System Electrical Efficiency Research Articles

New Hybrid Deep Neural Architectural Search-Based Ensemble Reinforcement Learning Strategy for Wind Power Forecasting

Wind power instability and inconsistency involve the reliability of renewable power energy, the safety of the transmission system, the electrical grid stability and the rapid developments of energy market. The study on wind power forecasting is quite important at this stage in order to facilitate maximum wind energy growth as well as better efficiency of electrical power systems. In this work, we propose a novel hybrid data driven model based on the concepts of deep learning-based convolutional-long short term memory (CLSTM), mutual information, evolutionary algorithm, neural architectural search procedure, and ensemble-based deep reinforcement learning (RL) strategies. We name this hybrid model as DOCREL. In the first step, the mutual information extracts the most effective characteristics from raw wind power time series datasets. Second, we develop an improved version of the evolutionary whale optimization algorithm in order to effectively optimize the architecture of the deep CLSTM models by performing the neural architectural search procedure. At the end, our proposed deep RL-based ensemble algorithm integrates the optimized deep learning models to achieve the lowest possible wind power forecasting errors for two wind power datasets. In comparison with fourteen state-of-the-art deep learning models, our proposed DOCREL algorithm represents an excellent performance seasonally for two different case studies.

Особенности построения современных систем автоматического резервирования мощности тяговых подстанций постоянного тока

The article presents the results of studies on improving the efficiency of electrical power redundancy systems in power supply systems of railway DC vehicles by improving the technological modes of traction substations. There are presented scientifically based technical solutions of the hardware, a control algorithm of the power reserve system for traction substations with two converter units and a methodology for selecting places for installing automatic power reserve systems to increase the efficiency of the power supply system for railway vehicles. Practical testing of the developed technical and technological solutions has shown the effectiveness of their use in operating conditions.

Retracted] Research on the Construction of Crossborder e‐Commerce Logistics Service System Based on Machine Learning Algorithms

Based on machine learning algorithms, this paper designs a crossborder e‐commerce logistics service system recommendation algorithm. First, we introduce the meaning of query recommendation, analyze the mechanism of e‐commerce platform shopping search, redesign the query recommendation process on this basis, establish a Markov decision process model for the problem, and solve the optimal recommendation strategy through deep machine learning algorithms. Second, we design a simple calculation example, use Python programming through a simulated shopping environment, give the solution process of the optimal recommendation strategy in the whole process, and prove the feasibility of the algorithm. The sentiment synthesis word vector is used as the input data structure of the text, the convolutional neural network model and the recurrent neural network model in machine learning are independently designed and constructed, and a shunt is proposed. The rule (shunt) realizes the operation of judging the data and inputting the two machine learning networks. The shunt fully realizes the combination of the advantages of the local feature characterization of the convolutional neural network and the timing characteristics of the recurrent neural network and achieves a more efficient and accurate electrical system. Finally, through simulation experiments, a series of data processing work such as data outlier cleaning, sliding window construction features of data variables, and training set and test set division are designed to convert regression prediction problems into classification problems to predict commodity demand. At the same time, it also compared the effect of the time series model, random forest model, GBDT, single Xgboost model, and the model used in this topic and analyzed the reasons for this difference and the application of each model.

Development of DSTATCOM Optimal Sizing and Location Technique Based on IA-GA for Power Loss Reduction and Voltage Profile Enhancement in an RDN

The efficiency of electrical distribution systems is being more affected by the increase in voltage drops and power losses. These issues of voltage drop and power loss can be significantly minimized by the incorporation of a Distribution Static Compensator (DSTATCOM) in the distribution network. However, inappropriate positioning and sizing of DSTATCOM can undermine its efficiency. Despite the contributions of many researchers to the optimal placement of DSTATCOM and other compensators in distribution networks, the problems of voltage drop, power losses, and power quality persist, necessitating the need for additional research in this area. In this paper, an innovative technique based on hybridized Immune and Genetic Algorithm (IA-GA) for optimal DSTATCOM placement and sizing for three distinct load levels is proposed. Simulation and analysis of the proposed algorithm were carried out using IEEE-33 bus radial distribution network (RDN) in MATLAB. The simulation results demonstrate a substantial decrease in power loss and a significant improvement in the voltage profile. Evaluation of the proposed method against existing techniques reveals that the proposed technique outperforms IA and PSO in terms of decreasing power loss and enhancement of voltage profiles. A cost-benefit analysis was performed, and it was discovered that the proposed technique yields improved annual cost savings.

An experimental study of the concentrator photovoltaic/thermoelectric generator performance using different passive cooling methods

Conducting an outdoor experimental investigation of a hybrid concentrator photovoltaics (CPV)/thermoelectric generators (TEG) system's performance is of great importance. It provides a reliable performance characteristic, as it is carried out under real solar spectral and atmospheric conditions. In the current work, a multi-junction solar cell subjected to a solar concentration ratio of 50 suns using different passive cooling methods has been investigated. To perform outdoor experiments, the solar cell integrated with a heat sink (HS) and a dual-axis elliptic solar tracker is used with a Fresnel lens-based concentrator. Several configurations are experimentally investigated including CPV-HS combined with a finned HS, TEG-HS, CPV-TEG-HS, and CPV-TEG-micro-channel heat pipe (MCHP)-HS. Results show a significant enhancement in the CPV-TEG-MCHP-HS power compared to alternate systems. At direct normal irradiance of 990 W/m2, the output power is about 1.14 Watt. However, the output power for CPV-HS, and CPV-TEG is about 1.1 W, and 1.05 W, respectively. The CPV cell and TEG areas were 1 cm2 and 16 cm2, respectively. In addition, the electrical efficiency of CPV system and CPV-TEG hybrid system is 26%, and 22.84%, respectively. However, the electrical efficiency of hybrid CPV/MCHP/TEG is 28.45%.

A novel multistage constant compressor speed control strategy of electric vehicle air conditioning system based on genetic algorithm

This study establishes a passenger cabin-coupled air conditioning model that the heat exchangers adopted in the air conditioning model, are calibrated by testing, during which the parameters for establishing the passenger cabin model are measured. The cabin temperature simulation results of the air conditioning model proposed in this paper fit well with the test results, with a maximum difference of 3 °C. A genetic algorithm (GA) optimization-based multistage constant-compressor speed (MCCS) air conditioning system control strategy is proposed. This control strategy sets the cabin temperature as the input control factor and the compressor speed as the output factor, and different cabin temperature ranges correspond to the MCCSs, which are optimized by the GA. The presented strategy is contrasted with the most commonly used on/off controllers and the proportional integral derivative (PID) controller, and an engineering-applied (EA) air conditioning control strategy. The proposed controller can maintain passenger cabin thermal comfort and save energy simultaneously, and it can be easily applied in engineering. Based on the simulation results, the MCCS controller can save 17.5, 7.5, and 5.8% more energy consumption than the on/off, PID, and EA controllers. Moreover, it can improve the coefficient of performance of the air conditioning system by 5.3 and 3.9% more than the PID and EA controllers. Therefore, the proposed MCCS controller can increase the operation efficiency of electric vehicles AC system.

For an efficient electric propulsion system, use iodine

For an efficient electric propulsion system, use iodine

Comparative study on dual-source direct-expansion heat pumps based on different composite concentrating photovoltaic/fin evaporators

Dislike the electrical performance, the heat collection capacity is always disappointing in the photovoltaic evaporators. It is always handled by adding additional finned-tube evaporators, which will increase space occupation and pipeline complexity. In this paper, a novel direct-expansion heat pump based on linear Fresnel photovoltaic/fin evaporator is designed. By integrating concentrating photovoltaic and fins into one composite photovoltaic-air evaporator, the above shortcomings can be solved and the solar & air energy can be fully utilized to maximize the output of the evaporator with a limited area. Compared with the direct-expansion heat pump with compound parabolic concentrator/fin evaporator, this system owns a higher concentration ratio, smaller photovoltaic area (making it possible to be equipped with GaAs cells), and larger finned-tube structure to enhance the heat capacity under the same receiving area. Dynamic models are established in MATLAB and comparative analysis is carried out under different wind speeds, irradiance, and ambient temperature. The influence of running time and the system performance with 40 °C water temperature (in actual application) are also discussed. The average electrical efficiency, COPPVT, and exergy efficiency of the heat pump system based on linear Fresnel photovoltaic/fin evaporator could be 28.21%, 3.55, and 27.07% under 900 W/m2, which are all higher than 16.02%, 3.15, and 20.09% in the system with compound parabolic concentrator/fin evaporator. Therefore, the newly designed system could enhance the performance of the hybrid system.

Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language

The problem of the optimal reactive power flow in transmission systems is addressed in this research from the point of view of combinatorial optimization. A discrete-continuous version of the Chu & Beasley genetic algorithm (CBGA) is proposed to model continuous variables such as voltage outputs in generators and reactive power injection in capacitor banks, as well as binary variables such as tap positions in transformers. The minimization of the total power losses is considered as the objective performance indicator. The main contribution in this research corresponds to the implementation of the CBGA in the DigSILENT Programming Language (DPL), which exploits the advantages of the power flow tool at a low computational effort. The solution of the optimal reactive power flow problem in power systems is a key task since the efficiency and secure operation of the whole electrical system depend on the adequate distribution of the reactive power in generators, transformers, shunt compensators, and transmission lines. To provide an efficient optimization tool for academics and power system operators, this paper selects the DigSILENT software, since this is widely used for power systems for industries and researchers. Numerical results in three IEEE test feeders composed of 6, 14, and 39 buses demonstrate the efficiency of the proposed CBGA in the DPL environment from DigSILENT to reduce the total grid power losses (between 21.17% to 37.62% of the benchmark case) considering four simulation scenarios regarding voltage regulation bounds and slack voltage outputs. In addition, the total processing times for the IEEE 6-, 14-, and 39-bus systems were 32.33 s, 49.45 s, and 138.88 s, which confirms the low computational effort of the optimization methods directly implemented in the DPL environment.

A SUPPLY AND DEMAND ANALYSIS FOR THE TURKISH ELECTRICITY MARKET: SUPPLY ADEQUACY AND RESOURCE UTILIZATION

Electricity is a critical commodity for which the demand should be met using reliable, cost-effective, and sustainable resources. The characteristics of supply and demand should be comparatively analyzed for efficient electric power system planning. This study examines Turkey's current electricity supply and demand and their characteristics for future balance. Turkey's installed capacity and electricity consumption per capita are analyzed using historical data, and trends for future electricity demand are estimated. Electricity supply based on generation sources is reviewed, and the historical contribution of each source to total generation is shown. Statistical distribution of electricity generation by generation types and their relationships are also investigated. As the supply adequacy should be carefully reviewed for sustainability, finally, the characteristics of supply are analyzed using capacity factors, reserve margins, capacity margins, load duration curves, and peak-to-average demand ratios. It is shown that although the margins are above comfortable levels after 2017, they still need to be increased as the increased use of renewables might require extra availability. The load duration curves and peak-to-average demand ratios have shown that the density of demand is increasing, and capacity needs to be expanded and utilized carefully in the future for the reliability of the power system.Keywords: Electricity Supply-Demand, Electricity Generation Sources, Consumption Trends, Capacity Factor, Reserve Margin, Load Duration CurveJEL Classifications: Q41, O13, L94DOI: https://doi.org/10.32479/ijeep.11412

NUMERICAL INVESTIGATION OF A SOLAR-DRIVEN ORGANIC RANKINE CYCLE COUPLED TO A GEOTHERMAL FIELD

The objective of this work is to investigate a solar-driven Organic Rankine Cycle (ORC) for power production with a geothermal well as the heat sink for the ORC condenser. The examined unit combines the exploitation of two renewable energy sources. Solar irradiation is exploited by using solar dish concentrators with spiral absorbers, while the geothermal field includes vertical boreholes with U-tubes. The system is investigated parametrically with a developed model in Engineering Equation Solver, and the examined parameters are the solar beam irradiation level, the total thermal conductivity of the ORC condenser, the borehole length, the number of the boreholes and the mean ground temperature. For the default scenario, it is found that system electrical efficiency is 21.45%, the ORC’s thermodynamic efficiency is 35.99%, and the solar field efficiency is 61.30%. Moreover, it is found that the examined system is 5.7% more efficient than a conventional air-cooled condenser system.

Perfecting the Operative Management of the Performance Efficiency of Electric Power System’s Unique Facilities

Perfecting the Operative Management of the Performance Efficiency of Electric Power System’s Unique Facilities

Development of Microcontroller Based Smart Grid Framework

Smart grid technology has been recognized as a promising solution for the next-generation energy efficient electric power systems to mitigate energy crisis. Smart grid provides highly consistent and reliable services, efficient energy management practices, smart metering integration, automation and precision decision support systems and self-healing facilities. The smart power grid introduces a sensing, monitoring, and control system that provides end users with the cost of energy at any moment through real-time pricing. The classical power system operation has no control over the loads except in an emergency situation when a portion of the loads can be dropped as needed to balance the power grid generation with its loads. Furthermore, the smart power grid supplies the platform for the use of renewable energy sources that acts as a safeguard against a complete blackout of the interconnected power grid. In this work, all the concepts involved in smart grid mechanism is implemented with PIC18F452 microcontroller and other supplementary components. A solar module with storage capacity is connected to the proposed system for minimizing grid energy consumption and plays a primary energy source for maximum utilization of green energy. This intelligent device may inherently reduce the consumption of electrical energy during peak hours and allow consumers to sell back electricity into grid using bi-directional technique. Barriers, challenges, benefits and future trends regarding the technologies and the role of users have also been discussed in this paper.

A novel Gamma‐type duplex Stirling system to convert heat energy to cooling power: Theoretical and experimental study

This article aims at coupling two Stirling machines together to produce cooling power from different heat sources. Two identical Gamma-type ST500 Stirling machines are coupled together. The first machine, named Stirling engine, is powered by burning natural gas and an electrical power supply as an auxiliary starter. The Stirling engine is connected to a second Stirling machine named Stirling refrigerator by a mechanical belt. The driving force is transferred to the Stirling refrigerator using the mechanical belt. Mechanical energy is then converted to cold energy in the Stirling refrigerator. This study presents the experimental and theoretical results by examining the whole system named duplex Stirling refrigerator system. Five experiments are performed on the system at different pressures to evaluate the results. Water circulation in copper coils is used to determine the cooling flux produced by the Stirling refrigerator. Finally, the coefficient of performance (COP) is calculated. The experimental data are validated using a MATLAB-based code developed based on the presented formulas in this study. The results show that the system's maximum COP and electrical efficiency, consisting of two similar 500 W Gamma-type Stirling machines, are between 0.21% and 70.8%, respectively. Setup theoretical and experimental efficiencies are 0.24 and 0.21, respectively, at the best case. The experimental results of the duplex Stirling refrigerator system used in this study are compared with the simulation results. Finally, the experimental results of this study are compared with some other reported results from different authors on the subject of the duplex Stirling refrigerator.

Design and performance analysis of a cascade solid oxide fuel cell system for high electrical efficiency

• Optimized design of the cascade solid oxide fuel cell system has been proposed. • Performance of cascade system has been compared other two types of systems. • Superiority of cascade system has been verified with various operating parameters. • Anode off-gas recirculation system has the highest stack electrical efficiency. • Cascade system has the highest system electrical efficiency except low external reforming ratio. To enhance the electrical efficiency of a solid oxide fuel cell system, a cascade system has been proposed. In the cascade system, two stacks are installed in series so that the second-stage stack utilizes the anode off-gas from the first-stage stack to increase the electrical efficiency of the system without an anode off-gas recirculation device. In this study, a mathematical model of the cascade system has been developed to achieve the system optimization. To confirm the superiority of the cascade system compared to the single-stage system and the anode off-gas recirculation system in terms of the system electrical efficiency, the effects of the operating parameters on the system efficiency has been analyzed, such as the current density, external reforming ratio, and steam-to-carbon ratio. The simulation results show that the cascade system has the highest system electrical efficiency among the three types systems, except for the low external reforming ratio of 30%. This study can provide the basic insight to establish the optimization for the cascade solid oxide fuel cell system.

Influence of glass cover on the characteristics of PV/trombe wall with BI-fluid cooling

A practical investigation was conducted to demonstrate the effect of a glass cover on the efficiency of the Photovoltaic/Trombe wall using Nano-fluid (water/Al2O3) as a coolant. Two concentrations of nan-particles (0.5% and 1%) were tested. Using the glass cover on the front of the modified Trombe wall causes an increase in the solar cell temperature, which decreases the system's electrical efficiency but increases the room temperature, leading to improved thermal system efficiency. The highest recorded thermal efficiency value was 80% when using glass cover and 0.5% Nano-fluid at 2 p.m. Moreover, the implementation of a Nano-fluid as a coolant was increased the electrical efficiency. The maximum electrical efficiency was 14% at 1 p.m. In the absence of the glass cover and by using 0.5% Nano-fluid as a coolant. In general, using low concentration Nano-particles with cooling water improves the system efficiency, and increasing the Nano-particles concentration causes a negative influence on the system performance. The maximum total efficiency was 88% at 2 p.m. for the operation conditions (with a glass cover and using 0.5% Nano-fluid at the discharge of 300 L daily).

Design and testing of concentrated photovoltaic arrays for retrofitting of solar thermal parabolic trough collectors

A new design and retrofit approach for a concentrated photovoltaic thermal (CPV-T) system based on a parabolic trough collector is presented. The design differs from previous hybrid architectures, employing a significantly simplified topology in order to reduce costs while keeping electrical efficiency high. To achieve this ambitious goal, the absorber tube of a conventional parabolic trough collector used in thermal systems is replaced by a newly developed hybrid absorber equipped with multi-junction solar cells. This offers the advantage that existing solar thermal parabolic trough facilities can be easily retrofitted, making the system scalable and cost-effective. A scaled prototype of the system was designed and tested in Graz, Austria. During on-sun tests an average electrical system efficiency of 26.8% with a simultaneous thermal efficiency of 48.8% was measured using a geometric concentration ratio of 150 (DNI based). This leads to an overall average system efficiency of 75.5%. Moreover, a solar cell peak efficiency of 30% was achieved, one of the highest measured solar-to-DC efficiencies for a parabolic trough-based solar collector. Special attention was paid to the temperature difference between the solar cells and the heat transfer fluid in order to ensure sufficient cooling of the cells and maximize thermal efficiency. The electrical, thermal and overall efficiencies at different heat transfer fluid temperatures were measured (17°C - 90°C) and their coefficients were derived. This work serves as an experimental proof-of-concept for the application of solar cells in parabolic trough collectors, thereby opening up new possibilities for cost reduction of CPV-T systems.

Distributed generation as a mechanism to improve the reliability and economic efficiency of electricity systems

The article assesses the application of distributed generation to meet the customer’s own needs for electricity and heat. Currently, the electric power industry is faced with many problems of functioning of electric power systems, which have a negative impact on the processes of transmission and distribution of electric energy to end users. These problems lead to decrease in reliability of power supply and economic efficiency of operation of enterprises. In order to solve the problems of increasing the reliability and economic efficiency of electric power systems the introduction of distributed generation is effective. The modes of electric power generation are considered. The paper also analyzes and identifies the features of the application of distributed generation to achieve the required indicators of reliability and economic efficiency of electric power systems.

Process simulation development of a clean waste-to-energy conversion power plant: Thermodynamic and environmental assessment

Waste-to-energy (WTE) conversion technologies for generating renewable energy and solving the environmental problems have an important role in the development of sustainable circular economy. This paper presents a novel high-efficiency WTE power plant using refuse-derived fuel (RDF) as feedstock by integrating torrefaction (T) pretreatment with plasma gasifier (PG), solid oxide fuel cell (SOFC), and combined heat and power (CHP) system. The combined impacts of torrefaction conditions (i.e. temperature and residence time) and steam-to-fuel (S/F) ratio on the energy and environmental performances of the proposed T-PG-SOFC-CHP power plant without CO2 capture (System I) is first evaluated. Results show that torrefaction of RDF prior to plasma gasification provides better syngas quality and therefore the system electrical efficiency (SEE) and CHP efficiency (CHPE) of System I can be markedly boosted compared to that of untreated RDF. However, the integration of torrefaction unit shows a negative effect on the energy return on investment (EROI) due to high energy demands for torrefaction and plasma gasification. Overall, the values of CHPE of System I range from 47.25% to 55.39% when the torrefaction temperatures of 200 and 250 °C are adopted. In contrast, the torrefaction of RDF at 300 °C is not a recommended condition for operation in the T-PG-SOFC-CHP power plant because of noticeably negative energy and environmental impacts. Moreover, to prevent the risk of carbon deposition on the SOFC anode, a recirculation ratio (RR) of the anode off-gas of 30% is required. Finally, the introduction of oxy-fuel combustion technology into the T-PG-SOFC-CHP system for CO2 capture (System II) allows to achieve a zero direct CO2 emission WTE power plant. However, this results in an energy penalty of about 5.40–6.77% associated with the CO2 capture and compression process.

Implications of passive energy efficiency measures on life cycle greenhouse gas emissions of high-rise residential building envelopes

The building industry has been developing measures for reducing operational emissions in the fight against climate change. Some of these well-intentioned measures may result in higher embodied emissions, potentially more than offsetting reductions achieved during operation. This research evaluates the effectiveness of different levels of application of five passive energy efficiency measures to reduce life cycle greenhouse gas (GHG) emissions in high-rise residential buildings in Toronto, Canada, while considering projected future climate and GHG intensity of energy sources. Through combining and automating life cycle assessment and energy simulation on a visual programing interface, the study evaluates 16,128 envelope variants, examining 56 wall, 12 roof, 6 window assemblies and 4 window-to-wall ratios (WWRs). Decreasing the WWR is found to be the most effective measure to reduce total envelope related GHG emissions (by about 28%). Increasing wall and roof insulation with GHG intensive materials (e.g., extruded polystyrene [XPS]), and increasing spandrel wall insulation potentially augment total emissions, depending on the scenario. Higher trade-offs between embodied and operational emissions are found when highly efficient electric HVAC systems are implemented (e.g., heat pumps). Results demonstrate it is imperative to assess both embodied and operational emissions during the design process of building envelopes to effectively reduce GHG emissions.