Electric Delivery Research Articles

Energy Consumption Optimization for an Electric Delivery Vehicle

For nearly two centuries, electric drives have been used in transportation. Nevertheless, they were not always favored by designers. The century-long dominance of heat engines led to the disregard of numerous challenges associated with the operation of electric drive systems. One of these issues is the optimization of energy consumption by an electric vehicle. This publication proposes an electronic Energy Consumption Optimizer (ECO) that predictively uses information about the shape of the route and speed limits on its individual sections to control the motor speed and gear changes in the gearbox. This work presents the structure of the optimizer system and the developed control algorithms. Additionally, electric motor excitation control was used, which may have contributed to reducing the power and weight of the electric drive motor. Simulation studies carried out using WLTP test cycles and cycles from real road routes showed the potential to decrease energy consumption for vehicle movement by approximately 10%.

Enhancing Smart Grid Stability through a Hybrid Biometric Pattern Recognition and Long Short-Term Memory Approach

The stability of power grids is critical in ensuring the consistent and efficient delivery of electricity. However, traditional predictive models often fall short in addressing grid data's intricate and ever-changing nature, making it challenging to maintain grid reliability. This paper introduces a novel hybrid approach that combines Biometric Pattern Recognition (BPR) with Long Short-Term Memory (LSTM) networks to enhance the prediction of smart grid stability. This approach employs BPR techniques to extract essential features from smart grid data by leveraging the pattern recognition capabilities typically used in biometric systems. These techniques are particularly effective in identifying and isolating the most relevant patterns within the complex datasets generated by smart grids. On the other hand, the LSTM-based model is designed to handle the temporal dependencies and nonlinear patterns characteristic of grid data. LSTMs, known for their proficiency in time-series analysis, are well-suited for capturing the sequential nature of grid data, enabling more accurate predictions over time. Integrating BPR and LSTM in this hybrid model addresses several limitations in existing predictive methods. By combining the strengths of both techniques, the model enhances the accuracy of predictions and improves the overall reliability of grid stability assessments. Extensive experiments were conducted using real-world datasets to validate the effectiveness of the proposed hybrid model. The results demonstrate a significant improvement in prediction accuracy, with the BPR-LSTM model achieving a 98.25% increase in accuracy compared to traditional prediction methods. This improvement underscores the potential of the BPR-LSTM hybrid approach to play a pivotal role in advancing the stability and reliability of smart grid systems.

Electric delivery vehicle routing problem optimization model with time-varying traffic congestion

In order to plan a reasonable scheme for the fleet travel and minimize the energy consumption of electric vehicles during traffic congestion periods, while relieving the mileage anxiety of delivery personnel, the pure electric delivery vehicle routing problem considering time-varying traffic congestion was studied. Firstly , a novel mixed integer programming model (TD-EVRP) is established to step for its extended model of EVRP, which especially characterizes the time-varying traffic congestion state and measures the energy consumption of electric delivery vehicles. This model also refines its constraints including customer time window, vehicle load, and vehicle charging requirements. Secondly, a traffic congestion avoidance strategy is introduced into the model, which allows vehicles to park and charge at customer points during peak traffic periods in order to actively avoid unnecessary energy consumption caused by traffic congestion. Finally, the improved ant colony algorithm is designed to acquire the optimal solution.

Evaluation of the Physical and Chemical Properties of a Number of Aquarium Waters in Kirkuk Governorate and Determination of Bacterial Content of Pond Water

This study aimed to evaluate the fish ponds in the outskirts of Kirkuk, starting from the Hawija district, Daqouq, Lylan, Yayji and Taza, and the tests were conducted in the Department of Environment and Agriculture and included water samples of carb fish ponds. The physical, chemical and biological traits were measured for January 2024. The temperature recorded the highest value of 40 m in September in the first station. The highest value of electrical delivery was recorded in the September at the fifth station, as it amounted to 3.227 microscopes/cm and the lowest value of 0.477 microscopes/cm per month in the fourth station, and the results showed the high values of electrical conductivity at the fifth station in all study months. As for the values of the total soluble solid materials at the five study stations, the highest value of 1860 mg/l in November was recorded in the fourth station and the lowest value in the same station was recorded in August, the results showed the high values of the total solid materials in the fifth station in all months of the study. As for the values of Akkara, it ranged between 111-0.833 mg/l, and the highest value of 111 mg/l was recorded in the month of August in the fourth station and the lowest value of 0.833 mg/l in November in the first station, and it was noted through the table the high values The second in all months of the study, and the values of the pH in fish ponds ranged between 6.4-7.4, meaning that the water in the fish ponds tends to be a little alkaline, as the fifth station in the month of August was registered with the highest values of hydrogen, 7.4, and the value was recorded at the second station 6.4.

Unveiling electric vehicle (EV) charging patterns and their transformative role in electricity balancing and delivery: Insights from real-world data in Sweden

Accurately estimating the charging behaviours of electric vehicles (EVs) is crucial for various applications, such as charging station planning and grid impact estimation. However, the analysis of EV charging behaviours using real-world data remains limited due to (confidential) data availability constraints. Furthermore, while existing modelling studies have demonstrated EVs as effective tools for electricity balancing and delivery between locations, their potential remains unexplored empirically. This study aims to bridge the research gap by studying EV charging behaviours and their capacity for electricity balancing and delivery. Using data from 179,665 real-world charging sessions in Sweden, we employed statistical and clustering analysis to scrutinize charging behaviours comprehensively. Synthetic weekly charging load profiles are generated for both residential areas and workplaces, considering varying charging power levels, which can be used as inputs for large-scale EV charging load modelling. Furthermore, performance indicators are proposed to quantify the potential of EVs for electricity balancing and delivery. Results show that EVs exhibit significant potential for electricity balancing (up to 51.5 kWh daily). Many EV owners underutilize their EV battery capacity, providing an opportunity for active electricity delivery across locations. This study can help understand EV charging behaviours and recognize their significant potentials for electricity regulation and integrating more renewables in the future power system.

Environmental performance of a multi-energy liquid air energy storage (LAES) system in cogeneration asset – A life cycle assessment-based comparison with lithium ion (Li-ion) battery

Increase in energy demand is shaping both developed and developing countries globally. As a result, the endeavour to reduce carbon emissions also encompasses electrical energy storage systems to ensure environmentally friendly power production and distribution. Currently, the scientific community is actively exploring and developing new storage technologies for this purpose. The focus of this work is to compare the eco-friendliness of a relatively novel technology such as liquid air energy storage (LAES) with an established storage solution such as Li-Ion battery (Li-ion). The comparison is carried out through Life Cycle Assessment (LCA) methodology which aims to assess the environmental impacts from each life stage, according to different impact categories. In particular, the study refers to the unitary storage and the delivery of electricity as well as cooling energy, considering all the inefficiencies and limits of each technology. The results show that in the full electric case study Li-ion battery environmentally outperform LAES due to (1) the higher round trip efficiency and (2) the significantly high environmental impact of the diathermic oil utilized by LAES, accounting for 92 % of the manufacture and disposal phase. Conversely, the cogeneration case study highlights that the “flexibility” and “dualism” of LAES, capable to efficiently deliver both electricity and cooling, offset the impact related to the higher electricity consumption during the use phase. Notably in energy mix frameworks with high share of primary energy source from fossil fuels, cogenerative LAES demonstrates superior environmental performance compared to Li-ion battery (i.e. 1302 kgCO2eq/MWhe vs 1140 kgCO2eq/MWhe for Singapore energy mix), attributable to its reduced electricity consumption.

Comparison Between Maintenance of Distribution Substations Using the Mobile Substation Unit (UGB) Method and Maintenance of Blackout Distribution Substations regarding Energy Not Served (ENS) which is not distributed to PLN UP3 Serpong

Electricity has become an important part of human life along with technological developments in this modern era. Economic progress, quality of life and the business world are very dependent on the electricity supply supplied by PT. PLN (Persero) UP3 Serpong. Electric power distribution is the final stage in the electric power delivery process. This is the process of distributing electric power from the electricity transmission system to electricity consumers. One of the main components in the electric power distribution system is the distribution substation. A distribution substation is an electrical installation device which contains disconnecting, connecting, safety and distribution transformer equipment to distribute electrical power according to consumer needs. Maintenance at distribution substations is carried out to support services to electricity consumers so that the substation equipment used is in reliable condition. and guaranteed continuity. Regular maintenance on distribution substations is important so that distribution substations do not experience damage and disruption while operating.

Design-Optimization of Solar-Collector Tilt Angle for Annual-Maximum and Seasonal-Balanced Energy Received

Abstract A detailed research study was performed on the annual energy received by a fixed-tilt solar collector. A new clear-sky model of solar radiation was developed by combining existing clear-sky models. Then, this model, was used to perform optimizations with two different objectives. The first objective is to achieve the maximum-annual solar energy received by a solar panel, while the second is to balance its energy received so that it is more uniform over the course of a year. Each of these objectives have differing optimum tilt values, depending on the location and usage of a solar receiver system. The novelty of this investigation is the use of the aforementioned solar model with a unique algorithm for multiple optimizations for these two different objectives, which results in two different optimum tilt angles that are in turn different from the widely accepted rule-of-thumb that recommends an angle that is equal to the latitude. The solar radiation results obtained with the model used herein were experimentally confirmed through comparison with measured weather data for a number of locations with different sky clearness indexes as well as comparison with those of other studies found in the literature. A major contribution of this study are the plots and tables showing optimum tilt angles as estimated by the model as well as with empirical data. By selecting the appropriate tilt angle, a designer can now decide to either maximize annual electrical energy production or else to balance delivery of electricity over the year.

Carbon reduction effects of electric delivery vehicle adoption in Chinese cities: Gradient pattern and scenario analysis

China's carbon peak and neutrality targets pose major challenges for the transportation sector due to its significant contribution to carbon emissions. The analysis of the penetration process and impact of electric delivery vehicles (EDVs) in the urban delivery industry (UDI) is relatively poor compared with electric passenger vehicles. This study conducts a scenario analysis of the electrification process and carbon impact of delivery vehicles (DVs) in Chinese cities based on current data and policies. In the baseline scenario, the stock of urban DVs is predicted to reach 22.4 million in 2035, while the stock of EDVs will reach 7.8 million, representing 35 % of the total. Carbon emissions from DVs will decline from a peak of 120.5 Mt in 2022 to 101.4 Mt in 2035 due to the penetration of EDVs. The high electrification rate (HER) scenario will result in an additional 10 Mt of carbon emissions reduction in 2035 as 45 % of DVs are electric. Furthermore, the impact of electrification on carbon emissions shows a spatial gradient due to city size and local policies. With a better understanding of EDV adoption and energy-related carbon emissions in Chinese cities, suggestions are proposed to promote low-carbon transition of UDI in different types of cities.

Enhancing Electric Field Distribution in the Pancreas for Improved TTFields Therapy: A Computational Modeling Investigation.

Tumor treating fields (TTFields) therapy has shown effectiveness in glioblastoma treatment and holds potential for other cancers. However, its application in pancreatic cancer and the distribution of electric fields in pancreas remain unexplored. This study aims to investigate the electric field distributions in pancreatic regions using different array configurations for TTFields therapy. Computational modelling was employed to simulate electric field distributions, and quantitative analysis was conducted. Human body impedance measurements were used to optimize the electric properties of the model. Various array configurations were examined to assess their impact on the electric field distributions. The study revealed that well-positioned arrays, specifically the combination of 20-piece transducer arrays in anterior-posterior orientation and 13-piece transducer arrays in left-right orientation, consistently achieved electric fields exceeding the 1V/cm threshold in over 99.4% of the pancreas. Even with a reduced number of transducers (13 pieces for both orientations), sufficient electric field coverage was achieved, exceeding the threshold in over 92.9% of the pancreas. Additionally, different array placements within the same orientation were explored to address clinical challenges such as skin rash and patient anatomical variations. This research lays the groundwork for understanding TTFields distribution within the abdomen, offering insights into optimizing array configurations for improved electric field delivery. The findings have the potential to guide practical designs of TTFields devices, enhance treatment efficacy, and improve patient outcomes. These results offer promises of advancing TTFields therapy for pancreatic cancer towards clinical applications, and potentially enhancing treatment efficacy and patient outcomes.

Determining Fault Location in Transmission Lines Using Differential Equation Algorithms

A transmission line, in the context of electrical engineering and power systems, is a high-voltage or high-tension line that is used to transmit electrical power over long distances from power generation sources (such as power plants) to substations, where the electricity is then distributed to homes, businesses, and industrial facilities. Transmission lines are the backbone of the electrical grid, serving as the highways for electricity delivery. Their efficient and reliable operation is essential for ensuring that electricity is generated, transmitted, and distributed effectively, meeting the needs of consumers while maintaining grid stability and resilience. Transmission line protection refers to a set of techniques and devices used in electrical power systems to detect and respond to faults or abnormal conditions that can occur in high-voltage transmission lines. These lines are a critical part of the electrical grid and are responsible for transporting electricity over long distances from power generation plants to distribution substations. This paper proposes a different differential equation algorithm to locate faulty section on transmission lines. As seen from performance curves, the proposed protection algorithm is able to distinguish normal and faulty conditions.

Solving low-carbon last mile delivery problem using discrete marine predators algorithm

With the increasing concentration of greenhouse gases, carbon peaking and carbon neutrality have gradually become a global issue. As the last link of e-commerce logistics, the last mile delivery should not only focus on customer satisfaction and enterprise cost, but also reduce carbon emission and promote green development. In order to solve the last mile delivery problem, this paper builds the last mile delivery model for two common delivery vehicles, considering the impact of transportation cost, carbon emission and customer satisfaction on the last mile delivery path planning. The last mile delivery is an NP-hard problem, a novel Discrete Marine Predators Algorithm(DMPA) is proposed to solve the problem, which combines neighborhood search strategy and RS hybrid operator. Six different test examples are generated based on Solomon for simulation experiments, and the experimental results verify that the proposed algorithm is obviously superior to the marine predators algorithm, simulated annealing algorithm and genetic algorithm. DMPA obtains significantly higher customer satisfaction than other algorithms. The customer satisfaction of C101 and C201 is as high as 0.99, which is close to the optimal value of 1. DMPA can achieve lower transportation costs and less carbon emissions compared with other algorithms. DMPA reduces the transportation cost by at least 61.12$ and the carbon emission by at least 1033.64 kg for C101 by minivan delivery. DMPA reduces the transportation cost by at least 28.89$ and the carbon emission by at least 210.9 kg for C101 by electric tricycle delivery. It can effectively reduce carbon emission, lower transportation cost, improve service level, and promote the integration of the dual carbon target with the internal requirements of national development.

Gene Electrotransfer via Conductivity-Clamped Electric Field Focusing Pivots Sensori-Motor DNA Therapeutics: "A Spoonful of Sugar Helps the Medicine Go Down".

Viral vectors and lipofection-based gene therapies have dispersion-dependent transduction/transfection profiles that thwart precise targeting. The study describes the development of focused close-field gene electrotransfer (GET) technology, refining spatial control of gene expression. Integration of fluidics for precise delivery of "naked" plasmid deoxyribonucleic acid (DNA)in sucrose carrier within the focused electric field enables negative biasing of near-field conductivity ("conductivity-clamping"-CC), increasing the efficiency of plasma membrane molecular translocation. This enables titratable gene delivery with unprecedently low charge transfer. The clinic-ready bionics-derived CC-GET device achieved neurotrophin-encoding miniplasmid DNA delivery to the cochlea to promote auditory nerve regeneration; validated in deafened guinea pig and cat models, leading to improved central auditory tuning with bionics-based hearing. The performance of CC-GET is evaluated in the brain, an organ problematic for pulsed electric field-based plasmid DNA delivery, due to high required currents causing Joule-heating and damaging electroporation. Here CC-GET enables safe precision targeting of gene expression. In the guinea pig, reporter expression is enabled in physiologically critical brainstem regions, and in the striatum (globus pallidus region) delivery of a red-shifted channelrhodopsin and a genetically-encoded Ca2+sensor, achieved photoactivated neuromodulation relevant to the treatment of Parkinson's Disease and other focal brain disorders.

Energy Consumption and Saved Emissions of a Hydrogen Power System for Ultralight Aviation: A Case Study

The growing concern about climate change and the contemporary increase in mobility requirements call for faster, cheaper, safer, and cleaner means of transportation. The retrofitting of fossil-fueled piston engine ultralight aerial vehicles to hydrogen power systems is an option recently proposed in this direction. The goal of this investigation is a comparative analysis of the environmental impact of conventional and hydrogen-based propulsive systems. As a case study, a hybrid electric configuration consisting of a fuel cell with a nominal power of about 30 kW, a 6 kWh LFP battery, and a pressurized hydrogen vessel is proposed to replace a piston prop configuration for an ultralight aerial vehicle. Both power systems are modeled with a backward approach that allows the efficiency of the main components to be evaluated based on the load and altitude at every moment of the flight with a time step of 1 s. A typical 90 min flight mission is considered for the comparative analysis, which is performed in terms of direct and indirect emissions of carbon dioxide, water, and pollutant substances. For the hydrogen-based configuration, two possible strategies are adopted for the use of the battery: charge sustaining and charge depleting. Moreover, the effect of the altitude on the parasitic power of the fuel cell compressor and, consequently, on the net efficiency of the fuel cell system is taken into account. The results showed that even if the use of hydrogen confines the direct environmental impact to the emission of water (in a similar quantity to the fossil fuel case), the indirect emissions associated with the production, transportation, and delivery of hydrogen and electricity compromise the desired achievement of pollutant-free propulsion in terms of equivalent emissions of CO2 and VOCs if hydrogen is obtained from natural gas reforming. However, in the case of green hydrogen from electrolysis with wind energy, the total (direct and indirect) emissions of CO2 can be reduced up to 1/5 of the fossil fuel case. The proposed configuration has the additional advantage of eliminating the problem of lead, which is used as an additive in the AVGAS 100LL.

A techno-economic framework for optimizing multi-area power dispatch in microgrids with tie-line constraints

Fuel-fired power plants are the primary electricity sources in Saudi Arabia. This investigation aims to reduce the overall costs and emissions of electricity production from thermal units operated by the Shuqaiq Water and Electricity Company. It also considers practical thermoelectric constraints, such as power losses, ramp-rate constraints, and environmental optimization functions, to align with the sustainability goals of Saudi Vision 2030. Optimizing electric energy delivery is crucial within an energy control center. The focus of this work is to develop an advanced computational technique that reduces reliance on fossil fuels and minimizes the production cost of electricity, while also considering environmental emissions as an optimization function. An examination was conducted through two distinct practical case studies with power demand of 850 MW—one involving renewable sources and the other without—to assess the effectiveness of the hybrid crow search and JAYA optimization algorithm in optimizing performance. This system includes a multi-area setup with limitations on the tie-line power flow constraints. Additionally, the study also involved RETScreen modelling to assess the practical financial, emission, and benchmark analysis of a proposed integrated solar plant. This analyses offers a thorough assessment of the facility’s performance and reliability in practical situations. This study serves as a motivating factor for energy operators, stakeholders, governmental organizations, and grid administrators to invest resources in environmentally-friendly initiatives. The simulation results showed that the proposed approach successfully reduced the electricity cost by 2.29% and 3.70% in hybrid energy networks while effectively handling the system constraints. In addition, the analysis revealed that the optimization algorithm effectively decreased toxic emissions from power plants while also supporting the sustainability objectives of United Nations SDG-7 and Saudi Vision 2030 through the successful integration of renewable sources.

Transient stability investigation of a grid integrating solar and wind energies: a case study of southern Algeria

The primary goal of electricity producers is to ensure the efficient operation of the electrical grid and the reliable delivery of electricity to individual households. Strengthening the electricity network with the integration of micro-power plants such as wind farms and photovoltaic power plants, as in the case of Algeria, contributes to improving the quality of electricity supplied to consumers. This work presents a simulation study of the electrical network of the Adrar region using ETAP program, to show the influence of the insertion of photovoltaic and wind power plants on the electrical network. The results showed good tolerance of the grid to the integration of wind energy, while the integration of photovoltaic energy needs more requirements and technical challenges to overcome, because, as shown by the results of simulations, the integration of photovoltaic energy makes the network more vulnerable to disturbances. The primary reason for this phenomenon is the lack of mechanical inertia, enabling the system to minimize perturbations. Where wind turbines are unique in their ability to withstand load variations and respond quickly to disruptions. They return to their initial value in 20 seconds, while solar power systems signal return to their initial value after 45 seconds due to their lack of mechanical inertia. Owing to the limitations of the electrical network, the majority of test scenarios demonstrate that wind farm structures can sustain a steady voltage and frequency of 50 Hz. On the other hand, there are momentary fluctuations in voltage and frequency in structures that have photovoltaic systems installed.

Analysis of the pressure drop of sulfur hexafluoride (sf6) gas in a circuit breaker 150 KV Siemens 3AQ1EG

Abstract. The development of technology in the current era is very rapid and has an impact on increasing electrical energy which is a major need for large industries and households. One of the electrical energy delivery equipment in the transmission system is a PMT or High Connection Breaker. This PMT is a mechanical equipment equipped with sulfur hexafluoride (SF6) gas arc extinguishing media. The process of extinguishing the arc occurs due to contact due to work from the movement that causes the contact to cause an arc. This decrease in SF6 gas pressure greatly affects reliability when operating, because the arc extinguishing process is not perfect. This is determined by the age of the equipment and the number of operating breakers. The results showed that SF6 gas which is in accordance with the standard normal pressure of 6.4 bar with an ambient temperature of 34°C can minimize the occurrence of equipment damage because it is able to approach arc pressure with SF6 gas velocity of 58 cm/s.kA, with a contact gap of 3,61224. cm, while the PMT cannot be operated at a pressure of 5.2 bar with an ambient temperature of 34°C because the speed of SF6 gas is 82 cm/s.kA with a contact gap of 5.10696. It is concluded that the higher the pressure affects the speed and distance when extinguishing the arc. several factors that affect the decrease in SF6 gas pressure using the FMEA method based on the highest value of the Risk Priority Number (RPN) of 810. Keywords: fire arc, Breakdown, Voltage breaker, SF6 . gas pressure

СУЧАСНІ ТЕНДЕНЦІЇ РОЗВИТКУ СИСТЕМ КОМПЕНСАЦІЇ РЕАКТИВНОЇ ПОТУЖНОСТІ

This paper surveys current trends and developments in reactive power compensation systems, elucidating their significance in enhancing system capacity and flexibility. By analyzing the capacity factor enhancement enabled by reactive power compensation, the study underscores its role in optimizing electricity delivery, thus conserving energy resources and facilitating the integration of renewable energy sources. It explores the key models and concepts driving advancements in reactive power compensation within power grids. As modern electrical systems grow in complexity, ongoing research into improving compensation methods becomes imperative to ensure the reliability and efficiency of industrial power grids. Future endeavors will involve developing a model utilizing real-world enterprise data to investigate the effects of technological variations in filter parameters on the performance of complex reactive power compensation schemes, encompassing both filters and capacitor banks. Keywords: reactive power, compensation systems, filter-compensating circuit, industrial power grid, electric power. Context. The paper considers the current trends used in the field of reactive power compensation, and the main directions of development of modern methods of reactive power compensation. Objective. The purpose of the work is to overview of current trends in the development of reactive power compensation systems, as well as an overview of possible ways of their effective application in various industrial networks. Methods. The paper presents a key aspect of reactive power compensation is its ability to increase system capacity and flexibility. By improving the capacity factor, utilities can deliver electricity more efficiently, reducing the need for excess capacity and thus conserving energy resources. In addition, this process plays an important role in supporting the integration of renewable energy sources such as wind and solar power, which often introduce volatility into electricity generation schemes. Results. The paper presents the main models and concepts in the field of reactive power compensation in power grids. Conclusions. Given the growing complexity of modern electrical systems, it is important to continue research into improving methods and means of reactive power compensation to ensure the reliability and efficiency of industrial power grids. In further research, it is planned to develop a model using a real enterprise as an example and investigate the impact of technological deviations of filter parameters on the steady-state and transient performance of complex reactive power compensation schemes, including not only filters but also capacitor banks.

Embedded Real-Swarm Evolutionary Programming Technique for Intelligent Load Curtailment Strategy

Some traditional optimization techniques are inaccurate and failed to reach their optimal solutions since the solutions normally stuck at local optimal. Thus, any optimization technique cannot be generalized as a reliable optimizer since some optimization techniques are unique to solve optimization problems. This may also occur in power system optimization problem. Load curtailment is one of the important issues in power systems since its approach can help control the power system loss. In general, it is termed as loss minimization so that the delivery of electricity to the consumers can be smoothened. This paper proposes a new optimization technique, Embedded Real Swarm Evolutionary Programming (ERSEP) for identify contingencies occurrence in power system. ERSEP is the integration of real mutation swarm operator with the traditional evolutionary programming (EP) which aims to produce better results in terms of achieving lower optimal solution. Comparative studies were conducted to observe the advantages of ERSEP over the traditional. Results exhibited that the proposed ERSEP outperformed the traditional EP in achieving lower optimal solution validated on IEEE 30-Bus Reliability Test System (RTS). Significant results deduced from this study revealed that total transmission loss reduction worth 52.83% was achieved by EP, 54.09% solved by PSO and 74.09% by ERSEP in Case 1 for chosen load condition. In Case 2, ERSEP maintains to achieve the highest loss reduction worth 54.97%, while EP achieved 51.03% and PSO achieved 52.98% loss reduction. ERSEP maintains to achieve highest loss reduction worth 61.63%, while EP achieved 51.03% and PSO achieved 52.98% loss reduction. This implies that ERSEP is superior in all cases to reach the lowest minimized transmission loss.

An efficient energy management strategy based on heuristic dynamic programming specialized for hybrid electric unmanned delivery aerial vehicles

Large-sized unmanned delivery aerial vehicles (UDAVs) stand out as prominent vertical take-off and landing aircraft, benefiting from integrating a hybrid electric propulsion system (HEPS) to enhance the power-to-weight ratio. Despite this advancement, UDAVs encounter challenges regarding range limitations and the need for swift computational solutions. Addressing these issues necessitates a computationally efficient energy management strategy (EMS) that optimizes power distribution to properly plan engine working points, ultimately aimed at enhancing fuel economy to increase flight range. This study proposes a heuristic dynamic programming (HDP)-based EMS tailored for the HEPS of a large-sized UDAV. In this strategy, the HDP framework is adopted to improve computational efficiency by iteratively updating control variables. To account for the specific flight characteristics, a flight state identifier incorporating selected flight command flags applicable to UDAVs is designed. This identifier aids in predicting velocity changes for different flight states by amalgamating corresponding prediction networks into an integrated velocity prediction network (IVPN). Substituting the model network with IVPN in the HDP framework significantly enhances prediction accuracy and guides power distribution towards optimal results, signifying an efficient EMS specialized for UDAVs. The proposed strategy is evaluated against baseline strategies in designed flight scenarios, highlighting a remarkable 51.37% improvement in prediction accuracy, a noteworthy 6.04% reduction in equivalent fuel consumption, and an impressive 95.81% reduction in global computation time. Finally, the actual applicability of the proposed strategy is validated in a hardware-in-loop test. Consequently, the proposed strategy can provide theoretical support for the efficient energy management of diverse large-sized UDAVs.