Energies

2023

Jump to: 2022, 2021

20 pages, 1460 KiB

Open AccessReview

A Survey on Hybrid SCADA/WAMS State Estimation Methodologies in Electric Power Transmission Systems

by Orestis Darmis and George Korres

Energies 2023, 16(2), 618; https://doi.org/10.3390/en16020618 - 4 Jan 2023

Cited by 11 | Viewed by 2892

Abstract

State estimation (SE) is an essential tool of energy management systems (EMS), providing power system operators with an overall grasp of the actual power system operating conditions and aiding them in sustaining reliable and secure operation of the grid. In modern transmission sectors, [...] Read more.

State estimation (SE) is an essential tool of energy management systems (EMS), providing power system operators with an overall grasp of the actual power system operating conditions and aiding them in sustaining reliable and secure operation of the grid. In modern transmission sectors, two main measurement systems are deployed, namely the supervisory control and data acquisition (SCADA) and the wide area monitoring systems (WAMS). The multiple advantages of augmenting conventional SCADA-based SE algorithms with synchrophasor measurements from WAMS are already well-established; thus, an abundance of different methodologies has been reported in the field of hybrid SE (HSE). Under this premise, this paper provides a thorough literature review of novel HSE methods in transmission systems and proposes a classification based on the scope and mathematical modeling of each method. Following a brief introduction to the concept of SE based on WAMS and SCADA measurements, an insight into the main challenges emerging in HSE implementations is provided. Various HSE methods which overcome these challenges are reviewed, for both static and dynamic SE implementations. In conclusion, the research trends in the area of HSE are summarized, and the main findings of this literature review are discussed. Full article

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2022

Jump to: 2023, 2021

16 pages, 557 KiB

Open AccessArticle

Optimal Management of Energy Communities Hosting a Fleet of Electric Vehicles

by Giovanni Gino Zanvettor, Marco Casini, Antonio Giannitrapani, Simone Paoletti and Antonio Vicino

Energies 2022, 15(22), 8697; https://doi.org/10.3390/en15228697 - 19 Nov 2022

Cited by 5 | Viewed by 1333

Abstract

In this paper, we study the problem of managing an energy community hosting a fleet of electric vehicles for rent. On the day ahead, service requests for electric vehicles are submitted to the community. Then, the optimal request-to-vehicle assignment has to be found, [...] Read more.

In this paper, we study the problem of managing an energy community hosting a fleet of electric vehicles for rent. On the day ahead, service requests for electric vehicles are submitted to the community. Then, the optimal request-to-vehicle assignment has to be found, as well as the optimal charging schedule of vehicle batteries. A suitable model is presented and included in an existing energy community architecture. The overall community management problem is formulated as a bi-level model, featuring two nested optimization problems. The optimal request-to-vehicle assignment requires the solution of a mixed-integer linear program. To reduce the computational complexity, a heuristic solution to the assignment problem is presented. Numerical results show that participation in the community grants a remarkable reduction in the electric vehicle charging cost. The adoption of the heuristic assignment solution provides a dramatic reduction in the computation time required to solve the bi-level model. At the same time, the level of suboptimality introduced appears to be negligible, being less than 1% in most of the considered cases. Full article

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23 pages, 1897 KiB

Open AccessReview

Sub Synchronous Oscillations under High Penetration of Renewables—A Review of Existing Monitoring and Damping Methods, Challenges, and Research Prospects

by Uvini Perera, Amanullah Maung Than Oo and Ramon Zamora

Energies 2022, 15(22), 8477; https://doi.org/10.3390/en15228477 - 13 Nov 2022

Cited by 13 | Viewed by 3510

Abstract

With the recent developments in renewable energy generation and addition of power electronic devices, power system dynamics have become extremely complex. One of the challenges faced due to this transition is the sub synchronous oscillations caused by the interaction of renewable energy sources [...] Read more.

With the recent developments in renewable energy generation and addition of power electronic devices, power system dynamics have become extremely complex. One of the challenges faced due to this transition is the sub synchronous oscillations caused by the interaction of renewable energy sources and various components of the power grid. Recently reported incidents due to sub synchronous oscillations highlight the need of monitoring and suppression of these harmful oscillations in real time. This paper gives an overview of the phenomena of sub synchronous oscillations and discusses the existing monitoring and damping techniques along with their limitations. Further, it highlights the research trends along this path. Full article

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16 pages, 2217 KiB

Open AccessArticle

A Fast Power Calculation Algorithm for Three-Phase Droop-Controlled-Inverters Using Combined SOGI Filters and Considering Nonlinear Loads

by Mingshen Li, Jose Matas, Jorge El Mariachet, Carlos Gustavo C. Branco and Josep M. Guerrero

Energies 2022, 15(19), 7360; https://doi.org/10.3390/en15197360 - 7 Oct 2022

Cited by 3 | Viewed by 1993

Abstract

The power calculation is an indispensable element in droop-controlled inverters because the bandwidth of the measured power has a direct impact on the controller performance. This paper proposes a fast and accurate power calculation algorithm based on the combined Second Order Generalized Integrator [...] Read more.

The power calculation is an indispensable element in droop-controlled inverters because the bandwidth of the measured power has a direct impact on the controller performance. This paper proposes a fast and accurate power calculation algorithm based on the combined Second Order Generalized Integrator (SOGI) filters in stationary coordinates for a three-phase system, which takes into consideration the use of nonlinear loads. The power calculation scheme is formed by the two-stage SOGI filters that are employed for obtaining the active and reactive powers required to perform a droop-based inverter operation, respectively. From the two-stage structure, the first SOGI is used as a band-pass filter (BPF) for filtering harmonics and obtaining the fundamental current of the nonlinear load; The second SOGI is used as a low-pass filter (LPF) for extracting the DC-component, which corresponds with the average power. A small-signal model of a two droop-controlled inverters system is built to obtain the dynamical response and stability margin of the system. And compared it with the dynamical behaviour of a standard droop-control method. Next, the proposed power calculation system is designed in order to achieve the same ripple amplitude voltage as that obtained with the standard droop-control method by adjusting the bandwidth gains. Through simulation and hardware in the loop (HIL) validation, the proposed approach presents a faster and more accurate performance when sharing nonlinear loads, and also drives the inverters’ output voltage with lower distortion. Full article

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2021

Jump to: 2023, 2022

15 pages, 833 KiB

Open AccessArticle

On the Use of Robust Techniques in Smart Grid Control

by Giuseppe Fusco

Energies 2022, 15(1), 7; https://doi.org/10.3390/en15010007 - 21 Dec 2021

Cited by 4 | Viewed by 2080

Abstract

This paper discusses the application of robust control techniques to a smart grid (SG) in order to find more powerful and suitable control tools to guarantee SG robustness. Two key aspects are in particular discussed. The first one relates to the need of [...] Read more.

This paper discusses the application of robust control techniques to a smart grid (SG) in order to find more powerful and suitable control tools to guarantee SG robustness. Two key aspects are in particular discussed. The first one relates to the need of a suitably model for the SG. The second one relates to the selection of an appropriate robust control technique to guarantee rejection of the adverse effects caused by mutual interactions among control loops and model uncertainty. The final purpose is to bridge the gap between the power of robust control theorems and the reality of SG operations. Full article

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17 pages, 2184 KiB

Open AccessArticle

Optimal Control of Plug-In Electric Vehicles Charging for Composition of Frequency Regulation Services

by Roberto Germanà, Francesco Liberati, Emanuele De Santis, Alessandro Giuseppi, Francesco Delli Priscoli and Alessandro Di Giorgio

Energies 2021, 14(23), 7879; https://doi.org/10.3390/en14237879 - 24 Nov 2021

Cited by 5 | Viewed by 1716

Abstract

This paper presents a novel control system for the participation of plug-in electric vehicles (PEVs) in the provisioning of ancillary services for frequency regulation, in a way that is transparent to the driver and harmonized with the smart charging service requirements. Given a [...] Read more.

This paper presents a novel control system for the participation of plug-in electric vehicles (PEVs) in the provisioning of ancillary services for frequency regulation, in a way that is transparent to the driver and harmonized with the smart charging service requirements. Given a power-frequency droop curve, which specifies how the set of PEVs collectively participate to the provisioning of the frequency regulation service (we call this curve a “global” droop curve), we propose an algorithm to compute “local” droop curves (one for each PEV), which are optimized according to the current status of the PEV and the current progress of the smart recharging session. Once aggregated, the local droop curves match the global one (so that the PEVs contribute as expected to the provisioning of the ancillary service). One innovative aspect of the proposed algorithm is that it is specifically designed to be interoperable with the algorithms that control the PEV recharging process; hence, it is transparent to the PEV drivers. Simulation results are presented to validate the proposed solution. Full article

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27 pages, 5656 KiB

Open AccessArticle

An Online Security Prediction and Control Framework for Modern Power Grids

by Ifedayo Oladeji, Ramon Zamora and Tek Tjing Lie

Energies 2021, 14(20), 6639; https://doi.org/10.3390/en14206639 - 14 Oct 2021

Cited by 10 | Viewed by 1953

Abstract

The proliferation of renewable energy sources distributed generation (RES-DG) into the grid results in time-varying inertia constant. To ensure the security of the grid under varying inertia, techniques for fast security assessment are required. In addition, considering the high penetration of RES-DG units [...] Read more.

The proliferation of renewable energy sources distributed generation (RES-DG) into the grid results in time-varying inertia constant. To ensure the security of the grid under varying inertia, techniques for fast security assessment are required. In addition, considering the high penetration of RES-DG units into the modern grids, security prediction using varying grid features is crucial. The computation burden concerns of conventional time-domain security assessment techniques make it unsuitable for real-time security prediction. This paper, therefore, proposes a fast security monitoring model that includes security prediction and load shedding for security control. The attributes considered in this paper include the load level, inertia constant, fault location, and power dispatched from the renewable energy sources generator. An incremental Naïve Bayes algorithm is applied on the training dataset developed from the responses of the grid to transient stability simulations. An additive Gaussian process regression (GPR) model is proposed to estimate the load shedding required for the predicted insecure states. Finally, an algorithm based on the nodes’ security margin is proposed to determine the optimal node (s) for the load shedding. The average security prediction and load shedding estimation model training times are 1.2 s and 3 s, respectively. The result shows that the proposed model can predict the security of the grid, estimate the amount of load shed required, and determine the specific node for load shedding operation. Full article

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24 pages, 1258 KiB

Open AccessArticle

A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration

by A.S. Jameel Hassan, Umar Marikkar, G.W. Kasun Prabhath, Aranee Balachandran, W.G. Chaminda Bandara, Parakrama B. Ekanayake, Roshan I. Godaliyadda and Janaka B. Ekanayake

Energies 2021, 14(20), 6596; https://doi.org/10.3390/en14206596 - 13 Oct 2021

Cited by 3 | Viewed by 2696

Abstract

The occurrence of voltage violations is a major deterrent for absorbing more rooftop solar power into smart Low-Voltage Distribution Grids (LVDGs). Recent studies have focused on decentralized control methods to solve this problem due to the high computational time in performing load flows [...] Read more.

The occurrence of voltage violations is a major deterrent for absorbing more rooftop solar power into smart Low-Voltage Distribution Grids (LVDGs). Recent studies have focused on decentralized control methods to solve this problem due to the high computational time in performing load flows in centralized control techniques. To address this issue, a novel sensitivity matrix was developed to estimate the voltages of the network by replacing load flow simulations. In this paper, a Centralized Active, Reactive Power Management System (CARPMS) is proposed to optimally utilize the reactive power capability of smart Photovoltaic (PV) inverters with minimal active power curtailment to mitigate the voltage violation problem. The developed sensitivity matrix is able to reduce the time consumed by 55.1% compared to load flow simulations, enabling near-real-time control optimization. Given the large solution space of power systems, a novel two-stage optimization is proposed, where the solution space is narrowed down by a Feasible Region Search (FRS) step, followed by Particle Swarm Optimization (PSO). The failure of standalone PSO to converge to a feasible solution for 34% of the scenarios evaluated further validates the necessity of the two-stage optimization using FRS. The performance of the proposed methodology was analysed in comparison to the load flow method to demonstrate the accuracy and the capability of the optimization algorithm to mitigate voltage violations in near-real time. The deviations of the mean voltages of the proposed methodology from the load flow method were:

6.5 \times 10^{- 3}

p.u for reactive power control using Q-injection,

1.02 \times 10^{- 2}

p.u for reactive power control using Q-absorption, and 0 p.u for active power curtailment case. Full article

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41 pages, 4211 KiB

Open AccessEditor’s ChoiceReview

Power Quality Phenomena, Standards, and Proposed Metrics for DC Grids

by Andrea Mariscotti

Energies 2021, 14(20), 6453; https://doi.org/10.3390/en14206453 - 9 Oct 2021

Cited by 38 | Viewed by 4192

Abstract

This work addresses the problem of power quality (PQ) metrics (or indexes) suitable for DC grids, encompassing low and medium voltage applications, including electric transports, all-electric ships and aircrafts, electric vehicles, distributed generation and microgrids, modern data centers, etc. The two main pillars [...] Read more.

This work addresses the problem of power quality (PQ) metrics (or indexes) suitable for DC grids, encompassing low and medium voltage applications, including electric transports, all-electric ships and aircrafts, electric vehicles, distributed generation and microgrids, modern data centers, etc. The two main pillars on which such PQ indexes are discussed and built are: (i) the physical justification, so the electric phenomena affecting DC grids and components (PV panels, fuel cells, capacitors, batteries, etc.), causing, e.g., stress of materials, aging, distortion, grid instability; and (ii) the existing standardization framework, pointing out desirable coverage and extension, similarity with AC grids standards, but also inconsistencies. For the first point, each phenomenon is discussed with quantitative conclusions on relevant thresholds: in many cases some percentage of distortion (ripple) is acceptable (stress on capacitors and storage, impact on fuel cells, and PV panels), whereas in other cases, much higher levels may be tolerated (interference to protection and monitoring devices). Standards are reviewed for indications not only of low-order harmonics and voltage fluctuations typical of old DC grid schemes, but also for high-frequency noise, including thus supraharmonics and common-mode disturbance, and filling the gap with the electromagnetic compatibility domain. However, phenomena typical of EMC and electrical safety (such as various types of overvoltages and fast transients) are excluded. Suitable PQ indexes are then reviewed, suggesting integrations and modifications, to cover the relevant phenomena and technological progress, and to better follow the normative exigencies: ripple is considered in time and frequency domain, in particular with a band limited implementation; for transients and pulsed loads, more traditional indexes based on area, energy, and half duration are confronted with indexes evaluating the power trajectory and its derivative. Full article

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12 pages, 2721 KiB

Open AccessArticle

Load Profile-Based Residential Customer Segmentation for Analyzing Customer Preferred Time-of-Use (TOU) Tariffs

by Minseok Jang, Hyun-Cheol Jeong, Taegon Kim and Sung-Kwan Joo

Energies 2021, 14(19), 6130; https://doi.org/10.3390/en14196130 - 26 Sep 2021

Cited by 18 | Viewed by 3953

Abstract

Smart meters and dynamic pricing are key factors in implementing a smart grid. Dynamic pricing is one of the demand-side management methods that can shift demand from on-peak to off-peak. Furthermore, dynamic pricing can help utilities reduce the investment cost of a power [...] Read more.

Smart meters and dynamic pricing are key factors in implementing a smart grid. Dynamic pricing is one of the demand-side management methods that can shift demand from on-peak to off-peak. Furthermore, dynamic pricing can help utilities reduce the investment cost of a power system by charging different prices at different times according to system load profile. On the other hand, a dynamic pricing strategy that can satisfy residential customers is required from the customer’s perspective. Residential load profiles can be used to comprehend residential customers’ preferences for electricity tariffs. In this study, in order to analyze the preference for time-of-use (TOU) rates of Korean residential customers through residential electricity consumption data, a representative load profile for each customer can be found by utilizing the hourly consumption of median. In the feature extraction stage, six features that can explain the customer’s daily usage patterns are extracted from the representative load profile. Korean residential load profiles are clustered into four groups using a Gaussian mixture model (GMM) with Bayesian information criterion (BIC), which helps find the optimal number of groups, in the clustering stage. Furthermore, a choice experiment (CE) is performed to identify Korean residential customers’ preferences for TOU with selected attributes. A mixed logit model with a Bayesian approach is used to estimate each group’s customer preference for attributes of a time-of-use (TOU) tariff. Finally, a TOU tariff for each group’s load profile is recommended using the estimated part-worth. Full article

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23 pages, 8456 KiB

Open AccessArticle

Optimal Sizing of Battery-Integrated Hybrid Renewable Energy Sources with Ramp Rate Limitations on a Grid Using ALA-QPSO

by Ramakrishna S. S. Nuvvula, Devaraj Elangovan, Kishore Srinivasa Teegala, Rajvikram Madurai Elavarasan, Md. Rabiul Islam and Ravikiran Inapakurthi

Energies 2021, 14(17), 5368; https://doi.org/10.3390/en14175368 - 28 Aug 2021

Cited by 11 | Viewed by 2513

Abstract

Higher penetration of variable renewable energy sources into the grid brings down the plant load factor of thermal power plants. However, during sudden changes in load, the thermal power plants support the grid, though at higher ramping rates and with inefficient operation. Hence, [...] Read more.

Higher penetration of variable renewable energy sources into the grid brings down the plant load factor of thermal power plants. However, during sudden changes in load, the thermal power plants support the grid, though at higher ramping rates and with inefficient operation. Hence, further renewable additions must be backed by battery energy storage systems to limit the ramping rate of a thermal power plant and to avoid deploying diesel generators. In this paper, battery-integrated renewable energy systems that include floating solar, bifacial rooftop, and wind energy systems are evaluated for a designated smart city in India to reduce ramping support by a thermal power plant. Two variants of adaptive-local-attractor-based quantum-behaved particle swarm optimization (ALA-QPSO) are applied for optimal sizing of battery-integrated and hybrid renewable energy sources to minimize the levelized cost of energy (LCoE), battery life cycle loss (LCL), and loss of power supply probability (LPSP). The obtained results are then compared with four variants of differential evolution. The results show that out of 427 MW of the energy potential, an optimal set of hybrid renewable energy sources containing 274 MW of rooftop PV, 99 MW of floating PV, and 60 MW of wind energy systems supported by 131 MWh of batteries results in an LPSP of 0.005%, an LCoE of 0.077 USD/kW, and an LCL of 0.0087. A sensitivity analysis of the results obtained through ALA-QPSO is performed to assess the impact of damage to batteries and unplanned load appreciation, and it is found that the optimal set results in more energy sustainability. Full article

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19 pages, 2028 KiB

Open AccessArticle

Spatio-Temporal and Power–Energy Scheduling of Mobile Battery Storage for Mitigating Wind and Solar Energy Curtailment in Distribution Networks

by Hedayat Saboori, Shahram Jadid and Mehdi Savaghebi

Energies 2021, 14(16), 4853; https://doi.org/10.3390/en14164853 - 9 Aug 2021

Cited by 8 | Viewed by 2116

Abstract

Several technical, computational, and economic barriers have caused curtailing a share of renewable-based power generation, especially in systems with higher penetration levels. The Mobile Battery Energy Storage (MBES) can cope with this problem considering the spatial and temporal distribution of the curtailed energy. [...] Read more.

Several technical, computational, and economic barriers have caused curtailing a share of renewable-based power generation, especially in systems with higher penetration levels. The Mobile Battery Energy Storage (MBES) can cope with this problem considering the spatial and temporal distribution of the curtailed energy. Accordingly, a new operation model is proposed for optimal scheduling of the MBES in a distribution network with wind and photovoltaic (PV) resources. The network experiences curtailment situations because of bus overvoltage, feeder overload, and power over-generation. The MBES is a truck-mounted battery system compacted in a container. The proposed model seeks to determine the optimal spatio-temporal and power–energy status of the MBES to achieve a minimum curtailment ratio. The model considers transportation time and cost of the MBES efficiently while both active and reactive power exchanges are modeled. The model is linear, without convergence and optimality problems, applicable to real-life large-scale networks, and can be easily integrated into the commercial distribution management software. The implementation results on a test system demonstrate its functionality to recover a considerable share of the curtailed energy for both wind and PV resources at all curtailment patterns and scenarios. Full article

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24 pages, 1230 KiB

Open AccessArticle

Augmented Power Dispatch for Resilient Operation through Controllable Series Compensation and N-1-1 Contingency Assessment

by Liping Huang, Zhaoxiong Huang, Chun Sing Lai, Guangya Yang, Zhuoli Zhao, Ning Tong, Xiaomei Wu and Loi Lei Lai

Energies 2021, 14(16), 4756; https://doi.org/10.3390/en14164756 - 5 Aug 2021

Cited by 2 | Viewed by 1899

Abstract

Research on enhancing power system resilience against extreme events is attracting significant attention and becoming a top global agenda. In this paper, a preventive augmented power dispatch model is proposed to provide a resilient operation. In the proposed model, a new N-1-1 security [...] Read more.

Research on enhancing power system resilience against extreme events is attracting significant attention and becoming a top global agenda. In this paper, a preventive augmented power dispatch model is proposed to provide a resilient operation. In the proposed model, a new N-1-1 security criterion is proposed to select disruptive N-1-1 contingency cases that might trigger cascading blackouts, and an iterative contingency assessment process based on the line outage distribution factor is proposed to deal with security constraints. In terms of optimization objectives, two objectives related to power flow on the transmission line are considered to reduce the possibility of overload outages. Controllable series compensation devices are also considered in the model to improve the power flow distribution. Case studies conducted on the modified IEEE 30-bus, 118-bus and Polish 2382-bus systems show that the power flow solution of the proposed power dispatch model can avoid some branches from undertaking excessively heavy loads, especially lines forecasted to be affected by extreme events. The results of blackout simulations through a hidden failure cascading outage simulation model show that the average power losses of the proposed model are reduced by around 40% in some cases as compared to the classical economic dispatch model. Full article

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28 pages, 6697 KiB

Open AccessArticle

Techno-Economic Planning and Operation of the Microgrid Considering Real-Time Pricing Demand Response Program

by Zi-Xuan Yu, Meng-Shi Li, Yi-Peng Xu, Sheraz Aslam and Yuan-Kang Li

Energies 2021, 14(15), 4597; https://doi.org/10.3390/en14154597 - 29 Jul 2021

Cited by 45 | Viewed by 3867

Abstract

The optimal planning of grid-connected microgrids (MGs) has been extensively studied in recent years. While most of the previous studies have used fixed or time-of-use (TOU) prices for the optimal sizing of MGs, this work introduces real-time pricing (RTP) for implementing a demand [...] Read more.

The optimal planning of grid-connected microgrids (MGs) has been extensively studied in recent years. While most of the previous studies have used fixed or time-of-use (TOU) prices for the optimal sizing of MGs, this work introduces real-time pricing (RTP) for implementing a demand response (DR) program according to the national grid prices of Iran. In addition to the long-term planning of MG, the day-ahead operation of MG is also analyzed to get a better understanding of the DR program for daily electricity dispatch. For this purpose, four different days corresponding to the four seasons are selected for further analysis. In addition, various impacts of the proposed DR program on the MG planning results, including sizing and best configuration, net present cost (NPC) and cost of energy (COE), and emission generation by the utility grid, are investigated. The optimization results show that the implementation of the DR program has a positive impact on the technical, economic, and environmental aspects of MG. The NPC and COE are reduced by about USD 3700 and USD 0.0025/kWh, respectively. The component size is also reduced, resulting in a reduction in the initial cost. Carbon emissions are also reduced by 185 kg/year. Full article

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20 pages, 23635 KiB

Open AccessArticle

Dynamics Analysis Using Koopman Mode Decomposition of a Microgrid Including Virtual Synchronous Generator-Based Inverters

by Yuko Hirase, Yuki Ohara, Naoya Matsuura and Takeaki Yamazaki

Energies 2021, 14(15), 4581; https://doi.org/10.3390/en14154581 - 28 Jul 2021

Cited by 5 | Viewed by 2629

Abstract

In the field of microgrids (MGs), steady-state power imbalances and frequency/voltage fluctuations in the transient state have been gaining prominence owing to the advancing distributed energy resources (DERs) connected to MGs via grid-connected inverters. Because a stable, safe power supply and demand must [...] Read more.

In the field of microgrids (MGs), steady-state power imbalances and frequency/voltage fluctuations in the transient state have been gaining prominence owing to the advancing distributed energy resources (DERs) connected to MGs via grid-connected inverters. Because a stable, safe power supply and demand must be maintained, accurate analyses of power system dynamics are crucial. However, the natural frequency components present in the dynamics make analyses complex. The nonlinearity and confidentiality of grid-connected inverters also hinder controllability. The MG considered in this study consisted of a synchronous generator (the main power source) and multiple grid-connected inverters with storage batteries and virtual synchronous generator (VSG) control. Although smart inverter controls such as VSG contribute to system stabilization, they induce system nonlinearity. Therefore, Koopman mode decomposition (KMD) was utilized in this study for consideration as a future method of data-driven analysis of the measured frequencies and voltages, and a frequency response analysis of the power system dynamics was performed. The Koopman operator is a linear operator on an infinite dimensional space, whereas the original dynamics is a nonlinear map on a finite state space. In other words, the proposed method can precisely analyze all the dynamics of the power system, which involve the complex nonlinearities caused by VSGs. Full article

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45 pages, 3299 KiB

Open AccessReview

Optimal Sizing and Energy Management of Microgrids with Vehicle-to-Grid Technology: A Critical Review and Future Trends

by Oussama Ouramdane, Elhoussin Elbouchikhi, Yassine Amirat and Ehsan Sedgh Gooya

Energies 2021, 14(14), 4166; https://doi.org/10.3390/en14144166 - 10 Jul 2021

Cited by 67 | Viewed by 6168

Abstract

The topic of microgrids (MGs) is a fast-growing and very promising field of research in terms of energy production quality, pollution reduction and sustainable development. Moreover, MGs are, above all, designed to considerably improve the autonomy, sustainability, and reliability of future electrical distribution [...] Read more.

The topic of microgrids (MGs) is a fast-growing and very promising field of research in terms of energy production quality, pollution reduction and sustainable development. Moreover, MGs are, above all, designed to considerably improve the autonomy, sustainability, and reliability of future electrical distribution grid. At the same time, aspects of MGs energy management, taking into consideration distribution generation systems, energy storage devices, electric vehicles, and consumption components have been widely investigated. Besides, grid architectures including DC, AC, or hybrid power generation systems, energy dispatching problems modelling, operating modes (islanded or grid connected), MGs sizing, simulations and problems solving optimization approaches, and other aspects, have been raised as topics of great interest for both electrical and computer sciences research communities. Furthermore, the United Nations Framework Convention on Climate Change and government policies and incentives have paved the way to massive electric vehicle (EV) deployment. Hence, several research studies have been conducted to investigate the integration of EVs in national power grid and future MGs. Specifically, EV charging stations’ bi-directional power flow control and energy management have been considerably explored. These issues index challenging research topics, which are in most cases still under progress. This paper gives an overview of MGs technology advancement in recent decades, taking into consideration distributed energy generation (DER), energy storage systems (ESS), EVs, and loads. It reviews the main MGs architecture, operating modes, sizing and energy management systems (EMS) and EVs integration. Full article

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