Load Requirements Research Articles

An Effective Control Approach of Hybrid Energy Storage System Based on FLC/Grey Wolf Optimisation

In the modern era, the integration of renewable energy sources (RES) has bolstered the autonomy of urban energy infrastructures, reducing reliance on distant sources and grids. Batteries serve as a vital bridge between power supply and fluctuating load demands within RES systems. However, the unpredictable nature of RES behavior and varying load requirements often subject batteries to repeated deep cycles and irregular charging patterns. These cycles diminish the battery’s lifespan and escalate replacement costs. This study presents an innovative control strategy for a Solar-Wind model featuring a Battery-Supercapacitor Hybrid Energy Storage System. The objective is to prolong the battery’s operational lifespan by mitigating intermittent strain and high current demands. In contrast to conventional methods, the proposed control approach incorporates a Low-Pass Filter (LPF) and a Fuzzy Logic Controller (FLC). Firstly, the LPF minimizes the oscillations in battery consumption. Simultaneously, the FLC optimizes the high current demand on the battery while vigilantly monitoring the supercapacitor’s charge levels. Moreover, Grey Wolf Optimization (GWO) is employed to fine-tune the FLC’s membership functions, ensuring optimal peak current attenuation in batteries. The effectiveness of the proposed model is benchmarked against standard control techniques, namely Rule- Based Controller and Filtration-Based Controller. Comparative analysis reveals that the proposed method substantially reduces peak current and high power requirements of the battery. Consequently, this enhances the utilization of the supercapacitor, significantly augmenting the battery’s operational life. The results demonstrate a remarkable improvement over conventional systems, emphasizing the potential of this approach in optimizing energy storage systems for sustainable, long-term performance.

Energy, exergy, economic, and environmental (4E) analysis of SAHP water heaters in very cold climatic conditions

Solar-assisted heat pumps (SAHPs) are emerging as promising solutions for space/water heating. Compared to conventional air-source heat pumps (ASHPs), SAHPs show superior thermal performance in cold climates where outdoor air temperatures are below freezing most of the heating season. However, given the inherent variability of solar energy, SAHPs have poor thermal performance to meet the load requirements during periods of weak solar radiation. To enhance the reliability of SAHPs, an air-source evaporator can be integrated with a SAHP, forming a dual SAHP – ASHP system with better performance. In this research, the energy, exergy, environmental, and economic performance of a dual-source solar/air source heat pump, which provides hot water for a typical Canadian household, is investigated. The performance of the system is compared with a solar-assisted direct-expansion heat pump (DX-SAHP), an ASHP, and conventional gas/electric water heaters. A thoroughly validated mathematical model based on heat transfer and thermodynamics fundamentals is developed and implemented in MATLAB® coupled with the CoolProp® library, which gives the refrigerant's properties. Results highlight the superior performance of the dual-source heat pump, particularly in the summer, where it surpasses the DX-SAHP. Among the examined heat pump configurations, the dual-source heat pump demonstrates the lowest annual power consumption. The system attains the maximum monthly average COP of 3.94 and achieves a minimum of 2.4 during the severe winter season in Calgary, Alberta. Compared to a conventional ASHP, the energy consumption of the system was reduced by 25%. The second-law analysis shows that the ASHP obtains the highest monthly average exergy efficiencies, followed by the DX-SAHP and the dual-source heat pump. Furthermore, results show that the solar/air source heat pump water heater can reduce CO2 emissions by 1450 kg/year, while the system's payback period is 19 years.

Design Optimization of a Grid-Tied Hybrid System for a Department at a University with a Dispatch Strategy-Based Assessment

In this research project, the optimal design and design evaluation of a hybrid microgrid based on solar photovoltaics, wind turbines, batteries, and diesel generators were performed. The conventional grid-tied mode was used in addition to dispatch strategy-based control. The study’s test location was the loads in the Electrical, Electronic and Communication Engineering (EECE) department at Pabna University of Science and Technology (PUST), Pabna, Bangladesh. DIgSILENT PowerFactory was employed to determine the power system-based behaviors (electrical power, current, voltage, and frequency) of the proposed hybrid system, while a derivative-free algorithm was used for the expense, optimal size, and emission assessments. While developing the microgrid, load following (LoF) and cycle charging (CyC) control were employed. The microgrid is supposed to have a 23.31 kW peak load requirement. The estimated microgrid’s levelized cost of energy (LE), its net present cost (NC), its operating cost, and its annual harmful gas emissions were estimated in this work. Additionally, since the microgrid is grid-connected, the amount of energy output that might be exported to the grid was also estimated, which will potentially increase during blackouts. The power system responses found in this study ensure that the various microgrid components’ voltage, frequency, current, and power outcomes are steady within the designated range, making the microgrid practical and robust.

Perencanaan Ulang Rumah Susun Tenaga Pendidik Universitas Gadjah Mada dengan Konsep Building Information Modeling (BIM) 5D

The innovative development in construction technology has introduced a system called Building Information Modeling (BIM), which can facilitate processes from pre-construction to post-construction. Therefore, this research focuses on the redesign of the University of Gadjah Mada's Faculty Housing Tower using the integrated BIM concept, based on structural analysis with ETABS and modeling with Tekla Structures. The redesign is carried out according to SNI 2847-2019 for concrete building structures, SNI 1727-2020 for loading requirements, and SNI 1726-2019 for seismic resilience standards. This redesign produces a structural analysis to assess the structural feasibility of the building. The 3D design modeling is performed using Tekla software, which can generate 2D designs for Detail Engineering Design, as well as provide the necessary volume of work for cost estimation (RAB calculation). Additionally, the software allows for scheduling and work simulation. The redesign of the University of Gadjah Mada's Faculty Housing Tower results in a budget plan of IDR 24,274,962,257.00, calculated using Quantity Take Off from the Tekla Structures software. The scheduling and work implementation simulation for the structural components are also done using Tekla Structures software. The duration of this redesign project is estimated to be 4 months and 2 weeks, starting from the preparation phase to the completion of the roof structure

Design and implementation of the monochromator shielding for the cold neutron spectrometers XINGZHI and BOYA

An innovative monochromator shielding is designed and implemented for the cold neutron spectrometers XINGZHI and BOYA operated by Renmin University of China at China Advanced Research Reactor. Via Monte Carlo simulations and careful mechanical designs, a shielding configuration has been successfully developed to satisfy safety requirements of below 3 μSv/h dose rate at its exterior, meanwhile fulfilling space, floor load and nonmagnetic requirements. Composite materials are utilized to form the sandwich-type shielding walls: the inner layer of boron carbide rubber, the middle layer of steel-encased lead and the outer layer of borated polyethylene. Special-shaped liftable shielding blocks are incorporated to facilitate a continuous adjustment of the neutron energy while preventing radiation leakage. Our work has demonstrated that by utilizing composite shielding materials, along with the sandwich structure and liftable shielding blocks, a compact and lightweight shielding solution can be achieved. This enables the realization of advanced neutron scattering instruments that provide expanded space of measurement, larger energy and momentum coverage, and higher flux on the sample. This shielding represents the first of its kind in neutron scattering instruments in China. Following its successful operation, it has been subsequently employed by other neutron instruments across the country.

Voltage Regulation and Power Factor Enhancement for EV Charging Station by Using Optimization Algorithm

A Cuk converter-based Power Factor (PF) and voltage regulation enhancement model for an electric vehicle (EV) charging circuit is created and developed, utilizing an optimization technique. Using the Cuk converter's performance measures in Continuous Conduction Mode (CCM), the charging system may produce a steady output current with better PF. This project implements an optimization algorithm-based correction approach for power factor and voltage regulation. The Jaya optimization algorithm, which is a basic metaheuristic algorithm, uses less algorithm-specific parameters. The use of an optimization algorithm aids in the dynamic adjustment of converter operation to maintain the appropriate power factor and voltage levels under non-linear situations such as load fluctuations and input changes. The algorithm evaluates the output and modifies the system's parameters to optimize performance for real-time EV applications, taking into account factors such as changing load requirements, input supply uncertainty, and desired voltage levels. The suggested method is created and tested in MATLAB/Simulink. The suggested algorithm is then confirmed experimentally as a hardware prototype.

Forecast-based stochastic optimization for a load powered by wave energy

Stand-alone renewable energy systems, which harness and use electricity without connection to a distribution grid, can benefit from using resource forecasts when making real-time decisions on how to manage power. An example of this is an ocean observation system that uses a wave energy converter (WEC) and battery bank to produce and store electricity in order to meet electrical load requirements for oceanographic sensors and instrumentation. By using wave forecasts to optimize the power consumption of this system, it is possible to reduce the size of the WEC and battery bank needed, thereby reducing the overall system’s cost and complexity. In this paper, we assess the benefits of forecasting for a generic wave-powered ocean observation system. We model an observation platform powered by a WEC and battery-storage system that can switch between four power states, full power: 600 W, medium power: 450 W, low power: 45 W, and survival mode: 1 W. To determine which power state to enter over time, we present a stochastic optimization method that interprets wave forecasts and system information to select a power state on an hourly basis and simulate over two months of consecutive decisions. Using this simulation framework, we compare 8 power management strategies across a range of WEC sizes (3–5 m) and battery capacities (2.5–35 kWh). We find that it is possible to maintain full (600 W) power consumption over the entire simulation window with a 5 m diameter WEC and 25 kWh battery bank, which is on the upper end of the ranges evaluated. To employ a smaller WEC or battery, load flexibility is required. We find that forecast-based methods for this power management handle tradeoffs in performance (e.g., cumulative power consumption, reducing intermittencies and meeting scheduled load targets) more effectively than power management strategies that do not use forecasting. Overall, our results indicate that forecasting for our stand-alone renewable energy system is most impactful when some loads must be met on or within a defined schedule.

Life cycle environmental analysis of offshore wind power: A case study of the large-scale offshore wind farm in China

China's decarbonization is indispensable for the large-scale utilization of renewable energy. In this process, the development of offshore wind energy has become an important support, because in the eastern region of China, especially the coastal areas, there's the most load requirements but limited onshore renewable resources. Under the goals of both carbon neutral and sustainable development, however, there's still a research gap in evaluating the environmental impacts of large-scale offshore wind plants in China. In this study, the research performed a comprehensive process-based life cycle environmental analysis of a large-scale (400 MW) offshore wind farm with large wind turbine units (5 MW) in China. Global Warming Potential is 25.73 g CO2-eq/kWh and greenhouse gas payback time is calculated as 12.05 months. Fossil fuel consumption amounts to 0.31 MJ/kWh with an energy payback period of 25.56 months. Material resources and ecotoxicity to freshwater need more attention with the values of 1.68 CTUe/kWh and 3.32 10−6 kg Sb-eq/kWh, respectively. The manufacturing stage contributes most to all the impacts examined. The disposal and recycling process shows significant environmental benefits for most impacts but exerts burdens on the particulate matter. Focusing on Global Warming Potential, the wind turbine generation set has the highest effect, among which the blades contribute 73.2% of it. Further, the evolution of electricity and heating mix of China and use of biomass-based precursors could decrease 57% of the blades' greenhouse gas emissions in 2050. This study could provide guidance on the sustainable design and policy-making of offshore wind farms.

Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach

This paper delves into the increasingly complex domain of Optimal Power Flow (OPF) within modern power systems, enhanced by the integration of unpredictable renewable energy sources. The research originally integrates stochastic photovoltaic and wind energy sources, along with a suite of Flexible AC Transmission System (FACTS) components – including thyristor-controlled series compensators, static VAR compensators, and thyristor-controlled phase shifters. The primary objective is to solve the OPF problem by reducing generation costs while accommodating the variable nature of renewable energy sources and load demands. This study prioritizes the examination of both constant and fluctuating load requirements. The inherent variability of PV and wind energy, along with load demand, is captured through the modelling of probability density functions. This approach enables a more detailed optimization process, incorporating not just the cost of thermal energy generation but also the scheduling costs of renewable sources and associated penalty costs. Moreover, the study examines the strategic placement and sizing of FACTS components, an aspect essential in minimizing the overall cost of power production. Employing both single- and multi-objective optimization algorithms, the research addresses the OPF problem in a modified IEEE-30 bus system through various case studies. The application of the recently developed flow direction algorithm, including its multi-objective variant with an ε-based constraint-handling mechanism to OPF problem is the primary contributions of this work. The results, benchmarked against several advanced metaheuristic algorithms, reveal the proposed algorithm's superior performance. This comprehensive study not only underscores the potential of integrating renewable energy sources into the grid but also highlights the efficacy of intelligent optimization strategies in managing the complexities of modern power systems.

The Impact of Fiber Density and Layering in NFRP on Confined Concrete Compressive Strength

Strengthening columns holds a crucial role in structural engineering and is frequently called for due to a range of factors, including heightened load requirements, structural degradation, design flaws, or the need for seismic retrofitting. Natural Fiber-Reinforced Polymers (NFRP) in concrete reinforcement has gained significant attention in recent years as a sustainable and eco-friendly alternative to strengthened reinforced concrete. NFRP jacketing presents an adaptable option, as it delivers an improved load-carrying capability as a confining effect. This paper explores the fundamental reasons behind the need for column strengthening and the advantages of employing NFRP jacketing as a preferred method. The study examined the influence of varying fiber densities and the number of fiber layers in NFRP on the mechanical properties of concrete, with a specific focus on its confined concrete compressive strength. The test specimen was a cylinder with a diameter of 150mm and a height of 300mm. NFRP, made from abaca fiber and resin, was attached around the specimen’s circumference to provide a confinement effect. Axial load was applied to the test specimen. The findings indicated that introducing abaca fiber as an NFRP material increased confined concrete compressive strength by up to 37% compared to unconfined concrete. Moreover, the application of three layers of NFRP fibers results in a 15% rise in confined concrete stress, especially when higher-density fiber types are utilized. Study findings suggest that natural fiber density and the number of layers play a role in enhancing concrete strength, however, their influence may not be significantly pronounced.

Ekonomik yük dağıtım problemi için elektrik baliği optimizasyonu

The Economic Load Dispatch (ELD) problem is an essential aspect of power system planning and operational scheduling. Different techniques and algorithms have been recommended to solve it, aiming to minimize the cost of power generation with satisfying the load requirements. In this paper, a new algorithm called Electric Fish Optimization (EFO) is used to solve the ELD problem by considering the line losses, ramp rate limits, maximum and minimum capacities of the generators and prohibited operating zones (POZ). The algorithm has been utilized in test systems consisting of 6 and 15 units and its outcomes have been compared to those from previous research studies. The proposed algorithm has been shown to achieve minimum cost, indicating its superiority and effectiveness in addressing power system planning challenges. It is evident that the presented algorithm offers a valuable solution for optimizing ELD problems.

Evaluating High‐Pressure Torsion Scale‐Up

Increasing sample dimensions in high‐pressure torsion (HPT) processing affects load and torque requirements, deformation distribution, and heating. Finite‐element modeling (FEM) and experiments are used to investigate the effect of technical parameters on the scaling up of HPT. Simulations confirm that axial load and torque requirements are proportional to the square and the cube of the sample radius, respectively. The temperature rise also displays a pronounced dependency on the radius. Decreasing the diameter‐to‐thickness ratio can cause heterogeneity in strain distribution along the thickness direction at the edges of the sample. Such heterogeneity is governed by friction conditions between the material and the lateral wall of the anvil depression. Simulation of HPT processing of ring‐shaped samples shows that it is possible to reach more homogeneous distribution of strain and flow stress in the processed material. Experiments using magnesium confirm a tendency for strain localization in the early stage of HPT processing but increasing the number of turns increases the homogeneity of the material. The embodied energy in HPT processing is discussed.

Performance Assessment of a MPID controller in Microgrid Systems for Load Frequency Control

This study provides a novel methodology to design an A.C. off-grid multi-microgrid (MMG) system and suggests an analytical method for load frequency management utilizing a multistage PID (MPID) controller based on the sine cosine algorithm. The unique benefits of an MMG system are similar to those of renewable energy sources (RES), such as solar system models, wind turbine models, etc. There is a conflict between the MMG system's source and the load requirement because of the erratic properties of renewable energy sources. The irregular nature of renewable energy sources has an impact on the frequency of the system. Therefore, it is very difficult these days to check the frequency in a MMG system. This article uses the SCA-based MPID to tune the controller parameter for secondary frequency control, despite all of the complexity. In the power system, LFC (load frequency control ) is achieved by regulating active power. The dynamic response of the conventional PI-PID controller has been used to assess the effectiveness of the proposed MPID controller. Using the sine and cosine approaches, the parameters are optimized.

An integrated framework for techno-enviro-economic assessment in nanogrids

This paper presents an integrated framework designed for capacity planning of grid-connected nanogrid, a small solar and energy storage system that can provide kilowatt-level services to individual buildings. This framework comprehensively evaluates nanogrid cost-effectiveness, sustainability, and reliability, employing a multi-faceted techno-enviro-economic assessment approach. Traditional nanogrid capacity planning often prioritizes peak load requirements, which may lack optimality owing to occasional peak load occurrences. Conversely, optimizing solely for base load requirements might also fall short of effectiveness, compromising reliability and sustainability objectives. The proposed framework employs a three-step, integrated process for nanogrid (NG) capacity planning. Firstly, the Planner module identifies optimal asset sizing considering a two-day look-ahead logic. Then, the Operator module serves as a digital twin for the system, conducting hourly calculations over a short-term horizon. Lastly, the Evaluator module evaluates technical, environmental, and economic metrics for each solution, assessing the effectiveness of asset-sizing decisions. A simulated case study has demonstrated the effectiveness of the proposed framework. The technical assessment revealed that a PV size of 24 kW and a storage capacity of 91 kWh led to the most reliable solution, with a probability of local sufficiency of 95 percent. Furthermore, the environmental assessment showcased a renewable fraction of 94% with a PV size of 26 kW and a storage of 85 kWh. Economically, the analysis identified that a PV size of 12 kW and a storage size of 24 kWh led to the minimum total cost. In contrast, a PV size of 26 kW and a storage size of 85 kWh yielded a total operating savings of $4,801.

Design and Simulation of Autonomous Up-and-down System for Transmission Line Live Operation Robot with the UAV Assistance

Aiming at the current bottleneck problem that restricts the practical application of robot system engineering in transmission line live operation, in order to improve the on-line and off-loading efficiency of live working robots on transmission lines and improve the practical level of the robot system as a whole, this paper proposes a design and operation method of autonomous on-line and off-loading mechanism of double-arm live working robots based on UAV assistance. Firstly, the realization process of autonomous up-and-down of the robot was analyzed, based on which the structure of the auxiliary hook of the up-and-down system and the lifting winch were designed. Then, the force analysis was carried out on the up-and-down process of the robot, and the appropriate winch drive motor was selected through theoretical calculation. In order to ensure the rationality of the up-and-down process, the operation motion planning was carried out on the up-and-down of the robot. Stress analysis and simulation were carried out on the maximum load bearing point of the auxiliary hook and the walking wheel mechanical arm under different states, and the results showed that the hook and the robot arm could meet the requirements of the robot loading and unloading, and the whole robot loading and unloading system was designed reasonably. Compared with the traditional loading and unloading system designed in this paper, the loading and unloading efficiency could be improved. It has important theoretical significance for the development of the physical system of robot uplink and down.

Application of two-dimensional temperature response functions for reconstruction of divertor heat flux profile in commercial fusion reactors.

To keep the tritium breeding rate TBR > 1 and to meet the high heat load and neutron shielding requirements for the first wall and divertor in fusion demonstration (DEMO) reactors, the number of port plugs and other openings must be limited. To accomplish this, it is necessary to develop alternatives to the use of infrared (IR) thermography to determine the peak heat flux and the heat flux profile onto divertor targets. A divertor tile equipped with multiple temperature monitoring channels can be used to reproduce the temperature profile. To avoid the high temperatures and high neutron flux environment in a DEMO, the monitoring positions can be set well away from the irradiated surface. However, the spatial resolution of this method is lower than that provided by IR thermography. In the present work, we apply two-dimensional temperature response functions and the corresponding heat conduction model to temperature data obtained from a divertor tile surface in the large helical device to study the effects of the spatial resolution of the monitored temperature profile on the reconstructed heat flux profile. The findings provide information that will be useful in defining a method for embedding thermocouples into the divertor tiles of future DEMO reactors.

Pv Off Grid System with Improved Charge Controller Using Closed Loop Control

A photovoltaic (PV) off grid system is a cutting-edge energy system that harnesses solar power to provide reliable electricity to localized areas. This abstract focuses on enhancing the performance of PV standalone off grid systems through the implementation of an advanced charge controller employing closed-loop control strategies. These autonomous energy systems, powered by solar panels, offer a decentralized solution to electricity generation and distribution. Traditional charge controllers may not efficiently adapt to varying solar irradiance levels, leading to suboptimal energy harvesting. The closed-loop control system proposed in this work addresses the need for dynamically adjusting the charging algorithm in response to real-time environmental conditions, ensuring maximum energy captured from the PV system. The open circuit voltage algorithm plays a pivotal role in increasing the overall efficiency of the PV micro grid. By responding intelligently to changes in solar irradiance and load requirements, the system minimizes energy losses and maximizes the utilization of available renewable resources, thereby addressing the need for efficient energy management. The results obtained from MATLAB simulation are compared with other methods in terms of maximum power efficiency. The results suggest that the open circuit voltage algorithm is efficient.

Power Quality Conditioners-Based Fractional-Order PID Controllers Using Hybrid Jellyfish Search and Particle Swarm Algorithm for Power Quality Enhancement

Power quality (PQ) is a major issue in today’s electrical system that affects both utilities and customers. The proliferation of power electronics devices, smart grid technology, and renewable energy sources (RES) have all contributed to the emergence of PQ concerns in today’s power system. The Unified Power Quality Conditioner (UPQC) is a versatile tool that can be used to fix distribution grid issues caused by irregular voltage, current, or frequency. Several tuning parameters, however, restrict the effectiveness of the Fractional-Order Proportional Integral Derivative (FOPID) control technique, which is proposed to improve UPQC performance. To move beyond these restrictions and find the optimal solution for the FOPID controller problem, a hybrid optimization strategy called the Hybrid Jellyfish Search Optimizer and Particle Swarm Optimizer (HJSPSO) is employed. To meet the load requirement during PQ issue periods, the suggested model incorporates a renewable energy source into the grid system. Whether the load is linear or non-linear, the design maintains PQ problems to a minimum. Furthermore, the FOPID control technique is compared with other controllers. Results show that grid-connected RES systems using the proposed FOPID control approach for UPQC have fewer PQ problems. The presented UPQC with HJSPSO strategy significantly outperformed, with the shortest computing time of 127.474 s and an objective function value of 1.423.

Enhancing Power Quality with PDO-FOPID Controller in Unified Power Quality Conditioner for Grid-Connected Hybrid Renewables

Addressing the pressing research problem of power fluctuations and grid harmonics in the integration of renewable energy, our proposed control strategy utilizes the Prairie Dog Optimization Fractional Order Proportional Integral Derivative (PDO-FOPID) controller within a Unified Power Quality Conditioner (UPQC) system. This innovative approach is tailored to mitigate harmonics and meet load requirements in grid-connected hybrid renewables. The UPQC system is instrumental in regulating coupling point voltage, countering voltage and current harmonics to enhance overall power quality. The PDO-FOPID controller dynamically adapts control parameters to system dynamics and load changes, ensuring a stable power supply despite the variability of renewable sources. Simulations in MATLAB/ Simulink confirm its superiority over traditional control strategies, such as PI, sliding mode, and fuzzy control, in harmonics mitigation, load fulfilment, and power stability. By effectively addressing these challenges, our proposed solution not only contributes to resolving a critical research problem but also advances the seamless integration of Hybrid Renewable Energy Sources (HRES) into power systems, thereby enhancing overall grid performance and the efficacy of renewable energy integration.

Design, development and characterization of Blumlein Pulse Forming Line based pulsed power system for High Power Microwave source research

This paper describes a complete cycle of designing, developing, and characterising a Pulsed Power System (PPS) and generating microwaves using the relativistic source. For low impedance relativistic High Power Microwave (HPM) sources, Blumlein Pulse Forming Line (BPFL) based high voltage pulsed power systems are the most suited. An HPM source such as a virtual cathode oscillator (VIRCATOR) operating in nanosecond durations consists of a primary voltage source that charges a Marx pulse generator’s capacitor bank over a long time. The requirements of a diode load are met by compressing the output pulse width of a Marx generator by a BPFL. This article describes the novel design, construction and characterization of a circulating De-Ionized (DI) water insulated BPFL pulsed power system. A novel approach of insulating gas filled Marx generator of this class/rating is attempted. A pulse power system consisting of high pressure gas insulated Marx generator and circulating DI water-based BPFL was developed and experimented with the resistive load as well as HPM source. The PSPICE simulation of the Blumlein circuit for various load conditions is described. Criticalities in the design of end bushings are elaborated along with the development and testing of a compact BPFL-based pulsed power system.