average, electrifying 100 additional rural households is associated with an increase of two additional electrified wells among newly electrified districts – eight times lower compared to 16 electrified wells per 100 electrified households among districts electrified pre-policy change. Our estimates imply that newly electrified districts would have witnessed nearly 20% more irrigated cropland in the dry season if rural electrification policy priorities had not shifted away from agriculture. These results highlight the need to complement household electrification with powering income-generating sectors of the rural economy.

Evaluation of geophysical parameters for groundwater productivity in the Commune of Jesse, Delta State Nigeria

&#x0D; Aquifer geohydraulic properties in Jesse were studied by the application of vertical electrical sounding (VES) and pumping test. The VES data was collected using ABEM SAS 1000 Terrameter and results processed using manual matching of curves and computer iteration, and interpreted in the forms of geologic models and geoelectric layers. The aquiferous unit was found at a depth of 5.30 m to 30.30 m with a range of resistivity from 87.30 Ω-m to 1945.40 Ω-m. Dar-Zarrouk parameters estimation and results of borehole pumping test produced the aquifer hydraulic parameters. The hydraulic conductivity values range from8.171 - 8.279 m/day, transmissivity from 43.8770 - 517.7480 m2/day, and formation factor from 0.369 - 8.501. These results are indications of a prolific and high yielding aquifer capable of withstanding long duration of pumping. Results of groundwater electrical conductivity and total dissolved solids ranged from 11.65 - 198.80 μs/cm, and 29.40 - 35.40 mg/dm3 respectively, signifying very moderate mineralization of the groundwater. The average electrical conductivity of 68.04 μS /cm and total dissolved solids of 32.58 mg/L were lesser than the acceptable limits of the Nigerian Standard for Drinking Water Quality (NSDWQ) of 1000 μS/cm and 500 mg/L respectively. This study affirmed that the aquifer in Jesse is suitable for groundwater exploitation for local and regional purposes.

Excitation Threshold Reduction Techniques for Organic Semiconductor Lasers: A Review

Organic semiconductor lasers have shown great application potential in various fields, such as low-cost sensing, high-performance lighting and display, and lab-on-a-chip devices. Since the introduction of organic lasers in the 1960s, research on semiconductor laser devices has expanded to include various materials and structures. The organic laser has attracted much attention due to its wide range of emission spectrum and simple synthesis and processing. Researchers constantly pursue the goal of using organic semiconductors to fabricate low-threshold thin-film organic laser devices while retaining the characteristics of a wide luminescence spectrum of organic materials, simple and portable structure, and low cost. However, organic semiconductor lasers face challenges due to material stability under optical pumping and large optical losses under electrical pumping, making commercialization difficult. Many scholars have put great efforts into enhancing the performance of materials and optimizing the structure to minimize the threshold of organic semiconductor lasers. Herein, based on the basic principles of organic lasers, the main factors affecting the excitation threshold are summarized. A comprehensive analysis of the relevant factors and threshold conditions is performed, considering both positive and negative aspects of modal gain and modal loss that need to be addressed. We expect to provide a wide range of ideas for reducing the threshold of organic lasers and offer theoretical guidance for the practical industrial production of organic lasers.

A case study on the failure analysis of 1 hp house hold electrical submersible pump in Prayagraj India

This paper deals with the failure analysis of a 1 HP household electrical submersible pump in Prayagraj city. The city is surrounded by two rivers i.e. the Ganga and the Yamuna. Therefore, domestic submersible pumps are widely used in the region. Hard water and sand particles cause various problems with the pump. The submersible pump consists of a pump section and a motor section. The failure analysis of the motor section consists of failure of the rotor, stator, cable and other parts. Similarly, the pump section consists of failure of the impeller, diffuser and other parts. Prevention methods for all failed components have also been discussed in this paper. The failure of a submersible pump can be summarized into three major categories i.e. mechanical failure (breakage, corrosion, dislocation and leakage), electrical failure (cable failure, motor failure, and connection severances) and operational failure (high temperature, high pressure and multiphase flow).