Total Power Requirement Research Articles

Power Management Strategy of a PEM Fuel Cell-Battery Powered Electric Vehicle

A MATLAB-Simulink based mathematical vehicle simulation model is developed in this investigation to analyze power management strategy of a proton exchange membrane (PEM) fuel cell and battery powered electric vehicle. The vehicle simulation model incorporated a real-world commercial passenger vehicle operator’s drive cycle inputs and associated vehicle dynamics to determine accurate estimation of total onboard power requirements and withdrawal of power from the fuel cell and battery sources to meet the demand. The power management strategy is designed to meet the vehicle’s onboard power demand based on the availability of hybrid combination of fuel cell and battery power sources. The fuel cell stack is the primary power source of the vehicle. The fuel cell is also charging the battery with excess power produced onboard and hence controls the state-of-charge of the battery. Battery is used as a supplemental power source for meeting the vehicle’s peak power demands. The parameters are optimized to implement the power management strategy by considering the battery state-of-the charge, the drive torque and the vehicle drive performance. The model simulation results with optimized parameters showed that the power requirement of the electric vehicle was significantly affected by the combination of fuel cell and battery power management system as well as the operating behaviors of the end user (driver).

Techno-economic feasibility study of coupling low-temperature evaporation desalination plant with advanced pressurized water reactor

The increasing demand for freshwater necessitates sustainable desalination solutions, and nuclear power plants offer a promising avenue by utilizing their low-grade waste heat. This study assesses a techno-economic feasibility of coupling a 5 MWth low-temperature evaporation plant with a UAE-based Advanced Pressurized Water Reactor (APR1400). The system addresses freshwater demand, aligning with sustainability goals through low-grade heat utilization. The investigation explores three extraction points for low-grade heat steam, with temperatures ranging from 80 °C to 130 °C. Thermodynamic evaluations using DE-TOP illustrate power requirements and losses, considering variations in maximum brine temperature from 50 °C to 65 °C. Economic analysis using DEEP estimates water production costs. Findings reveal negligible variances in power plant parameters and a minimal reduction in overall efficiency (<0.5 %). The power loss ratio increases proportionally (10 % to 18.6 %) with higher-temperature heat extraction, while the total power requirements for the desalination plant rises by around 30 %, with a negligible power output reduction ratios (0.03 % to 0.07 %). A consistent linear correlation between water production rate and maximum brine temperature doubles water production (∼900 to 1800 m3/day). Applying multiple extraction points across low-grade heat sources demonstrates scalability, reaching three times that of single-point extraction, with marginal increases in power requirements and losses, while maintaining the power reduction ratio below 0.15 %. Economic feasibility indicates competitive water production costs, ranging from 1.53 to 0.87 $/m3 for desalination capacities between 900 and 5400 m3/day. This study provides valuable insights into sustainable water production at the nexus of nuclear energy and desalination, with implications for necessary policy intervention.

Offshore wind energy potential along the Indian Coast considering ecological safeguards

This study focuses on assessing the offshore wind energy potential along the Indian Coast over a 10-year period (2005–2014) using high-resolution data from the simulation of the Weather Research and Forecasting (WRF) model. The predicted wind fields are utilized to identify potential sites, estimate offshore wind technical potential at different depths (ranging from 30 to 200 meters), and develop wind energy blocks within the Indian Exclusive Economic Zone. To ensure environmental protection, environmentally sensitive areas have been excluded from the offshore wind potential sites. The gross technical offshore wind potential was estimated to be 3941 GW within depths of 30–200 meters, excluding environmentally sensitive areas within the 0 to 30-m depth range. High-potential sites have been identified in the coastal states of Gujarat, Maharashtra, Kerala, and Tamil Nadu. The environmental offshore wind potential across these identified sites (feasible OWE sites) along the Indian coast is estimated at 432.34 GW within the 30 to 200-m depth range (at 140 m AGL).According to the report by the Central Electricity Authority (CEA), the predicted offshore wind power has the potential to significantly contribute to the country's total electrical power requirement for 2020–21. This study encourages exploration of offshore wind energy possibilities along the Indian coast and highlights the management challenges at suitable sites, including addressing potential conflicts between offshore wind energy development and other marine uses. The findings of this study can assist in the assessment of offshore wind resources and provide decision-makers with scientific evidence for the development of offshore wind energy in India, while also considering the management and conservation of marine ecosystems.

Design and techno-economic evaluation of hybrid renewable energy system for an Upazilla Health Complex (UHC) in Bangladesh

Upazilla Health Complex (UHC) offers the primary level health care facilities for rural communities. Every day thousands of patients come here for health care. The Health complex needs 24 hours electric supply. The national Grid cannot provide continuous electricity supply. Rural areas face various disturbance such as load shedding, blackouts problems and bad weather situation. In this paper, we report on the techno-economic assessment of net metering based On-grid photovoltaic system for Kaunia Upazila Health Complex in Rangpur District, Bangladesh. The analysis is based on the grid-connected photovoltaic system without battery storage. The HOMER software is used to obtain the overall analysis and the load study is carried out by HOMER powering tools. It suggests that the selected health complex requires a 34 kW PV system. The system’s net present cost (NPC) and the levelized cost of energy (COE) are $35,524 and $0.048 respectively. In this proposed system, renewable energy provides 99% of the total power requirements, while the generator and grid provide only 1%. The system produces 53,736 kWh a year of electricity where the system’s surplus electricity is 3226 kWh per year which can be sold to the national grid using a net-metering system.

Optimal placement and sizing of multiple distributed generators in power distribution networks

The primary objective of power systems is to meet the total power requirement, as well as to retain system reliability and security with the economic operation of the system. In recent years, exponential growth in power demand, lack of investments in up-gradation of electrical infrastructure, shortage in power generation and environmental concerns have been the key factors for unreliable and poor operation of the power systems. To tackle these problems, there is a need to rely on supplementary sources of generation and fortification of transmission capacity. Whereas, installation of large scale new generating units is not economical. An adequate number of small generating units incorporated is a more effective solution to meet the growing power demand. This research work focuses on the enhancement of voltage profiles while curtailing power loss by the optimal sizing and optimal placement of multiple distributed generators (DGs) at different buses. Different types of DG sizing and placement are carried out at 100%, 120% and 140% loading conditions.

Power distribution technique and small-signal modeling of grid-integrated solar PV system with hybrid energy storage systems

A model of a grid-integrated AC/DC microgrid with the assimilation of renewable energy resources and supercapacitors with battery storage-based hybrid energy storage is considered in this paper. The insertion of renewable resources and energy storage devices in the existing power grid requires rigorous analysis of the power balance and system stability. The microgrid is designed to absorb/deliver the defined power from/to the utility grid in a bidirectional manner. To simplify the power control strategy, the total power requirement in the system is divided into slow and fast varying components. So, the grid and battery will share the slowly varying components and the supercapacitor will suppress the fast varying components. This control strategy ensures improved performance by retaining the unity power factor operation of the grid, faster DC link voltage recovery, and harmonic mitigation. Again, a double-loop control structure based on small-signal modeling of the system is presented for stability analysis of the proposed system. MATLAB/Simulink results along with real-time simulation results are provided in this paper for verification of the proposed control technique.

Capacity optimal allocation of hybrid energy storage in DC distribution network based on Ensemble Empirical Mode Decomposition

In response to fluctuations in the power levels within the link connecting the direct current transmission system to the upper-level power grid, we propose an optimization approach for determining the ability of a Hybrid Energy Storage System (HESS). Our first step involves calculating the power agreement for the link and the total power requirements for the HESS, taking into account the system’s net load power and the dynamic pricing of electricity based on time-of-use. Subsequently, we utilize the Ensemble Empirical Mode Decomposition (EEMD) technique to break down the total energy generated by the HESS into its constituent components. Incorporating instructions for both powering up and losing power of the HESS across varying filter orders, we solve the capacity allocation model for the HESS using a particle swarm algorithm, with rated power and rated capacity as decision variables. Finally, we identify the filter order that yields the best objective function value and the corresponding energy storage configuration scheme. An illustrative analysis, conducted on an enhanced IEEE-14 node DC distribution network, demonstrates that the proposed HESS configuration effectively mitigates tie-line fluctuations and enhances system stability.

Photovoltaic assessment to achieve energy neutral buildings and cities in equatorial Andean climate

Energy is an important issue in the entire world and in under-development countries especially in these regions is where the main growth of energy requirements is expected. For more than fifty years ago Ecuador has been subsidizing fuels, considering that energy prices do have a huge impact on lowincome families. Cities and buildings do play a relevant role in reducing energy requirements to import energy to urban areas in order to achieve the maximum energy self-supply capability in buildings and cities. This study describes shortly recent works performed in Cuenca to decipher the energy resources available and the capability to self-supply in Cuenca, Ecuador. The main results obtained show that photovoltaics (PV) in buildings is the best option, it could supply the entire power requirements in the city, and around 22 % of the electrical requirements of industrial high-consumption buildings, also for a single-family home it is only required around 7 m2 of roof that corresponds around 10 % of a typical roof availability of a typical 2-floor house, and for higher education building it is possible to achieve the total power requirement with PV technology, but grid limitations imply limitations also to PV capability.

Novel Planning Methodology for Spatially Optimized RES Development Which Minimizes Flexibility Requirements for Their Integration into the Power System

An optimization model which determines optimal spatial allocation of wind (WPPs) and PV power plants (PVPPs) for an energy independent power system is developed in this paper. Complementarity of the natural generation profiles of WPPs and PVPPs, as well as differences between generation profiles of WPPs and PVPPs located in different regions, gives us opportunity to optimize the generation capacity structure and spatial allocation of renewable energy sources (RES) in order to satisfy the energy needs while alleviating the total flexibility requirements in the power system. The optimization model is based on least squared error minimization under constraints where the error represents the difference between total wind and solar generation and the referent consumption profile. This model leverages between total energy and total power requirements that flexibility resources in the considered power system need to provide in the sense that the total balancing energy minimization implicitly bounds the power imbalances over the considered time period. Bounding the power imbalances is important for minimizing investment costs for additional flexibility resources. The optimization constraints bound the installed power plant capacity in each region according to the estimated technically available area and force the total energy production to equal the targeted energy needs. The proposed methodology is demonstrated through the example of long-term RES planning development for complete decarbonization of electric energy generation in Serbia. These results could be used as a foundation for the development of the national energy strategy by serving as a guidance for defining capacity targets for regional capacity auctions in order to direct the investments in wind and solar power plants and achieve transition to dominantly renewable electricity production.

Improvement of Autonomy, Efficiency, and Stress of Fuel Cell Hybrid Electric Vehicle System Using Robust Controller

Among issues facing the transportation sector today is the limited autonomy of electric vehicles, which are highly reliant upon energy storage systems. Considering this issue as the current research gap, researchers seek to prolong vehicle dependability through renewable-free and sustainable energy that tackles negative environmental impacts. This research exploits the electric vehicle’s kinetic energy to improve its performance and reliability. It uses fuel-cell resources and supercapacitors hybridized with lithium-ion batteries, in addition to DC generators connected to front wheels that convert their rotations into energy contributing to the vehicle’s overall power balance. A state machine-based energy management strategy computes fuel-cell setpoint power, while a dual-loop structure uses a super-twisting controller for DC bus voltage regulation and recovery, in addition to tracking banks’ setpoint currents. A speed controller-based artificial intelligence is proposed to reduce power losses and enable accurate tracking of running trajectory to improve vehicle mechanisms. The simulation results using Matlab Simulink software proved the proposed vehicle’s feasibility by adopting the free kinetic energy of additional DC generators that provided 28% of its total power requirements, resulting in superior supply efficiency reaching 98%. Thus, the stress on FC and battery was minimized by 21% and 10%, respectively, in addition to reducing fuel consumption by 39%, so the vehicle autonomy was extended, and its reliability was enhanced and supported, as targeted.

A novel approach to estimate power demand of auxiliary engine loads of light duty vehicles

On par with rapid motorization, excessive energy demand and air pollution have become major challenges in the global context. Fuel economy programs and emission reduction targets have proven to be among the most effective in mitigating these issues. In developing successful fuel economy programs and policies, understanding the factors affecting the fuel consumption of road vehicles is essential. Auxiliary engine loads are one of the commonest factors affecting a vehicle’s fuel economy performance. An auxiliary engine load is defined as the energy utilized to operate auxiliary equipment that draws its power from the vehicle’s engine. This study was limited to light duty vehicles, and an analytical method was adopted to assess the fuel economy impact of the auxiliary equipment in terms of air-conditioning load, alternator load, and water pump and steering pump load. As one of the main deliverables, the study developed a novel approach for estimating and modeling the air-conditioning load which is the major auxiliary energy consumer. For an average car of 100 brake horsepower (bhp) (74.7 kW), the engine auxiliary equipment consumes approximately 13.130 kW of power at an engine operating speed of 3,000 RPM, which amounts to 17.6% of the total bhp output. The major contributors to engine power demand are the air-conditioning unit and the alternator, which account for over 97% of the total auxiliary power requirement, while the water-pump and power steering-pump use relatively little power at 3% of the total auxiliary power demand. The novelty of the method adopted during this study is that it theoretically determines the major contributor of the auxiliary power demand, the air-conditioning load, whereas prior reports have used approaches involving empirical methods.

Feasibility and Techno-Economic Evaluation of Hybrid Photovoltaic System: A Rural Healthcare Center in Bangladesh

This study aimed to investigate a techno-economic evaluation of the photovoltaic system, along with a diesel generator as a backup supply, to ensure a continuous twenty-four hours power supply per day, no matter the status of the weather. Healthcare centers in Bangladesh play a vital role in the health issues of the residents of rural areas. In this regard, a healthcare center in Baliadangi—Lahiri Hat Rd, Baliadangi, Thakurgaon, Bangladesh, was selected to be electrically empowered. The simulation software Hybrid Optimisation Model for Electric Renewables (HOMER) and the HOMER Powering Health tool were used to analyze and optimize the renewable energy required by the healthcare center. It was found that the healthcare center required a 24.3 kW solar PV system with a net current cost of $28,705.2; the levelized cost of electricity (LCOE) was $0.02728 per kW-hours, where renewable energy would provide 98% of the system’s total power requirements. The generator would provide 1% and the grid would supply the remaining 1%. The load analysis revealed that the hybrid PV system might be superior to other power sources for providing electricity for both the normal function and the emergencies that arise in healthcare’s day-to-day life. The outcome of the study is expected to be beneficial for both government and other stakeholders in decision-making.

Osmotically assisted reverse osmosis, simulated to achieve high solute concentrations, at low energy consumption

Microbial electrosynthesis (MES), is an emerging technology, for sustainable wastewater treatment. The dilute acetate solution, produced via MES, must be recovered, as dilute solutions can be expensive to store and transport. The acetate is expensive and environmentally damaging to recover by heat-intensive evaporative methods, such as distillation. In pursuit of a better energy economy, a membrane separation system is simulated to raise the concentration from 1 to 30 wt%, at a hydraulic pressure of approximately 50 bar. The concentrate is then simulated to be heat dried. Reverse osmosis (RO) could rase the acetate concentration to 8 wt%. A novel adaptation of osmotically assisted reverse osmosis (OARO) is then simulated to increase the concentration from 8 to 30 wt%. The inclusion of OARO, rather than a standalone RO unit, reduces the total heat and electric power requirement by a factor of 4.3. It adds to the membrane area requirement by a factor of 6. The OARO simulations are conducted by the internal concentration polarisation (ICP) model. Before the model is used, it is fitted to OARO experimental data, obtained from the literature. Membrane structure number of 701 µm and permeability coefficient of 2.51 L/m2/h/bar are ascertained from this model fitting exercise.

Examination of Desalination Model Parameters on a Reverse Osmosis Desalination Simulation Model

The clean water and energy are both the most important needs of mankind. The increasing population and the necessity to meet the need for freshwater requirements make the desalination process a popular topic. The reverse osmosis is one of the most popular technique for desalination. The main advantages of the reverse osmosis over other desalination techniques are the lower energy consumption and the robustness to the salinity of feedwater. The ambient conditions are the key parameters affecting the efficiency of desalination process. On the other hand, the design parameters of a reverse osmosis desalination plant also play an important role in the process. In this paper, both ambient conditions and the design parameters are investigated. The contributions of the study are to determine variation the specific power consumption and related total power requirement of single stage reverse osmosis desalination plant model with the ambient conditions and design parameters. The effects of design parameters and ambient conditions for power requirements are given in the results section. The simulation studies are performed at constant production rate in order to see the effects of each parameter to product properties. The increase in seawater temperature for constant seawater salinity decreases the power consumption while increasing the salinity of final product. The results indicated that design parameters should be optimized according to the size of the designed system and salinity of feedwater. Also, a case study is performed for a point at Marmara Region, Turkey.

Coupled Calculations of Data Center Cooling and Power Distribution Systems

Abstract Physics-based modeling aids in designing efficient data center power and cooling systems. These systems have traditionally been modeled independently under the assumption that the inherent coupling of effects between the systems has negligible impact. This study tests the assumption through uncertainty quantification of models for a typical 300 kW data center supplied through either an alternating current (AC)-based or direct current (DC)-based power distribution system. A novel calculation scheme is introduced that couples the calculations of these two systems to estimate the resultant impact on predicted power usage effectiveness (PUE), computer room air conditioning (CRAC) return temperature, total system power requirement, and system power loss values. A two-sample z-test for comparing means is used to test for statistical significance with 95% confidence. The power distribution component efficiencies are calibrated to available published and experimental data. The predictions for a typical data center with an AC-based system suggest that the coupling of system calculations results in statistically significant differences for the cooling system PUE, the overall PUE, the CRAC return air temperature, and total electrical losses. However, none of the tested metrics are statistically significant for a DC-based system. The predictions also suggest that a DC-based system provides statistically significant lower overall PUE and electrical losses compared to the AC-based system, but only when coupled calculations are used. These results indicate that the coupled calculations impact predicted general energy efficiency metrics and enable statistically significant conclusions when comparing different data center cooling and power distribution strategies.

Design, Testing and Feasibility Analysis of an Oil-Free Twin Screw Compressor with In-Chamber Flash Cooling

With the current aim of reducing CO2 emissions worldwide compressor efficiency is more in focus than ever before. An estimated 20% of all electricity generated worldwide is used for compressing air. Oil injected twin screw compressors form a large percentage of the total. The injected oil is used for cooling, as well as for sealing and lubrication of the rotors. Typical pressure ratios lie between 8:1 and 16:1. There are many investigations being conducted into oil-free screw technology for specific applications requiring no oil carry over. In this presentation we will take a close look into the possibility of producing a single stage oil-free twin-screw compressor operating at a pressure ratio of 8:1 and using evaporated water for cooling. The main objective in this case is to improve compressor efficiency. Additionally, we will compare efficiency results with a state-of-the-art single stage oil injected twin screw compressor. Previous results from an earlier paper by the author and team from City University of London on CFD analysis of a similar system are taken as the basis. Further simulated calculations using SCORG for the actual case in question allow preliminary performance analysis using the multi-domain chamber model. From simulation we can see that the oil drag force acting on the rotors forms a significant part of the total power requirement. It is therefore suggested that an oil-free solution will achieve improved specific power. To confirm this concept, verify the simulated calculations and understand the heat transfer process in the compression chamber more fully, experimental analysis was undertaken.

A randomized algorithm for joint power and channel allocation in 5G D2D communication

We formulate the joint power and channel allocation problem (JPCAP) for device to device (D2D) communication as a cost minimization problem, where cost is defined as a linear combination of the number of channels used and total power requirement. We first show that JPCAP is a NP-hard problem and providing n1/ε approximation for JPCAP ∀ε>0 is also NP-hard. Then we propose a mixed integer linear programming (MILP) to solve this problem. As solving MILP is a NP-hard problem we propose a greedy channel and power allocation (GCPA) algorithm to assign channels and powers to the links. We design GCPA in such a fashion that there exists an order of the links for which it produces optimum solution. We show that an order is equivalent to many orders and hence design an incremental algorithm (IA) to efficiently search good orders. Finally using IA we develop a randomized joint channel and power allocation (RJCPA) algorithm. We show that if a certain condition holds we can find the optimum in expected polynomial time else a slowly growing exponential time with very high probability. We then theoretically calculate the expected cost and energy efficiency (EE) produced by RJCPA. Through simulation, we show that RJCPA outperforms two existing approaches with respect to both cost and EE significantly. Finally we validate our theoretical findings through simulation.

Comparative study of embodied energy of affordable houses made using GFRG and conventional building technologies in India

The present situation vis-á-vis increased energy use and environmental emissions has urged the building sector to contribute more towards sustainable construction. This is possible only through appropriate choice of building materials and technologies that minimize the environmental impacts. Nevertheless, the adoption of the same need to necessarily satisfy the user in terms of aesthetics, utility and cost. This paper presents the comparison of embodied energy of a two-storey residential building, made using, i) GFRG (glass fibre reinforced gypsum), and, ii) load-bearing brick masonry, building technologies. GFRG technology uses load-bearing walls and slabs that are manufactured using gypsum waste, and consumes reduced quantity of reinforced concrete in comparison with conventional construction. It has been found in this study that the embodied energy related to building materials of the GFRG building is 16% less, and that associated with transport of resources is twice, compared to the conventional brick masonry building. The major advantages of the GFRG building construction are found to be about – reduction in structural weight and construction cost, – savings in construction time and – savings in total man power requirement for construction. Further, the use of cement, steel rebar and sand is reduced by 25%, 36% and 44% respectively.

Master Installation Design And Transformer Need Analysis in Faculty of Engineering Udayana University Denpasar

Faculty of Engineering, Udayana University, PB. Sudirman Denpasar has 5 building units (buildings A, B, C, D, AF). Currently the AF building is undergoing renovation and is planned to be on 4 floors. The entire building will be equipped with the installation of 2 elevator units. The construction of the two new buildings and the installation of the 2 elevator units caused new problems of electricity shortages, changes in safety settings, unbalanced loads, and changes in the size of the main cable and the needs of the transformer and its capacity. The AF building and building A are supplied from sources on the transformer which are joined with other faculties, while Buildings B, C, D and E are fed by one transformer No. 124303818 with a capacity of 160 kVA. The plan to build an Alumni Building does not yet have electricity.&#x0D; Based on the analysis of the design, the total amount of power needed in all buildings in the Sudirman Denpasar Faculty of Engineering is the result of the AF Building planning = 134,280 watts, the Alumni Building planning results (building area and building functions are considered equal = 134,280 watts), so the total needs power to the two buildings = 271 560 Watt with a load deviation of 65%, then 0.65 x 271 560 W = 176 514 Watt. Then the total power requirement of the entire building is 259,340 watts. The measurement result of Cos ? 0.92, then P (kVA) = 281,891,3043 Ampere = 281,8913 kVA. So that the transformer needs that must be prepared by the Faculty of Engineering to meet the power requirements at the Faculty of Engineering, Udayana University Denpasar with 80% transformer efficiency is a 350 kVA transformer with a placement position around the Faculty of Engineering area

Graphene Synthesis by Inductively Heated Copper Foils: Reactor Design and Operation

We report on the design of a reactor to grow graphene via inductively heating of copper foils by radio frequency (RF) magnetic fields. A nearly uniform magnetic field induced by Helmholtz-like coils penetrates the copper foil generating eddy currents. While the frequency of the current is being rapidly varied, the substrate temperature increases from room temperature to ~1050 °C in 60 s. This temperature is maintained under Ar/H2 flow to reduce the copper, and under Ar/H2/CH4 to nucleate and grow the graphene over the entire copper foil. After the power cut-off, the temperature decreases rapidly to room temperature, stopping graphene secondary nucleation. Good quality graphene was obtained and transferred onto silicon, and coated with a 300 nm layer of SiO2 by chemical etching of the copper foil. After synthesis, samples were characterized by Raman spectroscopy. The design of the coils and the total power requirements for the graphene induction heating system were first estimated. Then, the effect of the process parameters on the temperature distribution in the copper foil was performed by solving the transient and steady-state coupled electromagnetic and thermal problem in the 2D domain. The quantitative effects of these process parameters were investigated, and the optimization analysis results are reported providing a root toward a scalable process for large-sized graphene.