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A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (15 November 2020) | Viewed by 14123

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Prof. Dr. Tomonobu Senjyu

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Guest Editor

Department of Electrical and Electronics Engineering, University of the Ryukyus, Nishihara, Okinawa 903-0213, Japan
Interests: high-efficiency energy conversion system; renewable energy in small islands; optimization of power system operation and control
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Special Issue Information

Dear Colleagues,

The Guest Editor is inviting submissions to a Special Issue of Energies in the area of “Electronic Power and Energy Systems”. Optimization and control techniques are important for the efficient use of energy systems. There have been many emerging power and energy system techniques in recent years. Moreover, the Internet of Things (IoT) and Artificial Intelligence (AI) are also interesting topics for power and energy researchers.
This Special Issue will deal with novel optimization and control techniques for power and energy systems. Topics of interest for publication include but are not limited to:

power system control;
optimization of operation of power systems;
electric distributed systems;
energy storage systems;
energy management systems;
application of IoT and/or AI for power systems;
control method of power electronics;
optimal operation of renewable energy;
demand side management;
voltage stability and optimal line flow analysis.

Prof. Dr. Tomonobu Senjyu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Keywords

power electronics
power systems
energy systems
optimization techniques
control methods
energy storage systems
renewable energy
IoT
AI

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Published Papers (5 papers)

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Research

18 pages, 1780 KiB

Open AccessArticle

Zero Average Surface Controlled Boost-Flyback Converter

by Juan-Guillermo Muñoz, Fabiola Angulo and David Angulo-Garcia

Energies 2021, 14(1), 57; https://doi.org/10.3390/en14010057 - 24 Dec 2020

Cited by 5 | Viewed by 2123

Abstract

The boost-flyback converter is a DC-DC step-up power converter with a wide range of technological applications. In this paper, we analyze the boost-flyback dynamics when controlled via a modified Zero-Average-Dynamics control technique, hereby named Zero-Average-Surface (ZAS). While using the ZAS strategy, it is possible to calculate the duty cycle at each PWM cycle that guarantees a desired stable period-1 solution, by forcing the system to evolve in such way that a function that is constructed with strategical combination of the states over the PWM period has a zero average. We show, by means of bifurcation diagrams, that the period-1 orbit coexists with a stable period-2 orbit with a saturated duty cycle. While using linear stability analysis, we demonstrate that the period-1 orbit is stable over a wide range of parameters and it loses stability at high gains and low loads via a period doubling bifurcation. Finally, we show that, under the right choice of parameters, the period-1 orbit controller with ZAS strategy satisfactorily rejects a wide range of disturbances. Full article

(This article belongs to the Special Issue Electronic Power and Energy Systems)

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27 pages, 9063 KiB

Open AccessArticle

Integrated Algorithm for Selecting the Location and Control of Energy Storage Units to Improve the Voltage Level in Distribution Grids

by Agata Szultka, Seweryn Szultka, Stanislaw Czapp, Zbigniew Lubosny and Robert Malkowski

Energies 2020, 13(24), 6720; https://doi.org/10.3390/en13246720 - 19 Dec 2020

Cited by 6 | Viewed by 2631

Abstract

This paper refers to the issue that mainly appears in distribution grids, where renewable energy sources (RES) are widely installed. In such grids, one of the main problems is the coordination of energy production time with demand time, especially if photovoltaic energy sources are present. To face this problem, battery energy storage units (ESU) can be installed. In recent years, more and more attention has been paid to optimizing the use of ESU. This paper contains a simple description of available solutions for the application of ESU as well as an original proposal for selecting the optimal location and control of ESU. The ESU selection method is based on the use of a genetic algorithm and the ESU control method utilizes the fuzzy logic. The combination of the aforementioned methods/algorithms of ESU application is named an integrated algorithm. The performance of the proposed algorithm was validated by multivariate computer simulations with the use of the real low-voltage grid model. The DIgSILENT PowerFactory environment was employed to develop the simulation model of the integrated algorithm. The proposal was utilized to improve the voltage level in the distribution grid and to install the optimal number of ESU. Based on daily load variations for selected load profiles, it was shown that after the ESU application the voltage deviations in the analyzed network were significantly limited. Moreover, the analysis proves that both the location of ESU in the grid and the control of their active and reactive power are important from the point of view of reducing overall costs. Full article

(This article belongs to the Special Issue Electronic Power and Energy Systems)

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16 pages, 5609 KiB

Open AccessArticle

Improved Weighted k-Nearest Neighbor Based on PSO for Wind Power System State Recognition

by Chun-Yao Lee, Kuan-Yu Huang, Yi-Xing Shen and Yao-Chen Lee

Energies 2020, 13(20), 5520; https://doi.org/10.3390/en13205520 - 21 Oct 2020

Cited by 10 | Viewed by 2292

Abstract

In this paper, we propose using particle swarm optimization (PSO) which can improve weighted k-nearest neighbors (PWKNN) to diagnose the failure of a wind power system. PWKNN adjusts weight to correctly reflect the importance of features and uses the distance judgment strategy to figure out the identical probability of multi-label classification. The PSO optimizes the weight and parameter k of PWKNN. This testing is based on four classified conditions of the 300 W wind generator which include healthy, loss of lubrication in the gearbox, angular misaligned rotor, and bearing fault. Current signals are used to measure the conditions. This testing tends to establish a feature database that makes up or trains classifiers through feature extraction. Not lowering the classification accuracy, the correlation coefficient of feature selection is applied to eliminate irrelevant features and to diminish the runtime of classifiers. A comparison with other traditional classifiers, i.e., backpropagation neural network (BPNN), k-nearest neighbor (k-NN), and radial basis function network (RBFN) shows that PWKNN has a higher classification accuracy. The feature selection can diminish the average features from 16 to 2.8 and can reduce the runtime by 61%. This testing can classify these four conditions accurately without being affected by noise and it can reach an accuracy of 83% in the condition of signal-to-noise ratio (SNR) is 20dB. The results show that the PWKNN approach is capable of diagnosing the failure of a wind power system. Full article

(This article belongs to the Special Issue Electronic Power and Energy Systems)

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22 pages, 547 KiB

Open AccessArticle

Optimal Sizing of a Real Remote Japanese Microgrid with Sea Water Electrolysis Plant Under Time-Based Demand Response Programs

by Mahmoud M. Gamil, Makoto Sugimura, Akito Nakadomari, Tomonobu Senjyu, Harun Or Rashid Howlader, Hiroshi Takahashi and Ashraf M. Hemeida

Energies 2020, 13(14), 3666; https://doi.org/10.3390/en13143666 - 16 Jul 2020

Cited by 19 | Viewed by 3434

Abstract

Optimal sizing of power systems has a tremendous effective role in reducing the total system cost by preventing unneeded investment in installing unnecessary generating units. This paper presents an optimal sizing and planning strategy for a completely hybrid renewable energy power system in a remote Japanese island, which is composed of photovoltaic (PV), wind generators (WG), battery energy storage system (BESS), fuel cell (FC), seawater electrolysis plant, and hydrogen tank. Demand response programs are applied to overcome the performance variance of renewable energy systems (RESs) as they offer an efficient solution for many problems such as generation cost, high demand peak to average ratios, and assist grid reliability during peak load periods. Real-Time Pricing (RTP), which is deployed in this work, is one of the main price-based demand response groups used to regulate electricity consumption of consumers. Four case studies are considered to confirm the robustness and effectiveness of the proposed schemes. Mixed-Integer Linear Programming (MILP) is utilized to optimize the size of the system’s components to decrease the total system cost and maximize the profits at the same time. Full article

(This article belongs to the Special Issue Electronic Power and Energy Systems)

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13 pages, 776 KiB

Open AccessArticle

Output Control of Three-Axis PMSG Wind Turbine Considering Torsional Vibration Using H Infinity Control

by Kosuke Takahashi, Nyam Jargalsaikhan, Shriram Rangarajan, Ashraf Mohamed Hemeida, Hiroshi Takahashi and Tomonobu Senjyu

Energies 2020, 13(13), 3474; https://doi.org/10.3390/en13133474 - 5 Jul 2020

Cited by 19 | Viewed by 2646

Abstract

Due to changes in wind, the torque obtained from the wind turbine always fluctuates. Here, the wind turbine and the rotor of the generator are connected by a shaft that is one elastic body, and each rotating body has different inertia. The difference in inertia between the wind turbine and the generator causes a torsion between the wind generator and the generator; metal fatigue and torsion can damage the shaft. Therefore, it is necessary to consider the axial torsional vibration suppression of a geared wind power generator using a permanent magnet synchronous generator (PMSG). In addition, errors in axis system parameters occur due to long-term operation of the generator, and it is important to estimate for accurate control. In this paper, we propose torque estimation using

H_{\infty}

observer and axial torsional vibration suppression control in a three inertia system. The

H_{\infty}

controller is introduced into the armature current control system (q-axis current control system) of the wind power generator. Even if parameter errors and high-frequency disturbances are included, the shaft torsional torque is estimated by the

H_{\infty}

observer that can perform robust estimation. Moreover, by eliminating the resonance point of the shaft system, vibration suppression of the shaft torsional torque is achieved. The results by the proposed method can suppress axial torsional vibration and show the effect better than the results using Proportional-Integral (PI) control. Full article

(This article belongs to the Special Issue Electronic Power and Energy Systems)

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