Hasil untuk "Distribution or transmission of electric power"

Jian Zhang, Yigang He

High penetration of electrical vehicles (EVs) and renewable distributed generators (DGs) into active distribution networks (ADNs) lead to frequent, rapid and fierce voltages magnitudes violations. A novel two-timescale coordination scheme for different types of adjustable devices in ADNs is put forward in this article by organically integrating data-driven deep reinforce-ment learning (DRL) into physical convex model. A Markov Decision Process (MDP) is formulated on slow timescale, in which ratios/statuses of on load transformer changers (OLTCs) and switchable capacitors reactors (SCRs) and ESSs charging/ discharging power are set hourly to optimize network losses while regulating voltages magnitudes. An improved DRL with relaxation-prediction-correction strategies is proposed for eradicating discrete action components dimension curses. Whereas, on fast timescale (e.g., several seconds or minutes), the optimal reactive power of DGs inverters and static VAR compensators (SVCs) in balanced and unbalanced ADNs are set with physical convex optimization to minimize network losses while respecting physical constraints. Five simulations cases with IEEE 33-node balanced and 123-node unbalanced feeders are carried out to verify capabilities of put forward method.

Shahriar Rahman Fahim, Rachad Atat, Cihat Kececi et al.

The integration of information and communication technologies into modern power systems has contributed to enhanced efficiency, controllability, and voltage regulation. Concurrently, these technologies expose power systems to cyberattacks, which could lead to voltage instability and significant damage. Traditional false data injection attacks (FDIAs) detectors are inadequate in addressing cyberattacks on voltage regulation since a) they overlook such attacks within power grids and b) primarily rely on static thresholds and simple anomaly detection techniques, which cannot capture the complex interplay between voltage stability, cyberattacks, and defensive actions. To address the aforementioned challenges, this paper develops an FDIA detection approach that considers data falsification attacks on voltage regulation and enhances the voltage stability index. A graph autoencoder-based detector that is able to identify cyberattacks targeting voltage regulation is proposed. A bi-level optimization approach is put forward to concurrently optimize the objectives of both attackers and defenders in the context of voltage regulation. The proposed detector underwent rigorous training and testing across different kinds of attacks, demonstrating enhanced generalization performance in all situations. Simulations were performed on the Iberian power system topology, featuring 486 buses. The proposed model achieves 98.11% average detection rate, which represents a significant enhancement of 10-25% compared to the cutting-edge detectors. This provides strong evidence for the effectiveness of proposed strategy in tackling cyberattacks on voltage regulation.

Wiebke Gerth, Eric Schulze Berge, Marius Güths et al.

The transformation of heating supply is critical to achieve climate neutrality by 2045. In 2024, new regulations specify climate-neutral heating solutions for new quarters. Heating networks are a viable option for meeting these requirements. This contribution presents an automated methodology for heating network planning in new quarters. The entire process is completed within a few seconds to minutes per optimization level, enabling an iterative approach between heating network planning and energy-based optimization. This method can be applied to both small and large quarters and provides essential data for electricity network planning, particularly regarding economic efficiency and the number of consumers served by alternative decentralized solutions.

Asaad Shemshadi, Hamid Yousef Khani

Wind power systems provide significant benefits, including ease of installation, high efficiency, and scalability. However, one of the major challenges in these systems is the occurrence of sub-synchronous oscillations (SSOs), which can severely compromise power grid stability. This study examines recent advancements in SSO mitigation strategies for Doubly-Fed Induction Generator (DFIG)-based wind energy systems, the most widely adopted technology in modern wind turbines. Various control approaches, such as intelligent controllers, adaptive control mechanisms, and predictive algorithms, are reviewed. Simulation experiments carried out using MATLAB/Simulink software confirm the effectiveness of the proposed Direct Current Vector (DCV) control method in attenuating SSOs and improving overall system performance. In addition to identifying current challenges and research gaps, this work emphasizes the critical importance of ongoing research to develop robust SSO mitigation techniques for grid-connected wind power systems. The results demonstrate that incorporating advanced technologies and sophisticated control strategies plays a vital role in reducing sub-synchronous oscillations and enhancing the operational performance of wind energy systems.

Hiroshi Kikusato, Ryu Ando, Jun Hashimoto et al.

This paper presents a methodology for optimizing the short-term operation of electric vehicle (EV) charging and discharging while considering the potential curtailment of active power due to volt-var control (VVC) prioritizing reactive power output. The proposed approach involves exchanging information between the EV aggregator and the distribution system operator (DSO). This approach allows the EV aggregator to optimize EV charge/discharge schedules while considering voltage-related constraints in the distribution system (DS). Initially, the aggregator shares the optimized schedule with the DSO to estimate the anticipated active power reduction through power flow analysis. Subsequently, the aggregator revises the constraint on active power output to avoid its expected curtailment and performs a second optimization for EV charging and discharging operation. Numerical simulations conducted on a realistic DS model in Japan validate the effectiveness of the proposed method in enhancing profitability in the day-ahead market while ensuring the quality of DS voltage. The results demonstrate an increase in profit by shifting the time of EV charging and discharging based on shared information from the DSO.

Masoud Shokri, Taher Niknam, Mojtaba Mohammadi et al.

Abstract Smart cities consist of various energy systems and services that must be optimally scheduled to improve energy efficiency and reduce operation costs. The smart city layout comprises a power distribution system, a thermal energy system, a water system, and the private and public transportation systems. Additionally, several new technologies such as reconfiguration, regenerative braking energy of the metro, etc. are considered. This study is one of the first to consider all these technologies together in a smart city. The proposed power distribution system is a grid‐connected hybrid AC–DC microgrid. The biogeography‐based optimization algorithm was utilized to seek the best solution for scheduling micro‐turbines, fuel cells, heat pumps, desalination units, energy storage systems, AC–DC converters, purchasing power from the upstream, distributed energy resources, and transferring power amongst electric vehicle parking stations and metro for the next day. Also, the reduced unscented transformation layout was used to capture the system's uncertainty. The suggested layout is implemented on an enhanced IEEE 33‐bus test system to show the efficiency of the suggested method. The results show that costs and environmental pollution are reduced. By comparing the proposed smart city with other studies, the efficiency and completeness of the proposed smart city are shown.

Marina Martins Mattos, João Antônio G. Archetti, Leonardo de A. Bitencourt et al.

Abstract The decarbonization of the power generation and transport sector encourage the analysis of connection of distributed energy resources (DER), such as electric vehicles (EVs), to the electrical system, as well as the evaluation of their impact on smart cities. A better understanding of the negative impacts on the power systems will lead to propose mitigation measures and eventually revolutionize the way distributed generation works. This paper aims at modelling and evaluating the impact of EVs on a real distribution network. The energy system chosen operates at 60 Hz, 34.5 kV (medium voltage) and 0.208 kV (low voltage) and it is simulated using PSCAD/EMTDC. To reproduce realistic user consumption profiles, dynamic load profiles based on EV owners behaviour have been simulated. The vehicle‐to‐grid (V2G) technology is modelled to mitigate the impacts of high penetration of EVs by supporting the network from undervoltage. The results show the importance of active management in modern power systems, especially considering the increase in DER penetration expected for the coming years. This work shows the benefits of implementing V2G technology while highlighting the challenges involved in a real case.

Jennie Angela Jose Shirley, Harini Manivelan, Prashant Khare et al.

Abstract The demand for electric power has consistently been on the rise, owing to urbanisation and technological improvements. On the generation side, renewable sources have been favoured over their polluting, exhaustible, non‐renewable counterparts. These changes in the power system have necessitated a system for maintaining the supply‐demand balance, to maintain system stability. A complex power system is also more prone to blackouts and grid failure. Islanding helps in provision of supply to consumers in a microgrid, reducing the possibility of a blackout. Depending on the power demand and generation, loads need to be shed or restored to mitigate power imbalances. A wide area distribution management system (WADMS) is proposed to dynamically shed and restore loads in the islanded mode, with the aid of micro phasor measurement units (µPMUs). A priority and consumer‐based load shedding and restoration (PCLS) algorithm is proposed in the WADMS that preferentially sheds or restores loads based on their assigned load priority indices and number of consumers. The algorithm has been tested on a modified IEEE 13 bus system, incorporated with a solar photovoltaic (PV) system, diesel generators (DGs) and an energy storage system (ESS) in MATLAB Simulink.

Reza Saberi, Hamid Falaghi, Mostafa Esmaeeli et al.

Abstract High‐impact, low‐probability events that cause significant annual damages seriously threaten the health of distribution networks. The effects of these events have made the expansion planning for distribution systems something beyond the traditional reliability criteria, so there is an ever‐increasing need for modifications in current planning approaches and focusing on the resilience in the expansion planning of distribution networks. The new attitude dealing with resilience and distributed generation sources in distribution networks necessitates a fundamental reconsidering of traditional distribution network planning methods. Here, by modelling common natural disasters such as floods and storms, an appropriate index is introduced to evaluate the distribution network resilience in the presence of distributed generation (DG) sources, including conventional gas‐fired and photovoltaic sources. Then, by presenting an appropriate model for load and photovoltaic production, the problem of comprehensive distribution network planning, including substations, feeders, and DG sources, is mathematically formulated as a multi‐objective optimization problem to improve resilience and optimize costs. Furthermore, a non‐dominated sorting genetic algorithm is used to solve the problem of comprehensively planning a resilient distribution network. Implementation of the proposed model on the IEEE 54‐bus sample network shows that network resilience can be improved with minimum cost by optimal network planning.

Dan Huang, Huadong Sun, Jian Zhang et al.

Abstract Increasing penetration of renewable energy sources (RESs) into power systems has brought new challenges to guarantee transient voltage stability (TVS) of the system, due to complex and different characteristics of the RES compared with the synchronous generator. The related theories to the TVS for power systems with RES (PSRESs) are incomplete, and it is difficult to construct accurate physical model of the PSRES by using traditional TVS analysis method. Here a novel data mining‐based approach for extracting key factors that affect the TVS of a PSRES is put forward. The original Relief algorithm is modified to deal with the imbalance of sample size between stable and unstable samples of the practical data set and improve the calculation accuracy. Then, a data mining scheme based on the modified Relief algorithm is presented to acquire key factors affecting the TVS. With the proposed scheme, the influence degrees of different factors on the TVS can be evaluated quantitatively by their weighting values, and then the key factors as well as the influence patterns can be determined. Test results which are conducted on the modified IEEE‐39 test system with RESs are presented to demonstrate the accuracy and efficiency of the proposed method.

Jing Ma, Chen Liu, Peng Cheng

Abstract Concerning the insufficient accuracy of the criterion for identifying commutation failure in HVDC transmission systems, a new detection method for commutation failure based on the variation rate of commutation inductance energy is proposed. First, the conducting states of the converter valves in both normal commutation and commutation failure conditions are analysed, and the correlation between the differential of valve‐side line current and the conducting state of the converter in different commutation scenarios is established. On this basis, combining the topologies of D/Y‐bridge converters, a model to calculate the variation rate of commutation inductance energy is built. Then, considering the fault characteristics of DC current, DC voltage and valve currents, it is found that the calculated value of the variation rate of commutation inductance energy is consistent with the actual value under normal commutation conditions but inconsistent under commutation failure conditions. This allows for the construction of a criterion for identifying the commutation failure. Finally, the simulation results obtained with the RT‐LAB platform verify that, the proposed method can detect the occurrence of commutation failure quickly without measuring the valve currents, and it remains accurate when dealing with commutation failure near the threshold.

Tianhui Zhao, Jianxue Wang, Tao Ding et al.

Abstract With the fast development of wind power generation, many countries actively encourage wind power to trade in the medium‐long term market. However, the traditional forward contracts from medium‐long term markets are only suitable to conventional power generation enterprises, instead of wind farms. To facilitate the accommodation of wind power in the medium‐long term market, this paper focuses on two problems: The framework of the block‐based forward contract trading method and the procurement strategy of retailers with block‐based contracts. First, a novel block‐based forward contract is proposed, where the time attributes, that is, starting and ending time, and power during each period are stipulated. Aggregating all the block‐based forward contracts will naturally form the power supply curve, which can provide boundary information for wind farms when they take part in other markets. Secondly, a chance‐constrained procurement strategy model is proposed for retailers, where the uncertainty of wind power generation, constraints of block‐based contracts, and quota obligations of retailers are considered. Furthermore, a bilinear Benders decomposition algorithm with a variant of Jensen's inequalities is applied to solve the proposed model. Finally, experimental results demonstrate the effectiveness of the proposed model and method, which is computationally efficient in solving the chance‐constrained procurement strategy problem.

Denison Gimenes Mesquita, Edson Da Costa Bortoni, Davi Marcelo Febba et al.

This paper aims to present a technique to estimate the losses of a dry-type air-core reactor (DTACR) assembled with one cylinder based on calorimetry principles while employing infrared thermography techniques. The technique is intuitive, practical, and easy to apply both in a laboratory and in the field. Nowadays, the losses on DTACR can be measured only inside of specific laboratories and the equipment shall be disconnected from system and powered-off. Instead of installing contact temperature sensors in the reactor’s internal and external surfaces, temperature measurements were remotely performed with equipment in regular operation and the losses can be obtained by the method proposed. The paper presents the nature of the losses and the theoretical basis of the proposed method. The results obtained from the proposed technique are compared to those achieved by the standard method and used to calculate results through tests performed on prototypes.

Ning Zhou, Shaobu Wang, Junbo Zhao et al.

Abstract Observability and detectability analyses are often used to guide the measurement setup and select the estimation models used in dynamic state estimation (DSE). Yet, marginally observable states of a synchronous machine prevent the direct application of conventional observability and detectability analyses in determining the existence of a DSE observer. To address this issue, the authors propose to identify the marginally observable states and their associate eigenvalues by finding the smallest perturbation matrices that make the system unobservable. The proposed method extends the observability and detectability analyses to marginally observable estimation models, often encountered in the DSE of a synchronous machine. The effectiveness and application of the proposed method are illustrated on the IEEE 10‐machine 39‐bus system, verified using the unscented Kalman filter and the extended Kalman filter, and compared with conventional methods. The proposed analysis method can be applied to guide the selection of estimation models and measurements to determine the existence of a DSE observer in power‐system planning.

Shuping Gao, Xiaochen Song, Huanfei Ye et al.

Abstract In hybrid bipolar DC transmission systems with different types of converters at each pole, the transient high‐frequency component of the voltage signal under a single‐pole grounding fault and an inter‐pole fault is significantly different for internal and external faults because of smooth‐wave reactors on both sides of the DC line. Based on these characteristics, a single‐ended electrical quantity protection scheme based on transient energy is proposed. First, the voltage fault component is extracted and then processed by using a wavelet packet transform to obtain the transient energy in each frequency band. Second, the protection criterion is determined based on the ratio between low‐frequency energy and the sum of high‐frequency energy. After the setting principle is given, the influence of the protection scheme under high transition resistance is analysed. The protection scheme is implemented in MATLAB and tested based on fault data obtained from a hybrid bipolar HVDC transmission model built in PSCAD under different operating conditions. The effectiveness of the proposed protection method is verified by simulation tests under different fault types at different fault distances. The proposed method can provide strong tolerance to high transient resistance, accurately identify internal/external faults and automatically identify fault poles.

Tarek Medalel Masaud, Ehab El‐Saadany

Abstract Unlike traditional microgrids, Provisional Microgrid (PMG) utilizes only renewable generation and small energy storage units; thus, it does not have an inherent self‐islanding capability and instead, relies on importing power from any coupled microgrid (CMG) for islanding purposes. Therefore, assuring adequate power sharing between interconnected provisional and coupled MGs is crucial for assuring self‐islanding capability and reliable operation. The optimal power that can be transferred between the coupled MG and the PMG is mainly restricted by the size of the interconnecting tie‐line; hence, determining the tie‐line optimal size becomes a crucial task that must be tackled. Furthermore, the amount of power transferred is significantly influenced by the flexibility level of each microgrid. Since battery storage systems (BSS) is the main source of flexibility in PMGs, it becomes also vital to obtain the optimal size of the BSS for planning islanded PMG system. This paper presents an optimization model to jointly determine the optimal size of the BSS in each MG and the tie‐line size to assure optimal power sharing and minimum system cost (tie‐line investment cost, BSS investment cost, and interconnected system’s operation cost). Numerical results demonstrate the effectiveness of the proposed model.

Naga Venkata Durga Vara Prasad Eluri, Pradipta Kishore Dash, Snehamoy Dhar

Abstract This study presents a novel approach using adaptive variational mode decomposition with detrended fluctuation analysis to detect the islanding disturbances for photovoltaic based DC micro grid. DC parameters are simple to estimate in comparison to AC profile. Thus DC parameters are recorded under islanding scenario, and processed through proposed adaptive variational mode decomposition which decomposes the signals into intrinsic mode functions. These segregated intrinsic mode functions are further selected optimally by choosing the significant weighted kurtosis index. This optimal selection (maximisation of weighted kurtosis index) is ensured by modified particle swarm optimisation in terms of number of modes (K) and penalty factor (σ). For detection and monitoring (D&M) accurate islanding scenario the significant intrinsic mode functions are subjected to detrended fluctuation analysis, where power exponent (α) values are utilised for correct detection (i.e. distinguishing islanding out of other grid contingencies by two and three dimensional scattering plots). The effectiveness of the proposed D&M for DC micro grid is established in this paper in terms of classification accuracy and relative computational time. The proposed DC side islanding D&M method is less complex (as compared to AC signals) to be implemented. Fastness and accuracy of proposed D&M is established and performed in MATLAB/Simulink platforms.

Fathalla Eldali, Siddharth Suryanarayanan

Supply curtailment in wind energy-rich electricity grids occurs when electric energy supply exceeds demand. Grid-level energy storage assets with the potential for storing the excess electric energy generated from wind are yet cost-prohibitive and prone to inefficiencies. An alternative for managing this excess energy is the targeted charging of available plug-in electric vehicles (PEVs). The different power requirements, load duration, and times of usage requires PEVs to be treated differently. Consequently, using a universal pricing mechanism may not lead to the maximum benefit for the utility and the consumers, especially when trying to rely on charging PEVs with wind energy. In this study, we use a data-driven approach to investigate an existing pricing mechanism for a city (Austin, Texas) in a wind energy-rich electricity grid (ERCOT) and with high projections of PEVs. The study provides a general framework for the wind energy-rich utilities to better evaluate their profitability and the benefits of the consumers. In our case study, the results indicate the need for an alternative pricing mechanism (e.g., time-of-use) dedicated to PEVs than the existing choices for maximizing the utility of available energy from wind in the absence of grid-level energy storage.

Jens Schoene, Muhammad Humayun, Brenden Russell et al.

A common challenge forward-looking utilities are facing when deploying advanced applications that facilitate voltage optimization and service restoration is to provide adequate sensor data for a Distribution System State Estimator (DSSE) so that it provides sufficiently accurate estimates of the system states to enable these applications in an operational environment. We developed a stochastic method that informs telemetry and operational forecasting requirements by quantifying the DSSE performance in supporting advanced applications. The performance metric used is the α risk, which is the likelihood of a DSSE giving a false positive when determining if voltage and loading constraints are met. We applied this method to six real-world industrial/commercial/residential distribution circuits and evaluated α risk improvements provided by circuit-level sensors and operational forecasting. The results show that a combination of sensor deployment schemes was needed to reduce the α risk for undervoltage to effectively zero. Also, sensors deployed at large loads significantly reduce c risks on industrial/commercial circuits while operational forecasting consistently reduces α risks on all circuits. The practical method does not require advanced mathematics and can be readily used by utilities to inform grid modernization investments in sensor technologies so that advanced applications can be executed optimally and violation-free.

Syed A. Raza, Jin Jiang

A benchmark distribution system is developed for investigating control and energy management of distributed generation (DG) at a residential level in the form of three single-phase microgrids. The benchmark is derived from a typical distribution network architecture with common parameters found in North-America systems including wiring specifications, line impedances and connection details for rooftop PV systems. This benchmark system can accommodate microgrids operating in both grid-connected and islanded modes. Within this benchmark, multiple single-phase DG sources located in different phases can be coordinated to form a dynamically balanced three phase system under different load and generation profiles in different phases. The coordination of DG sources in a particular phase is achieved through an intra-phase power management device, while mitigating loads and generation imbalance among all phases are done by an inter-phase power management scheme. It is expected that this benchmark system will facilitate investigation of impacts posed by proliferation of single-phase distributed generation devices and local storage systems in private residences. Three case studies have been carried out to demonstrate the versatility and effectiveness of this benchmark system.