Smart Solutions of Distributed Energy Systems: Design, Operation, and Application

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: closed (15 February 2022) | Viewed by 22453

Special Issue Editor

Department of Electrical and Electronic Engineering, Hanseo University, Chungcheongnam-do 31962, Korea
Interests: network management; green IT; smart grid; smart energy community; smart city
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Energy networks are large, heterogeneous, complex networks that include heat, water, and electricity. The energy sector has been introducing new elements and technologies due to the increasing impact of climate change, increasing the operational complexity of energy networks, and reducing their reliability and stability. The increase in uncertainty associated with human behavior, as well as natural phenomena, such as renewables, makes this more difficult. Fortunately, big data collection and real-time control through ICT can alleviate this difficulty.

 

This Special Issue on ‘Smart Solutions of Distributed Energy Systems: Design, Operation, and Application’ focuses on efficient solutions for energy systems with newly introduced environments and technologies. It covers not only the system design for distributed systems, virtual power plants, and microgrids, but also its operation and application, including distributed/decentralized energy transaction and market. It covers academic and industrial activities, addressing the state of the art, theory, and practice in energy systems.

Assoc. Prof. Dr. Eunsung Oh
Guest Editor

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Keywords

  • Renewable energy
  • Virtual power plant
  • Microgrid
  • Peer-to-peer
  • Market

Published Papers (8 papers)

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Research

14 pages, 4216 KiB  
Article
Dynamic Virtual Energy Storage System Operation Strategy for Smart Energy Communities
by Eunsung Oh and Sung-Yong Son
Appl. Sci. 2022, 12(5), 2750; https://0-doi-org.brum.beds.ac.uk/10.3390/app12052750 - 07 Mar 2022
Cited by 4 | Viewed by 2046
Abstract
The concept of a virtual energy storage system (VESS) is based on the sharing of a large energy storage system by multiple units; however, the capacity allocation for each unit limits the operation performance of the VESS. This study proposes an operation strategy [...] Read more.
The concept of a virtual energy storage system (VESS) is based on the sharing of a large energy storage system by multiple units; however, the capacity allocation for each unit limits the operation performance of the VESS. This study proposes an operation strategy of a dynamic VESS for smart energy communities. The proposed VESS operation strategy considers the usage-limited constraint rather than the capacity allocation constraint and it guarantees the usage of VESS resources of each participant for an operation period. Therefore, the degrees of freedom for VESS operation can be increased at each operation time. The dynamic VESS operation problem is formulated as a mixed-integer linear problem that could be solved optimally by applying gradient methods and dual decomposition. The dataset of a VESS in Korea is used for simulation. The simulation results demonstrate that, when the proposed operation strategy is used, the cost efficiency achieved is more than twice that achieved when the existing VESS operation strategy is used. Furthermore, the proposed strategy accurately reflects the characteristics of the participants; thus, more units can participate in the VESS operation service. The proposed VESS operation can improve the system performance of the utility grid and increase the net benefit of the participants. Full article
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26 pages, 1690 KiB  
Article
Design and Control of a Battery Charger/Discharger Based on the Flyback Topology
by Carlos Andres Ramos-Paja, Juan David Bastidas-Rodriguez and Andres Julian Saavedra-Montes
Appl. Sci. 2021, 11(22), 10506; https://0-doi-org.brum.beds.ac.uk/10.3390/app112210506 - 09 Nov 2021
Cited by 7 | Viewed by 2276
Abstract
Devices connected to microgrids require safe conditions during their connection, disconnection and operation. The required safety is achieved through the design and control of the converters that interface elements with the microgrid. Therefore, the design of both power and control stages of a [...] Read more.
Devices connected to microgrids require safe conditions during their connection, disconnection and operation. The required safety is achieved through the design and control of the converters that interface elements with the microgrid. Therefore, the design of both power and control stages of a battery charger/discharger based on a flyback is proposed in this paper. First, the structure of a battery charger/discharger is proposed, including the battery, the flyback, the DC bus, and the control scheme. Then, three models to represent the battery charger/discharger are developed in this work; a switched model, an averaged model, and a steady-state model, which are used to obtain the static and dynamic behavior of the system, and also to obtain the design equations. Based on those models, a sliding-mode controller is designed, which includes the adaptive calculation of one parameter. Subsequently, a procedure to select the flyback HFT, the output capacitor, and the Kv parameter based on operation requirements of the battery charger/discharger is presented in detail. Five tests developed in PSIM demonstrate the global stability of the system, the correct design of the circuit and controller parameters, the satisfactory regulation of the bus voltage, and the correct operation of the system for charge, discharge and stand-by conditions. Furthermore, a contrast with a classical PI structure confirms the performance of the proposed sliding-mode controller. Full article
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14 pages, 1173 KiB  
Article
Risk-Based Virtual Power Plant Implementation Strategy for Smart Energy Communities
by Eunsung Oh
Appl. Sci. 2021, 11(17), 8248; https://0-doi-org.brum.beds.ac.uk/10.3390/app11178248 - 06 Sep 2021
Cited by 7 | Viewed by 1815
Abstract
This paper focuses on a virtual power plant (VPP) implementation strategy for smart local energy communities (SECs) with energy service providers. It is difficult to balance energy in the implementation stage due to uncertainties in demand and resources. Therefore, VPP implementation was modeled [...] Read more.
This paper focuses on a virtual power plant (VPP) implementation strategy for smart local energy communities (SECs) with energy service providers. It is difficult to balance energy in the implementation stage due to uncertainties in demand and resources. Therefore, VPP implementation was modeled using the risk factor of energy balance. Using this risk factor, it was shown that the temporal correlation between demand and resources was the dominant factor involved in VPP implementation. Based on this, two risk-based VPP implementation strategies are proposed: an optimization-based strategy and a simple strategy that is solved in an iterative way. To minimize VPP implementation costs, the proposed strategies select the resources that have high correlation coefficients with demand and low correlation coefficients with other resources. Experimental results using real data sets show that the proposed strategies based on the risk factor are effective means of VPP implementation for commercial and residential SECs. The results imply that VPPs for commercial SECs are possible when PV is used as the main resource and is supplemented by wind, and it is effective to configure VPPs for residential SECs using wind according to the correlation between demand and resources. Full article
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15 pages, 4876 KiB  
Article
Power System Reconfiguration in Distribution Network for Improving Reliability Using Genetic Algorithm and Particle Swarm Optimization
by Omar Kahouli, Haitham Alsaif, Yassine Bouteraa, Naim Ben Ali and Mohamed Chaabene
Appl. Sci. 2021, 11(7), 3092; https://0-doi-org.brum.beds.ac.uk/10.3390/app11073092 - 31 Mar 2021
Cited by 41 | Viewed by 4292
Abstract
This paper presents an optimal method for optimizing network reconfiguration problems in a power distribution system in order to enhance reliability and reduce power losses. Network reconfiguration can be viewed as an optimization problem involving a set of criteria that must be reduced [...] Read more.
This paper presents an optimal method for optimizing network reconfiguration problems in a power distribution system in order to enhance reliability and reduce power losses. Network reconfiguration can be viewed as an optimization problem involving a set of criteria that must be reduced when adhering to various constraints. The energy not supplied (ENS) during permanent network faults and active power losses are the objective functions that are optimized in this study during the reconfiguration phase. These objectives are expressed mathematically and will be integrated into various optimization algorithms used throughout the study. To begin, a mathematical formulation of the objectives to be optimized, as well as all the constraints that must be met, is proposed. Then, to solve this difficult combinatorial problem, we use the exhaustive approach, genetic algorithm (GA), and particle swarm optimization (PSO) on an IEEE 33-bus electrical distribution network. Finally, a performance evaluation of the proposed approaches is developed. The results show that optimizing the distribution network topology using the PSO approach contributed significantly to improving the reliability, node voltage, line currents, and calculation time. Full article
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12 pages, 2189 KiB  
Article
Risk-Based Virtual Energy Storage System Service Strategy for Prosumers
by Eunsung Oh
Appl. Sci. 2021, 11(7), 3020; https://0-doi-org.brum.beds.ac.uk/10.3390/app11073020 - 28 Mar 2021
Cited by 3 | Viewed by 1658
Abstract
The high cost of an energy storage system (ESS) is a barrier to its use. This paper proposes a risk-based virtual ESS (VESS) service strategy for prosumers. The basic concept of the VESS service is to logically refer to a physical ESS by [...] Read more.
The high cost of an energy storage system (ESS) is a barrier to its use. This paper proposes a risk-based virtual ESS (VESS) service strategy for prosumers. The basic concept of the VESS service is to logically refer to a physical ESS by multiple users. The VESS service can install ESS with a larger capacity compared to the case of installing ESS individually. Therefore, the VESS reduces the cost barrier through economies of scale. Moreover, ESS is not always being utilized at its maximum in the VESS service. Considering the risk, a VESS can offer a greater capacity than an installed ESS capacity. In this paper, the VESS service model suggested considers not only the economic benefit of increasing the VESS installation capacity but also the value at risk arising from servicing a greater capacity. The VESS service problem is formulated as a convex problem according to the VESS installation capacity and service price by applying stochastic approximation and is optimally solved using the gradient descent method in an iterative manner. The simulation results demonstrate that, when the proposed service strategy is used, the service provider that considers the risk achieves a significantly greater economic benefit of around 30% for the 128-prosumer pair case as compared to the one that does not consider risk. The benefit of the prosumer is increased by approximately 3.5% for the 128-prosumer pair case because the mismatched quantity is reduced during the peer-to-peer energy transaction. In addition, it is discussed how the proposed VESS service strategy achieves benefit through unit ESS cost reduction by the economics of scale and achieves increased service capacity with the multi-user diversity gain of participants. Full article
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17 pages, 6903 KiB  
Article
A Hierarchical Coordinative Control Strategy for Solid State Transformer Based DC Microgrids
by Zheng Li, Tao Zheng, Yani Wang and Chang Yang
Appl. Sci. 2020, 10(19), 6853; https://0-doi-org.brum.beds.ac.uk/10.3390/app10196853 - 29 Sep 2020
Cited by 5 | Viewed by 1925
Abstract
A solid state transformer (SST), as a kind of energy router in the Energy Internet, provides a unified access point for AC or DC distributed power subjects. However, the DC-link capacitors inside the SST will suffer huge voltage fluctuations when the output power [...] Read more.
A solid state transformer (SST), as a kind of energy router in the Energy Internet, provides a unified access point for AC or DC distributed power subjects. However, the DC-link capacitors inside the SST will suffer huge voltage fluctuations when the output power of the microgrid changes dramatically. With respect to this problem, caused by the random and intermittent characteristics of distributed generation (DG), a hierarchical coordinative control strategy is proposed. Compared with the common independent control, the proposed method not only makes full use of the regulation capacity of super capacitors, but also enhances the dynamic power tracking speed and reduces the speed difference between different stages of an SST. The dynamic voltage response under the proposed method is analyzed in frequency domain and compared with the independent control. To validate the effectiveness of the coordinative control strategy, a simulation model of an SST-based grid-connected DC microgrid system is established, and the topology of the SST is improved. The voltage stability of the DC bus is compared under different control strategies, and the coordinative control strategy is also verified, effectively under transition conditions. Full article
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13 pages, 1789 KiB  
Article
Reinforcement-Learning-Based Virtual Energy Storage System Operation Strategy for Wind Power Forecast Uncertainty Management
by Eunsung Oh
Appl. Sci. 2020, 10(18), 6420; https://0-doi-org.brum.beds.ac.uk/10.3390/app10186420 - 15 Sep 2020
Cited by 13 | Viewed by 1754
Abstract
Uncertainties related to wind power generation (WPG) restrict its usage. Energy storage systems (ESSs) are key elements employed in managing this uncertainty. This study proposes a reinforcement learning (RL)-based virtual ESS (VESS) operation strategy for WPG forecast uncertainty management. The VESS logically shares [...] Read more.
Uncertainties related to wind power generation (WPG) restrict its usage. Energy storage systems (ESSs) are key elements employed in managing this uncertainty. This study proposes a reinforcement learning (RL)-based virtual ESS (VESS) operation strategy for WPG forecast uncertainty management. The VESS logically shares a physical ESS to multiple units, while VESS operation reduces the cost barrier of the ESS. In this study, the VESS operation model is suggested considering not only its own operation but also the operation of other units, and the VESS operation problem is formulated as a decision-making problem. To solve this problem, a policy-learning strategy is proposed based on an expected state-action-reward-state-action (SARSA) approach that is robust to variations in uncertainty. Moreover, multi-dimensional clustering is performed according to the WPG forecast data of multiple units to enhance performance. Simulation results using real datasets recorded by the National Renewable Energy Laboratory project of U.S. demonstrate that the proposed strategy provides a near-optimal performance with a less than 2%-point gap with the optimal solution. In addition, the performance of the VESS operation is enhanced by multi-user diversity gain in comparison with individual ESS operation. Full article
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11 pages, 1739 KiB  
Article
Condition Assessment of Power Transformers Based on Health Index Value
by Patryk Bohatyrewicz, Janusz Płowucha and Jan Subocz
Appl. Sci. 2019, 9(22), 4877; https://0-doi-org.brum.beds.ac.uk/10.3390/app9224877 - 14 Nov 2019
Cited by 30 | Viewed by 5538
Abstract
In electric power systems, health index algorithms are mostly used for evaluation of the transformer population. In this method, some assessment criteria are insensitive when it comes to judging the technical state of the edges of the age spectrum. This paper presents a [...] Read more.
In electric power systems, health index algorithms are mostly used for evaluation of the transformer population. In this method, some assessment criteria are insensitive when it comes to judging the technical state of the edges of the age spectrum. This paper presents a new health index calculation method that aims to improve the overall effectiveness of the assessment. The proposed algorithm is based on regularly conducted oil diagnostics and easily available maintenance data to enable estimation and updating of the device’s health status in short intervals from an operational point of view. This method is compared to another health index algorithm built from the same parameters, but with different weights and an alternative result assessment philosophy. The two health index calculation methods are tested on a population of 96 power transformers and then compared to results obtained with an expert system, which is based on much more advanced diagnostic tests to determine the technical condition of the unit. The results of the experiment show that proper selection of weighting factors of the transformer’s technical condition parameters during health index calculation may help in simplifying its assessment while maintaining satisfactory accuracy in comparison to a highly advanced expert method. Full article
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