Model Of Electric System Research Articles

A deep reinforcement learning approach to energy management control with connected information for hybrid electric vehicles

Considering the importance of the energy management strategy for hybrid electric vehicles, this paper is aiming at addressing the energy optimization control issue using reinforcement learning algorithms. Firstly, this paper establishes a hybrid electric vehicle power system model. Secondly, a hierarchical energy optimization control architecture based on networked information is designed, and a traffic signal timing model is used for vehicle target speed range planning in the upper system. More specifically, the optimal vehicle speed is optimized by a model predictive control algorithm. Thirdly, a mathematical model of vehicle speed variation in connected and unconnected states is established to analyze the effect of vehicle speed planning on fuel economy. Finally, three learning-based energy optimization control strategies, namely Q-learning, deep Q network (DQN), and deep deterministic policy gradient (DDPG) algorithms, are designed under the hierarchical energy optimization control architecture. It is shown that the Q-learning algorithm is able to optimize energy control; however, the agent will meet the ”dimension disaster” once it faces a high-dimensional state space issue. Then, a DQN control strategy is introduced to address the problem. Due to the limitation of the discrete output of DQN, the DDPG algorithm is put forward to achieve continuous action control. In the simulation, the superiority of the DDPG algorithm over Q-learning and DQN algorithms in hybrid electric vehicles is illustrated in terms of its robustness and faster convergence for better energy management purposes.

Hindcasting to inform the development of bottom-up electricity system models: The cases of endogenous demand and technology learning

Bottom-up, technology-rich electricity system models are commonly used to generate scenarios for policy support at a national or global level. In literature, previous hindcasting studies (also called retrospective modeling or ex-post modeling) evaluated existing models rather than sought to inform model development from the beginning. In this study, we present a hindcasting exercise with D-EXPANSE model for national electricity systems in 31 European countries over the 1990–2019 period. We develop several model versions with or without elastic electricity demand and with or without endogenous technology learning, and use hindcasting to choose the most accurate configuration of the bottom-up model. The hindcasting results show that a model with endogenous elastic demand can capture well the real-world evolution of electricity demand, if elasticity factor is chosen well and if the countries did not undergo severe structural changes. Endogenous technology learning, however, increases the uptake of new emerging technologies in cost-optimal scenarios, but still cannot fully capture the real-world dynamics and at times even introduces further inaccuracies.

Modeling the transition to a zero emission energy system: A cross-sectoral review of building, transportation, and electricity system models in Canada

Models have long been effective tools in the planning and policy making of energy systems, but low-carbon electrification—decarbonizing generation supply while expanding electrical demand—poses new challenges for the modeling community. At its core, electrification relies on integrating insights that span the supply and demand side of power systems, resolving operational characteristics and long-term climate change, and the integration of previously independent engineered systems. However, our modeling landscape consists of a suite of models that focus on distinct sectors (power, buildings, transport) and spatial–temporal scales (municipal, provincial, federal). This paper probes whether the existing suite of energy system models, which span sectors, disciplines, and jurisdictions, is up to the task of charting net-zero pathways, specifically in the Canadian context. To do so, we analyze an inventory of energy system models that are being used in practice using a recently assembled model database. Next, we supplement our analysis with a web-based search and literature review. For each model category, we describe the key modeling approaches, strengths and weaknesses, and typical ways and areas in which these models are applied. We find that by focusing on a specific scale and sector, these models by their very definition, omit out-of-scope interactions leaving critical information gaps. Many of the most imperative areas for future research straddle multiple sectors or multiple scales—electric vehicle charging, carbon policy coordination, regional electricity trading, to name a few. Future research should focus on identifying ways in which different models could be used together to produce policy-related conclusions that are as detailed but more holistic than conclusions that can be gleaned from an individual model.

Ensuring energy balance for sudden demand changes in smart grids

With the increasing diversity in the use of electrical energy and the inclusion of renewable electricity power plants in the system, more efficient and more controllable electrical power systems are provided by smart grid technologies. Load balance based on pricing in electrical power systems; It is a strategy that takes into account customer demands, enables customers to use electrical energy at the most attractive price, and provides suppliers with the desired profit, that is, in summary, it coordinates the efficient operation of energy systems. In this study; While load balance is created with smart grid technology, demand-supply-price balance is achieved by using an optimum Fuzzy Logic PI controller within a closed-loop electric power control system model. Within the scope of the study, the simulation results obtained by applying 6 different demand scenarios to the power system model consisting of different types of generation resources were given graphically and analyzed. The different demand scenarios applied include difficult demand conditions such as possible sudden increase or decreases in demand in the electrical power system.

Cascaded fast terminal sliding mode control for UAV electric braking system

The anti-skid braking system of unmanned aerial vehicle has the characteristics of high-order nonlinearity, strong coupling, and time-varying parameters, which will seriously affect the taxiing performance of the unmanned aerial vehicle. This paper proposed a cascaded fast terminal sliding mode control method for unmanned aerial vehicle electric braking system, which can accurately track the optimal slip rate and ensure the stability of the braking system. First, the electric braking system model of unmanned aerial vehicle is established, which gets rid of the reliance on the ground binding coefficient fitting formulas. Second, combined with the concept of the inversion control, the cascaded fast terminal sliding mode controller is designed to achieve the accurate tracking of the slip rate and the reference braking force. The stability of the controller is proved by the Lyapunov stability theory. Finally, the effectiveness of the proposed control strategy is verified by simulation results.

RETRACTED: Risk-involved modeling of electrical and thermal energy storage systems in smart apartment building utilizing downside risk constraints approach

RETRACTED: Risk-involved modeling of electrical and thermal energy storage systems in smart apartment building utilizing downside risk constraints approach

Fault Alarms and Power Performance in Hybrid Electric Vehicles Based on Hydraulic Technology

In order to improve the fault alarm effect on the power performance of hydraulic hybrid electric vehicles (HEV), this paper proposes a fault alarm method for hybrid electric vehicle power performance based on hydraulic technology, builds a hybrid electric vehicle power system model, uses hydraulic technology to extract the characteristic signals of key components, uses support vector mechanisms to build a hybrid electric vehicle classifier, and obtains the fault alarm results for dynamic performance based on hydraulic technology. The results show that the proposed method can improve real-time diagnosis and alarm for engine faults in HEV, and the fault can be diagnosed after 5 s of injection, thus ensuring the dynamic stability of HEV.

Harmonic Resonance Analysis of Shale Gas Distribution Network with Phased Load

Based on the background of achieving carbon peaking and carbon neutrality, the development and application of new high-power compressors, electric grid drilling RIGS and electric fracturing pump system provide new equipment support for the electric, green and intelligent development of shale gas fields in China. However, the harmonic pollution of shale gas grid becomes more serious due to the converter and frequency conversion device in the system, which easily causes harmonic resonance problem. Therefore, the harmonic resonance of shale gas grid is comprehensively analyzed and treated. Firstly, the working mechanism of compressor, electric drilling RIGS of the harmonic impedance model of electric fracturing pump system is established. Secondly, the main research methods of harmonic resonance analysis are introduced, and the basic principle of modal analysis is explained. Modal analysis method was used to analyze. Finally, harmonic resonance is suppressed. The results show that there may be multiple resonant frequency points in the distribution network changes, but these changes are relatively clear; if the original resonant frequency point of the resonant loop does not exist, the resonant frequency point disappears. The optimal configuration strategy of passive filter can effectively suppress harmonic resonance of distribution network in shale gas field.

Концептуальное представление энергетического перехода в электроэнергетике региона в новых реалиях

The energy transition is a global problem affecting environmental and energy security, sustainable economic development, social well-being. However, since its implementation differs in certain regions, it is necessary to develop specific approaches that consider local factors, external threats and risks. The article proposes a conceptual vision of energy transition at the regional level in the context of crisis, economic and logistical changes, and socio-economic, scientific and technical transformations. It is hypothesised that in order to implement the energy transition, a compensation method is required to ensure the equivalence of environmental, economic and technical results. The study analysed expert opinions published in foreign and Russian journals indexed in the SCOPUS, Science Direct, MDPI, WIT Press databases, as well as analytical reports of international energy agencies and consulting firms. The analysis revealed that the most appropriate form of organisation of the regional electric power system is a flexible model combining system and regional circuits and involving power plants with a wide range of generating capacities. The integrated power system and decentralised energy sources are seen as energy transition objects. The study presented an energy transition scheme from the implementation of low-cost energy demand management measures to the reconstruction of coal-fired power plants and construction of renewable energy facilities. An ideal model of the regional electric power system was developed as a strategic guideline in the energy transition implementation. Possible scenarios and stages of the energy transition were discussed. The findings can be applied by government and industry regulators, energy companies, large electricity consumers when planning structural, organisational and market transformations in the regional energy sector under uncertainty.

Dynamic Phasor Finite-Element Modeling of a DFIG for Grid Connection Studies

Co-simulation studies of electric power systems and electric machines have been always a challenge. In order to reduce the simulation time to a reasonable value, lumped-parameter Electric-Machines models are commonly used in electric power system modeling software packages to avoid the heavy computational burden of more accurate modeling methods especially Finite Element Method (FEM) on the expense of less accuracy. The proposed technique in this paper combines the Dynamic Phasor Modeling technique for power system simulations with FEM to accurately model the DFIG while connected to the grid. The utilization of dynamic phasors enables adopting large simulation time-steps resulting in a significant reduction in the simulation time compared to the conventional time-domain FEM modeling. The mathematical foundation of the proposed modeling method is presented including the generator's core saturation. Custom-written C++ codes have been developed by the authors to execute the new dynamic phasor FEM algorithm and the conventional time-domain FEM in order to fairly compare their accuracy and numerical performances. As the proposed method combines time and frequency domains, a unique capability of modeling the rotor movement can be achieved. The rotation can be represented by physically incrementing the rotor and airgap mesh as in regular time-domain solvers, by mathematically representing the rotation using the Virtual Blocked Rotor method as in frequency-domain solvers, and the proposed method of combining the two aforementioned approaches. The three methods of modeling rotor rotation are discussed and their simulation results are compared to give a guide to choose the proper method for the different modeling targets. The results show that the proposed dynamic phasor FEM is capable of producing comparable results to the traditional time-domain solver at a substantially reduced simulation time.

How CO2 prices accelerate decarbonisation – The case of coal-fired generation in Germany

This paper analyses the potential impact of the world's two main coal phase-out instruments: 1) direct regulatory intervention restricting the operation of existing coal-fired generation capacity and prohibiting investment in new capacity and 2) market-based CO2-pricing instruments that make emission-intensive coal-fired generation less competitive. We quantify these instruments' potential effects in the empirical setting of Germany, where both instruments are employed concurrently. However, this paper's approach and methodology can be applied in any jurisdiction or energy system worldwide.Our paper provides quantitative results with a pan-European partial-equilibrium electricity system model. The model applies an innovative three-step approach. Step 1 solves an investment and dispatch problem with reduced technical and temporal complexity for European countries. Step 2 computes the dispatch problem at a bihourly resolution and step 3 solves the investment and dispatch problem for Germany with increased technical complexity.Our results confirm that both a regulated phase-out as well as a price on CO2 emissions can reduce the amount of coal-fired generation in an electricity system. If CO2 prices remain at current levels, coal-fired power plants leave the market significantly before the regulated phase-out date, reducing demand for employees in the Lusatian lignite industry. Regions and federal governments should take this finding into account when planning and preparing for structural change.

Development and test of a cost-efficient gridded ion thruster propulsion system for small satellites – IonJet

IonJet is an engineering model of a low-cost electric propulsion system for small satellites. Whereas the flow control subsystem is based on the MICROJET 2000 system launched 2016 on the BIROS satellite, the thruster subsystem is based on a novel gridded ion thruster where the neutralizer is integrated in the ion thruster allowing for simultaneous ion and electron extraction. This design allows reducing the number of components and consequently costs and system complexity. The whole system was successfully tested under vacuum conditions regarding ignition and stable operation of the propulsion system. In the performance tests, thrusts of 1 mN could be achieved using Xe gas as propellant at a total power consumption of less than 50 W as well as specific impulses larger than 1000 s, including the gas consumption of the neutralizer. In addition, first tests with Kr gas were performed showing that for the same total power the achievable thrust is reduced to 55% – 68% of that for Xe.

Feed-Forward Neural Network for health monitoring of a parallel hybrid electric power system

Hybrid engines are becoming more and more widespread. Electric energy instead is a valid help to reduce the environmental impact. In hybrid engines, the number of components is higher and this results in a decrease in reliability. With Engine Health Monitoring (EHM) we mean the set of techniques used to monitor the health status of a system based on the values assumed by some related parameters. Artificial Intelligence (AI) methods are widely used nowadays in this discipline. In this paper, an EHM approach was developed to monitor the health status of some components constituting an hybrid turboshaft. The dynamic model of the hybrid electric power system is described in an accompanying paper. Feed-Forward Neural Network (FFNN) is used as AI tool to built the just cited system. The engine modelled with Simulink, was used to perform a series of steady-state simulations implementing a degradation condition in some selected components. The degradation condition was simulated by changing the value of the Performance Parameters (PPs) related to each of the selected components. The results of the simulation were used to obtain a dataset useful to train the FFNN to predict the values of the same PPs in a degraded case.

A dynamic model of a Hybrid Electric Propulsive System for degradation assessment

The present study proposes a model for the simulation of the steady-state and transient behaviors of a Hybrid Electric Propulsive System (HEPS), in presence of several forms and degrees of performance degradation. The power system, which is made of a turboshaft engine coupled with an electric power source is intended for urban air mobility applications. The proposed model encompasses the capability of modeling battery aging effects, and, consequently, updating the performance of the system with battery life. Moreover, the versatility of the proposed model makes it suitable for the analysis of the dynamic behavior of the system, for example in presence of small perturbations around predefined operational settings or following a known mission profile. In this investigation the model is applied to the test of the HEPS under different operating conditions with different degradation criteria, affecting both the thermal and the electric drive with different levels of severity. The application of the model allowed the generation of relevant information concerning the propulsive system state of health which will be processed with the employment of machine learning algorithms in an accompanying paper.

Coupled Model and Node Importance Evaluation of Electric Power Cyber-Physical Systems Considering Carbon Power Flow

To improve the distributed carbon emission optimization control capability of the smart distribution network system, thereby reducing the carbon emissions in the distribution process, it is a very important issue to comprehensively analyze the importance of the node carbon emission flow of the smart distribution network. This paper transforms the power grid into a carbon emission flow network through power flow calculations: Based on the complex network theory, it determines the coupling scale of the two networks by means of the correlation coefficient method and the correlation matrix method, and establishes a coupling network model based on the carbon emission flow network; Combining the different business characteristics of carbon emission flow and information flow, an evaluation index system considering the dual-network coupling scale is established, and a multi-indicator comprehensive evaluation method that combines the Topsis and grey relational analysis method, that can objectively evaluate indicators that contain subjective components was proposed; The obtained node importance values can be used to determine the relative key line, greater sum node importance values represent a greater carbon emission impact of the line, providing a sequential basis for the carbon reduction and restructuring of the distribution network; Taking the 3-machine 9-node system as an example, the carbon flow distribution in the corresponding network is calculated, and the comprehensive importance value of the coupling node is calculated to analyze the rationality of this method.

RF Stray Currents in SPIDER Power Circuits: Model Assessment and Experimental Results

The ITER Neutral Beam Test Facility (NBTF), Padua, Italy, hosts two different experiments: Source for Production of Ion of Deuterium Extracted from Rf plasma (SPIDER), the prototype of the ion source (IS) of ITER neutral beam injector (NBI), and Megavolt ITER Injector and Concept Advancement (MITICA), the prototype of the ITER NBI. The ISs of SPIDER and MITICA are driven by radio frequency (RF) power, for a total of 800 kW at 1 MHz. The RF power is delivered to the inductively coupled plasma drivers of the IS by four tetrode oscillators. Operation of SPIDER at high power pointed out the presence of RF stray currents circulating in the electric system. These currents hinder the correct operation of the system, causing damage to its components. To improve the comprehension of the issue, after an overall circuital investigation and the identification of a possible reclosing path for the RF stray currents, a simplified model of SPIDER electric system was developed, initially focusing on a single RF circuit. The aim of the work presented in this article is to extend the model to four RF circuits, to study the impact of their mutual coupling and of the common potential references on RF stray currents magnitude, with a view to improve the comprehension of the issue and the effect of the provisions to mitigate it. The results obtained with this model are compared to SPIDER experimental measurements for validation.

Active-reactive power collaborative optimization model of electrical interconnection system based on deep learning under the goal of “carbon neutrality”

With the goal of carbon neutralization put forward, new energy units have gradually become the main power supply, and its volatility has brought great challenges to the control and optimization of the system, especially the distribution network. In order to solve the reactive power problem caused by the high proportion of renewable energy connected to the distribution network, a source network load storage centralized optimal dispatching model considering reactive power optimization and multi energy collaborative interaction is proposed. The model aims at the optimal operation cost, minimum network loss and minimum carbon emission of the multi energy system, and considers reactive power compensation, energy storage regulation and energy conversion, so as to realize the safe and low-carbon economic dispatching of the electrical interconnection system. The switching capacity of the discrete reactive power compensation device is linearized, and the model is transformed into a mixed integer second-order cone programming problem for solution. The simulation results show that the proposed method can effectively compensate the reactive power required by the wind turbine parallel network, coordinate the energy interaction between electricity and gas, and improve the stability and flexibility of the distribution network after large-scale renewable energy access, According to the charging and discharging power and charge state, and the automatic adjustment of the gears of on load voltage regulating transformer and compensation capacitor bank, this paper shows that the system has safe and stable operation performance.

OSeMOSYS Global, an open-source, open data global electricity system model generator

This paper describes OSeMOSYS Global, an open-source, open-data model generator for creating global electricity system models for an active global modelling community. This version of the model generator is freely available and can be used to create interconnected electricity system models for both the entire globe and for any geographically diverse subset of the globe. Compared to other existing global models, OSeMOSYS Global allows for full user flexibility in determining the time slice structure and geographic scope of the model and datasets, and is built using the widely used fully open-source OSeMOSYS energy system model. This paper describes the data sources, structure and use of OSeMOSYS Global, and provides illustrative workflow results.

Fabrication and Mathematical Modeling of the Brushless Doubly Fed Induction Generator-Based Wind Electric Conversion System

Electricity generation with minimal environmental pollution is required for the world’s sustainable future, and wind electric generation is one of them. Brushless doubly fed induction generator (BDFIG), which derives from cascade induction machine technology, has grown in popularity as a wind electric generator due to advantages over doubly fed induction generator (DFIG) and permanent magnet synchronous generator (PMSG) such as the absence of slip rings and brushes and high-cost permanent magnets. Wind energy research is critical for any country’s economic development and long-term sustainability. As a result, an experimental setup in a laboratory is required to replicate the behaviour of a wind turbine in the steady state. This study discusses the emulation of wind turbine characteristics in the laboratory using a prototype of a separately excited DC motor mechanically coupled to a brushless doubly fed induction generator (BDFIG). The wind turbine emulator-brushless doubly fed induction machine (WTE-BDFIM) prototype was tested in the laboratory under high power and low wind speed conditions. As a result, the simulation of the same hardware configuration in MATLAB was performed to investigate the overall performance of the BDFIM-based WECS. To determine the equivalent circuit parameters of the BDFIM, which are required for simulation, tests were performed on a prototype of 3.5 kW, 2/6 pole, 400 V, star/delta-star, and BDFIM in two modes, namely, the simple induction mode and the cascade induction mode. Based on the BDFIM parameters, a MATLAB Simulink model of a BDFIG-based wind electric conversion system (WECS) is created and its performance is investigated. Results of both hardware and simulation show that BDFIG can be used as the wind electric generator over a wider speed range compared to that of DFIG, an important feature that is required to get maximum power extraction from the wind turbine.

Matching and performance analysis of a solid oxide fuel cell turbine-less hybrid electric propulsion system on aircraft

Advanced low-carbon propulsion technology is one of the major initiatives to address aviation environmental challenges. In this paper, a solid oxide fuel cell turbine-less hybrid electric propulsion system is developed. It is a new engine, in which the power consumed by the compressor comes from a fuel cell, not a turbine. The aircraft's propulsion comes from the high-velocity exhaust discharged from the nozzles. To make the key fuel cell work properly and determine the system operating parameters, it is necessary to study the matching and performance of the hybrid electric propulsion system. In this study, a performance analysis model of the hybrid electric propulsion system is established. In particular, a one-dimensional fuel cell is simulated to obtain its localized thermal gradient. The results show that the hybrid electric propulsion system has a satisfactory performance under the design conditions. It is superior to the gas turbine-based engine in performance, and they have different performance trends. The operating range of compressor pressure ratio is determined. The sensitivity analysis shows that in addition to compressor pressure ratio, Mach number, reforming temperature, and fuel utilization have a great influence on the performance, which is worthy of further study.