Entire Electrical System Research Articles

The effects of wind power on electricity markets: A case study of the Swedish intraday market

We investigate the process of electricity price formation in the Swedish intraday market, given a large share of wind power in the Swedish electricity system. According to Karanfil and Li's (2017) approach, if the intraday market is efficient, with large shares of intermittent electricity in the entire electricity system, intraday prices should send signals based on scarcity pricing for balancing power. Based on this theory, we analyze Swedish electricity market data for the period 2015–2018 and find that the Swedish intraday market, despite its small trading volumes, is functioning properly. In particular, our results show that intraday price premia mostly respond to wind power forecast errors and other imbalances resulting from either supply or demand sides of the electricity market, as they should if the intraday market is efficient. The results of wind power forecast errors hold for central and southern Sweden, but not for northern Sweden where the share of wind power production is still very small. However, we find no effect of unplanned nuclear power plant outages on intraday price premia.

Incipient fault diagnosis method for DC–DC converters based on sensitive fault features

DC–DC converters play an important role in electrical systems. The fault state of a DC–DC converter has a major impact on the operation of the back-end components and the entire electrical system. Therefore, the fault diagnosis is very necessary when the fault state of DC–DC is in the early stage. It can decrease the likelihood of happening the serious faults that may result in the enormous economic loss. To effectively diagnose the incipient fault in DC–DC converters, an incipient fault diagnosis method based on sensitive fault features is proposed. Firstly, for each type of the incipient fault, this study obtains the statistical features in time domain and the wavelet analysis local energy values in the frequency domain of the output. Then to further improve the incipient fault diagnosis accuracy, this study removes the redundant fault features based on overlap calculation, the unique fault features for each type of incipient fault will be selected. Finally, these sensitive fault features are used to build support vector data description models, which can diagnose the incipient faults. Simulation and hardware experimental results validate the practicability and effectiveness of the proposed method.

The impact of neighboring markets on renewable locations, transmission expansion, and generation investment

Many long-term investment planning models for liberalized electricity markets either optimize for the entire electricity system or focus on confined jurisdictions, abstracting from adjacent markets. In this paper, we provide models for analyzing the impact of the interdependencies between a core electricity market and its neighboring markets on key long-run decisions. This we do both for zonal and nodal pricing schemes. The identification of welfare optimal investments in transmission lines and renewable capacity within a core electricity market requires a spatially restricted objective function, which also accounts for benefits from cross-border electricity trading. This leads to mixed-integer nonlinear multilevel optimization problems with bilinear nonconvexities for which we adapt a Benders-like decomposition approach from the literature. In a case study, we use a stylized six-node network to disentangle different effects of optimal regional (as compared to supra-regional) investment planning. Regional planning alters investment in transmission and renewable capacity in the core region, which affects private investment in generation capacity also in adjacent regions and increases welfare in the core region at the cost of system welfare. Depending on the congestion-pricing scheme, the regulator of the core region follows different strategies to increase welfare causing distributional effects among stakeholders.

Non-Strategic Capacity Withholding from Distributed Energy Storage within Microgrids Providing Energy and Reserve Services

Microgrids have the potential to provide security and flexibility to power systems through the integration of a wide range of resources, including distributed energy storage, usually in the form of batteries. An aggregation of microgrids can enable the participation of these resources in the main system’s energy and ancillary services market. The traditional minimum-cost operation, however, can undermine microgrid’s ability to hold reserve capacity for operation in islanded mode and can rapidly degrade distributed batteries. This paper studies the impacts of various operational strategies from distributed energy storage plants on their revenues and on market prices, considering an array of microgrids that act in a synchronized fashion. The operational model minimizes the entire electric power system cost, considering transmission-connected and distributed energy resources, and capturing capacity degradation of batteries as part of the cost function. Additionally, microgrid-based, distributed batteries can provide energy arbitrage and both system-level and microgrid-level security services. Through several case studies, we demonstrate the economic impacts of distributed energy storage providing these services, including also capacity degradation. We also demonstrate the benefits of providing reserve services in terms of extra revenue and battery lifespan. Finally, we conclude that limitations in the provision of system-level services from distributed batteries due to degradation considerations and higher microgrid-level security requirements may, counterintuitively, increase system-level revenues for storage owners, if such degradation considerations and microgrid-level security requirements are adopted, at once, by a large number of microgrids, leading to unintended, non-strategic capacity withholding by distributed storage owners.

Energy performance prediction of the centrifugal pumps by using a hybrid neural network

It is of great significance to rapidly and accurately predict the energy performance of centrifugal pumps for the macro-control of the entire electric power system. However, some challenges are encountered, for example, the numerical simulation requires huge computing resources and calculating time, the theoretical loss model needs to improve the prediction accuracy, etc. Based on the multiple geometrical parameters and operation conditions, a hybrid neural network is proposed to predict the energy performance (i.e. the head, power and efficiency) of centrifugal pumps, where the theoretical loss model is incorporated into the back propagation neural network and then the neural network structure is optimized by automatically determining the node number of hidden layers. When compared with the experiments, the energy performance is well predicted by using the hybrid neural network with the mean-square-error (MSE) for the head, power and efficiency of 0.0062, 8.4E-4, 0.020, respectively. Besides, by considering the theoretical loss model, the hybrid neural network demonstrates a dramatic decrease in the head MSE and the efficiency MSE when compared with the original neural network. Furthermore, the hybrid neural network performs much better than the traditional linear regression in a wide flow-rate range for multiple centrifugal pumps.

Optimal scheduling for electric bus fleets based on dynamic programming approach by considering battery capacity fade

The extension of battery life in electric bus fleets depends intimately on the effective energy management of both internal controls on board and external operations on roads. In this work, an optimal scheduling method based on dynamic programming was proposed to minimize battery replacement costs during the entire service life of electric bus fleets. It highlighted a three-part model. In the first part, the dynamic programming model was proposed to solve the scheduling problem for electric bus fleets. In the second part, a reverse order matching strategy was proposed to simultaneously consider the battery capacity fading processes and the differences in the working loads. In the third part, the battery capacity degradation model was used to determine the amount of battery capacity loss and the number of battery replacements. A case study was used to demonstrate the implementation procedure of the proposed method. The influences of practical factors, such as the differences in the working loads, the number of the electric bus fleets, the duration of the scheduling period, and the working temperature of batteries on the electric bus fleet scheduling were analysed and discussed. Compared with the base case, the proposed method reduces the investment for battery replacements by 20% for the entire electric bus fleet system. The proposed method can readily be applied to a large-scale public transit system to formulate optimal scheduling schemes.

The Effects of Wind Power on Electricity Markets: An Evaluation Using the Swedish Electricity Market Data

We investigate the process of electricity price formation in the Swedish intraday market, given a large share of wind power in the Swedish electricity system. According to Karanfil and Li’s (2017) approach, if the intraday market is efficient and liquid, with large shares of intermittent electricity in the entire electricity system, the intraday price should send signals based on scarcity pricing for balancing power. Based on this theory, we analyze the Swedish electricity market data for the period 2015–2018 and find that the Swedish intraday market, despite its small trading volumes, is functioning properly. In particular, our results show that intraday price premia respond in an expected way to wind power forecast errors and other imbalances resulting from either supply or demand sides of the electricity market. The results of wind power forecast errors hold for central and southern Sweden, but not for northern Sweden where the share of wind power production is still very small. In addition, we find no effect of unplanned nuclear power plant outages on intraday price premia.

Online Anomaly Detection in DC/DC Converters by Statistical Feature Estimation Using GPR and GA

DC/DC converters play an important role in electrical systems. The anomalous state of a dc/dc converter has a major impact on the operation of the back-end components and the entire electrical system. To effectively recognize an anomalous state, particularly for dc/dc converters with unknown circuit structures, an online anomaly detection method that involves statistical feature estimation using Gaussian process regression (GPR) and a genetic algorithm (GA) is proposed. In the proposed method, the normal output range is built upon the dc/dc normal output signal using GPR, and seven statistical features are considered as the detection indexes. In the detection process, the output signal of the dc/dc converter is acquired, and the corresponding extreme values of statistical features are calculated by using GA, which can effectively reduce the operation time and the calculation consumption. The working state of the dc/dc converter is distinguished according to these features. Simulation and hardware experimental results validate the practicability and effectiveness of the proposed method.

Electric Vehicle Relay Lifetime Prediction Model Using the Improving Fireworks Algorithm–Grey Neural Network Model

The relay reliability has an impact on the reliability of the entire electric vehicle system. This paper contributes to propose the improving fireworks algorithm optimizing the grey neural network model to predict the relay lifetime. This paper shows how the mutation operation and mapping operation in the fireworks algorithm are used to improve the convergence ability and running speed; the convergence performance and running speed of improved fireworks algorithm are tested with standard test function and compared with fireworks algorithm; and the grey neural network model–improved fireworks algorithm is used to predict the relay life and compared with grey model, grey neural network, and grey neural network model–fireworks algorithm. The results show that the convergence accuracy of the improved fireworks algorithm is better than the fireworks algorithm. The running time of improved fireworks algorithm is the shortest; the improved fireworks algorithm–grey neural network model has the best prediction effect and the root mean square error value is 6.75% smaller than the fireworks algorithm–grey neural network model.

Supervised learning for early and accurate battery terminal voltage collapse detection

Rechargeable batteries are critical components in many electrical systems nowadays. One has to ensure reliable diagnosis and assessment of the installed batteries for smooth and safe operations. Assessment of the remaining capacity of a battery is crucial diagnostic information. A battery management system (BMS) needs to reliably report the ability of the battery to supply power or the lack thereof. If the BMS fails to do so at an early stage, this may compromise the health of the entire electric system. When a battery nears a region where the battery state-of-charge (SOC) is low, there is a risk of an abrupt drop in the terminal voltage. An early detection of such a region is crucial; otherwise, the BMS may not have enough time to react. To address this issue, our work provides a novel supervised learning approach towards an early detection of Li-ion battery terminal voltage collapse. No knowledge of initial SOC or battery model parameters is required. This is particularly important as batteries lose their capacity to store charge over time. The efficacy of the proposed approach is demonstrated by an early and accurate detection of terminal voltage collapse over a set of discharge tests conducted using multiple batteries.

Development of GB distribution networks with low carbon technologies and smart solutions: Scenarios and results

This is the second paper of the two-paper suite that describes development of future GB distribution networks integrating low carbon technologies (LCTs) and traditional and smart solutions for network reinforcement. The static and dynamic aspects of distribution networks development, as well as impact on the entire GB transmission system are investigated. The overall planning concept, planning assumptions and concepts, most important features of steady-state and dynamic studies, as well as traditional and smart solutions for the network development are presented in the first paper. This paper presents the energy LCT scenarios, projected LCT uptakes, modelling and profiles of different types of LCTs first. Results of the distribution network development studies are given next, which is followed by the results of studies that do not change development paths. The aggregated impact of all GB distribution networks on the entire electricity system is given through the analysis of system-wide frequency disturbances. Conclusions related to specific studies and networks are presented in the relevant sections, whilst the closing section gives generalized conclusions approved by the GB industry as answers to the key issues the future networks are faced with.

Application Analysis of Single Chip Microcomputer Technology in Electric Drive Control System

With the continuous development of information technology, the performance of the entire electrical traditional system is gradually optimized. Among them, the single-chip technology as an important part of the electrical traditional system determines the operation quality of the entire traditional system. Based on past work experience, this paper summarizes the basic overview of single-chip technology. This paper is analyzing the application in software system, the improvement of the whole device performance algorithm, the application in the system header file, the application in the control system, the practical application. The six aspects of precautions and application examples are discussed in the application of single-chip technology in electric drive control system.

Review of Substation Grounding System Behavior Under High Frequency and Transient Faults in Uniform Soil

Substations are important parts of electric power systems, and they require well-designed grounding systems. A proper grounding system guarantees the safety of the personnel working in an environment surrounded by grounded equipment from possible electric shock, protects the equipment against unnecessary breakdowns, and conserves the stability of the entire electrical system throughout its operation. Grounding systems developed under power frequency conditions generally react differently under high frequency and transient conditions, such as switching transients and lightning strikes. This work reviews the modeling methods for substation grounding systems and their performance when grounding design parameters change under high frequency and transient fault conditions.

Cost minimization for fully renewable electricity systems: A Mauritius case study

Climate change is the world's most prominent environmental problem, and fossil-fuel combustion is its primary cause. To set carbon reduction goals, policy makers require information on feasibility and cost of renewable energy systems. In this study, we describe an economic approach to modeling a national electricity system based entirely on renewable sources, using the island-nation of Mauritius as a case study.Many renewable electricity studies consider levelized costs of electricity (LCOE), which represents average cost of electricity, but cost minimization requires equalizing marginal costs. With variable sources, marginal costs change over time. Minimizing cost thus requires a model incorporating variability at high time resolution (daily or hourly), with the objective of minimizing the levelized cost of electricity for an entire electricity system (LCOES).In Mauritius, the minimum-cost renewable electricity portfolio includes roughly equal proportions of solar, wind, and biomass electricity, along with electricity storage. Policy issues include setting renewable energy targets, selecting policy instruments to incentivize optimum renewable energy portfolios, incorporating energy efficiency, determining appropriate discount rates, ensuring land availability, and accounting for non-cost considerations. Many of the economic and policy issues identified apply universally, and methods demonstrated in this study could be used anywhere in the world.

Investigating Phase Over-Current (OC) Protection in Medium-Voltage networks

Overcurrent protection is protection against excessive currents or current beyond the acceptable current rating of equipment. It generally operates instantly. Short circuit is a type of overcurrent. Magnetic circuit breakers, fuses and overcurrent relays are commonly used to provide overcurrent protection. There is always a need to protect expensive power equipment. Protective relaying is a very important part of any electric power system that comes into play during trouble, fault or abnormal condition. The purpose is to isolate unhealthy part of electrical power system while the rest continue their normal operation. The entire electric power system from source to load centers is exposed and subject to natural hazards. The effects of these hazards are capable of interrupting normal operations of the system. Since these hazards cannot be prevented, precautions are taken to minimize or eliminate their effect on the system. The relay is a basic component of any protection scheme. The information (or signals) received from the power system actuates the relay, when necessary, to perform one or more switching actions. The signals are proportional to the magnitudes and phase angles of power system voltages and currents. When the relay receives these signals, it decides to close (or open) one or more sets of normally open (or closed) contacts, and consequently, the trip coil of a circuit breaker will be energized to open the power circuit. This paper investigates over-current relay protection scheme applied to medium-voltage electrical network. Methods of current and time grading have been applied in the coordination of the overcurrent relays in a radial network. Different time/current characteristics of relays such as the normal inverse (NI), very inverse (VI), and extreme inverse (EI) have been examined in order to obtain optimum discrimination.

Investigating Phase Over-Current (OC) Protection in Medium-Voltage networks

Overcurrent protection is protection against excessive currents or current beyond the acceptable current rating of equipment. It generally operates instantly. Short circuit is a type of overcurrent. Magnetic circuit breakers, fuses and overcurrent relays are commonly used to provide overcurrent protection. There is always a need to protect expensive power equipment. Protective relaying is a very important part of any electric power system that comes into play during trouble, fault or abnormal condition. The purpose is to isolate unhealthy part of electrical power system while the rest continue their normal operation. The entire electric power system from source to load centers is exposed and subject to natural hazards. The effects of these hazards are capable of interrupting normal operations of the system. Since these hazards cannot be prevented, precautions are taken to minimize or eliminate their effect on the system. The relay is a basic component of any protection scheme. The information (or signals) received from the power system actuates the relay, when necessary, to perform one or more switching actions. The signals are proportional to the magnitudes and phase angles of power system voltages and currents. When the relay receives these signals, it decides to close (or open) one or more sets of normally open (or closed) contacts, and consequently, the trip coil of a circuit breaker will be energized to open the power circuit. This paper investigates over-current relay protection scheme applied to medium-voltage electrical network. Methods of current and time grading have been applied in the coordination of the overcurrent relays in a radial network. Different time/current characteristics of relays such as the normal inverse (NI), very inverse (VI), and extreme inverse (EI) have been examined in order to obtain optimum discrimination.

Shared electric push ship scheme based on "Internet +" in the Lake

Aiming at the problems of current diesel engine pollution, water-powered ship promotion, and slow battery charging, this paper designs a shared electric pusher scheme for the "Internet +" lake area waters. Through the power transformation of agricultural ships on inland rivers and lakes, the original diesel engine ships were replaced by electric pushers. The design of shared batteries, different kinds of charging piles, information sharing network platform and operation mode are added. After the power transformation of the ship, the charging pile is used to provide a stable charging platform for the shared battery; The information sharing network platform is used to provide users with information about the location and usage of shared batteries and charging piles, and to provide managers and maintenance personnel with information about the frequency and location distribution of equipment, so as to realize online tracking of equipment. The operation mode is used to realize the operation of the entire shared electric push boat system.

Rapid‐prototyping and hardware‐in‐the‐loop laboratory platform for development and testing of electro‐mechanical actuator controls

To meet the challenges posed by the increasing use of electrical actuation on board next generation aircraft, advanced experimental testing capabilities are required to investigate optimal system design, performance and control. Rapid control-prototyping and hardware-in-the-loop (HiL) techniques provide the ability to expedite experimental testing, allowing for elements of the system to be validated without requiring fully realised hardware. Previously, this would require large scale laboratory setups, where the entire electrical and mechanical system would have to be designed and built prior to experimental testing. This study presents the development of a laboratory HiL and rapid-prototyping test-bench, capable of investigating the performance of actuator motor control schemes, under a variety of test conditions. Experimental testing is carried out using a laboratory test-bench, demonstrating the performance of landing gear electromechanical actuator controls under power system and load transients.

Implementation of the Automatics for Switching the Combined-Cycle Plant of Power-Generating Unit No. 5 at Hrazdan Thermal Power Plant to the Steam Power Plant and Gas Turbine Modes

The article describes an automated technology put into practice for switching power-generating unit no. 5 at Hrazdan Thermal Power Plant from the combined-cycle plant (CCP) mode to the steam power plant or gas-turbine unit (SPP and GTU, respectively) modes upon an emergency shutdown of the gas or steam turbine. The layout of the power unit based on the waste-gas heat utilization scheme enables the thermal power plant to operate with a partial mix of the equipment, viz., without the gas turbine or steam turbine. However, the initial project did not provide for changing the operational mode without the total shutdown of the power unit. During a sudden shutdown, the considerable unit output of the power unit results in considerable disturbances in the entire electric power system of the Republic of Armenia. The maintenance of a partial capacity of the power unit under emergency shutdown of the equipment reduces unwanted consequences for both the power plant and the electric power system as a whole. A great scope of urgent switching operations and changes in the automatic regulator settings upon sudden shutdown of the gas or steam turbine makes successful actions of the operator under the manual changeover from the CPP mode to the SPP or GTU modes unlikely. Such a changeover can be performed only by the automatics with the operator performing fine correction of the mode upon completion of first-priority switching operations if necessary. The appropriate algorithms for automatic change of the mode when shutting down the gas or steam turbine were implemented in the Automated Process Control System (APCS) of the power unit. In the article, the basic scope and the sequence of actions performed by the automatic devices upon shutting down the gas or steam turbine, as well as the principles of automatic adjustment of the circuits for automated control of the fuel-to-water and fuel-to-air ratios and the temperature conditions of the boiler, are set forth. The article also provides the results of full-scale tests and an example of the behavior of the basic parameters upon shutting down the gas turbine and switching the power unit over to the SPP mode.

Behavior and functional modeling methods of doubly salient electromagnetic generators for aircraft electrical power system applications

The Doubly Salient Electromagnetic Generator (DSEG) is a promising candidate in aircraft generator application due to the simplicity, robustness and reliability. However, the field windings and the armature windings are strongly coupled, which makes the inductance characteristics non-linear and too complex to model. The complex model with low precision also leads to difficulties in modeling and analysis of the entire aircraft Electrical Power System (EPS). A behavior level modeling method based on modified inductance Support Vector Machine (SVM) is proposed. The Finite Element Analysis (FEA) inductance data are modified based on the experiment results to improve the precision. A functional level modeling method based on input–output characteristics SVM is also proposed. The two modeling methods are applied to a 9 kW DSEG prototype. The steady state and transient process precision of the proposed methods are proved by comparing with the experiment results. Meanwhile, the modeling time consumption, the application time consumption and the calculation resource demand are compared. The DSEG behavior and functional modeling methods provide precious results with high efficiency, which accelerates theoretical analysis and expands the application foreground of the DSEG in the aircraft EPS.