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Smart Grids and Renewables

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (20 November 2022) | Viewed by 15981

Special Issue Editors


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Guest Editor
School of New Energy, Harbin Institute of Technology, Weihai 264209, China
Interests: battery energy storage systems (BESSs); microgrids (MGs); renewable power generation; energy-based (EB) control

E-Mail Website
Guest Editor
School of New Energy, Harbin Institute of Technology at Weihai, Weihai 264209, China
Interests: microgrids (MGs); nonlinear control theory; renewable power generation; energy-based (EB) control

Special Issue Information

Dear Colleagues,

As small green generators, electric vehicles, prosumers, and other adjustable resources are booming on the energy consumption side, the original deterministic distribution network is gradually being transformed into a complex system with high uncertainty. Faced with the unceasing penetration of fragmented and fluctuating adjustable resources in the low-voltage distribution network, how to implement efficient and orderly control of adjustable resource clusters is an urgent problem to be solved. This Special Issue is dedicated to improving the internal vitality and efficiency of the adjustable resource cluster on the energy-consumption side and increasing the value of organizational collaboration. In the future, the collective effect of the division of labor is expected to stabilize the random fluctuations in power consumption on the consumer side, and to absorb the power supply resources on the distribution network side nearby. Moreover, the Special Issue aims to contribute to the development of the energy Internet strategy, which will carry out research on promoting reasonable allocation of energy storage capacity and small, encouraging microresources to participate in power auxiliary services and supporting the in-depth development of the power market reform.

Prof. Dr. Yanbin Qu
Dr. Huihui Song
Guest Editors

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Keywords

  • renewable power generation
  • nonlinear control theory
  • blockchain
  • active distribution networks
  • vivid distribution network

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Published Papers (6 papers)

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Research

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23 pages, 3698 KiB  
Article
Peer-to-Peer Electrical Energy Trading Considering Matching Distance and Available Capacity of Distribution Line
by Natnaree Tubteang and Paramet Wirasanti
Energies 2023, 16(6), 2520; https://doi.org/10.3390/en16062520 - 7 Mar 2023
Cited by 2 | Viewed by 1695
Abstract
The concept of peer-to-peer (P2P) energy trading leads to the flexible energy transaction of prosumers and consumers, for which the P2P business model is normally the main attention. It still requires system operators to address the challenges in trading and constraint problems. In [...] Read more.
The concept of peer-to-peer (P2P) energy trading leads to the flexible energy transaction of prosumers and consumers, for which the P2P business model is normally the main attention. It still requires system operators to address the challenges in trading and constraint problems. In this context, this work regards the congestion constraint in conjunction with energy trading. Firstly, a matching approach based on the cost path is proposed. It is consistent with the cost for the dispatch along each route, making a suitable matching in both distance and bids. In combination with the matching process, the available capacity has to be considered to avoid line congestion. Secondly, the bus transfer factor (BTF) and the partitioning zone approach are proposed to overcome the issue. BTF refers to a response of bus power to the congested line power. The partitioning zone, separated into the source and the load area, enables a simple management strategy. Thereby, the power adjustment in each area follows BTF. Moreover, compensation and opportunity cost are discussed. In comparison with the demand-side reprofiling approach, this work creates more trading chances for buyers and sellers by 24.70% and 30%, respectively. The reason is traders do not have to curtail their power unnecessarily for congestion management. Full article
(This article belongs to the Special Issue Smart Grids and Renewables)
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14 pages, 1622 KiB  
Article
Virtual Inertia Adaptive Control Strategy of ESU in DC Microgrid
by Tao Wang, Hongshan Li, Taiyu Wang, Meng Liu, Tong Zhu and Hongchen Liu
Energies 2022, 15(17), 6112; https://doi.org/10.3390/en15176112 - 23 Aug 2022
Cited by 3 | Viewed by 1594
Abstract
With the increasingly obvious DC characteristics at both ends of the source and load sides of the low-voltage distribution network, the application scenarios of low-voltage DC microgrid gradually appear. Compared with the AC system, the DC microgrid has the characteristics of low inertia, [...] Read more.
With the increasingly obvious DC characteristics at both ends of the source and load sides of the low-voltage distribution network, the application scenarios of low-voltage DC microgrid gradually appear. Compared with the AC system, the DC microgrid has the characteristics of low inertia, weak damping, and poor anti-disturbance capabilities, all of which are important for improving operational stability. A virtual inertia adaptive control approach for fast-tracking energy storage under varied disturbances is presented using energy storage as a virtual inertia unit. Firstly, a stability analysis model including constant power load is constructed for the low-voltage DC microgrid; then, the control logic of the virtual inertia of the energy storage system is designed. Finally, the corresponding model is built in MATLAB/SIMULINK and the experiment platform to verify the correctness and effectiveness of the proposed control strategy. Full article
(This article belongs to the Special Issue Smart Grids and Renewables)
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21 pages, 891 KiB  
Article
A Two-Level Model Predictive Control-Based Approach for Building Energy Management including Photovoltaics, Energy Storage, Solar Forecasting and Building Loads
by Hanieh Agharazi, Marija D. Prica and Kenneth A. Loparo
Energies 2022, 15(10), 3521; https://doi.org/10.3390/en15103521 - 11 May 2022
Cited by 6 | Viewed by 1880
Abstract
This paper uses a two-level model predictive control-based approach for the coordinated control and energy management of an integrated system that includes photovoltaic (PV) generation, energy storage, and building loads. Novel features of the proposed local controller include (1) the ability to simultaneously [...] Read more.
This paper uses a two-level model predictive control-based approach for the coordinated control and energy management of an integrated system that includes photovoltaic (PV) generation, energy storage, and building loads. Novel features of the proposed local controller include (1) the ability to simultaneously manage building loads and energy storage to achieve different operational objectives such as energy efficiency, economic cost efficiency, demand response and grid optimization through the design of specific power trajectory tracking performance functionals, (2) an energy trim function that minimizes the impact of solar forecasting errors on system performance, and (3) the design of a state of charge controller that uses day-ahead forecast of solar power and building loads to intialize energy storage at the start of each day. The local controller is tested in simulation using an exemplary system with PV generation, energy storage and dispatchable building loads. Two sample days with different PV forecasts and multiple case scenarios are considered, and the performance of the algorithm in managing the real and reactive net building load trajectories and the ramp rate of PV injections into the utility network are evaluated. The simulations are based on actual forecasted and measured PV data, and the results show that the local controller meets the tracking requirements for real and reactive power within the operating constraints of the building. Full article
(This article belongs to the Special Issue Smart Grids and Renewables)
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19 pages, 7055 KiB  
Article
Research on Oscillation Suppression Methods in Shunt Active Power Filter System
by Rui Hou, Pengfei Wang, Jian Wu and Dianguo Xu
Energies 2022, 15(9), 3125; https://doi.org/10.3390/en15093125 - 25 Apr 2022
Cited by 5 | Viewed by 1605
Abstract
The shunt active power filter (SAPF) system oscillation is a massive threat to the security and stability of the power grid. This study classifies SAPF oscillation into two categories according to the difference in mechanisms. The SAPF oscillation in one category is caused [...] Read more.
The shunt active power filter (SAPF) system oscillation is a massive threat to the security and stability of the power grid. This study classifies SAPF oscillation into two categories according to the difference in mechanisms. The SAPF oscillation in one category is caused by the resonant characteristics of a switching noise filter and is called external loop amplification. The SAPF oscillation in the other category is induced by the presence of a capacitor in the load current for SAPF and is called self-excited oscillation. Unlike previous studies, this study tried to reveal the internal relationship between the two kinds of SAPF oscillation, present a general shunt virtual-damping-based SAPF oscillation suppression strategy covering the previous resonant damping method, and provide the discrete domain stability criterion of the control system. The sampling frequency was at least six times the resonant frequency. The stability region was enlarged with an increase in the sampling frequency and narrowed with a rise in the resonant frequency. As to the harmful self-excited oscillation problem, this study proposes a composite control strategy combining selective harmonic compensation and grid-side current feedback. Moreover, this study considers the more general resistance–inductance–capacitance load situations and analyzes the stability of the SAPF–Thyristor Switched Capacitor (TSC) hybrid compensation system. Simulations and experiments demonstrated that the proposed compound control method can reduce the primary harmonics of the system by more than 90% and has a better oscillation suppression performance than previous suppression methods. In particular, if we selected the TSC series reactance rate following more than 6%, self-excited oscillation could usually be avoided. Full article
(This article belongs to the Special Issue Smart Grids and Renewables)
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14 pages, 2233 KiB  
Article
Kron Reduction Based on Node Ordering Optimization for Distribution Network Dispatching with Flexible Loads
by Huihui Song, Linkun Han, Yichen Wang, Weifeng Wen and Yanbin Qu
Energies 2022, 15(8), 2964; https://doi.org/10.3390/en15082964 - 18 Apr 2022
Cited by 4 | Viewed by 3811
Abstract
Kron reduction is a general tool of network simplification for flow calculation. With a growing number of flexible loads appearing in distribution networks, traditional Kron reduction cannot be widely used in control and scheduling due to the elimination of controllable and variable load [...] Read more.
Kron reduction is a general tool of network simplification for flow calculation. With a growing number of flexible loads appearing in distribution networks, traditional Kron reduction cannot be widely used in control and scheduling due to the elimination of controllable and variable load buses. Therefore, this paper proposes an improved Kron reduction based on node ordering optimization whose principles guarantee that all the boundary nodes are retained eventually after eliminating the first row and the first column in every step according to the order, thereby making it possible to take full advantage of their potential to meet different requirements in power system calculation and dispatching. The proposed method is verified via simulation models of IEEE 5-bus and 30-bus systems through illustrating the dynamic consistency of the output active power of the generator nodes and the power flow data of preserved nodes before and after reduction. Full article
(This article belongs to the Special Issue Smart Grids and Renewables)
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Review

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15 pages, 1014 KiB  
Review
A Review of Denial of Service Attack and Mitigation in the Smart Grid Using Reinforcement Learning
by Ines Ortega-Fernandez and Francesco Liberati
Energies 2023, 16(2), 635; https://doi.org/10.3390/en16020635 - 5 Jan 2023
Cited by 38 | Viewed by 4228
Abstract
The smart grid merges cyber-physical systems (CPS) infrastructure with information and communication technologies (ICT) to ensure efficient power generation, smart energy distribution in real-time, and optimisation, and it is rapidly becoming the current standard for energy generation and distribution. However, the use of [...] Read more.
The smart grid merges cyber-physical systems (CPS) infrastructure with information and communication technologies (ICT) to ensure efficient power generation, smart energy distribution in real-time, and optimisation, and it is rapidly becoming the current standard for energy generation and distribution. However, the use of ICT has increased the attack surface against the electricity grid, which is vulnerable to a wider range of cyberattacks. In particular, Denial-of-Service (DoS) attacks might impact both the communication network and the cyber-physical layer. DoS attacks have become critical threats against the smart grid due to their ability to impact the normal operation of legitimate smart-grid devices and their ability to target different smart grid systems and applications. This paper presents a comprehensive and methodical discussion of DoS attacks in the smart grid, analysing the most common attack vectors and their effect on the smart grid. The paper also presents a survey of detection and mitigation techniques against DoS attacks in the smart grid using reinforcement learning (RL) algorithms, analysing the strengths and limitations of the current approaches and identifying the prospects for future research. Full article
(This article belongs to the Special Issue Smart Grids and Renewables)
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