energies-logo

Journal Browser

Journal Browser

Power System Planning and Quality Control

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F1: Electrical Power System".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 12482

Special Issue Editors

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
Special Issues, Collections and Topics in MDPI journals
Media Integrated Laboratory, Osaka University, Osaka, Japan
Interests: power quality analysis; harmonics estimation; renewable energy control and management; optimization of power system operation and control; meta-heuristic optimization theory and applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The continued growth of renewable energies and their integration to the power grids, especially through distributed integration, has increased the importance of electrical power control and management. In addition to distributed integration of the renewables, the increasing applications of the recent technology of light-emitting diodes (LEDs) and resultant power electronics have impacted power quality as well. As such, power quality analysis has an important role to play not just in power management but also in the final electrical power quality delivered to customers. This Special Issue invites researchers in the fields of power control and management, renewable power distribution, and power quality measuring and control to submit their quality research works for publication. The Special Issue includes but is not limited the following topics:

  • Renewable energy management;
  • Distributed power generation;
  • Power system control;
  • Power system generation planning;
  • Power system transmission planning;
  • Optimized power systems;
  • Optimization of the power system planning;
  • Electrical power quality measurement;
  • Power systems harmonics and inter-harmonics measurement;
  • Power system sub-harmonics measurement;
  • Supra-harmonics interference to electrical power.

Prof. Dr. Tomonobu Senjyu
Dr. Mahdi Khosravy
Guest Editors

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.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Power systems control
  • Power system management
  • Renewables integration
  • Power quality

Published Papers (6 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Editorial

Jump to: Research

2 pages, 151 KiB  
Editorial
Power System Planning and Quality Control
by Tomonobu Senjyu and Mahdi Khosravy
Energies 2022, 15(14), 4995; https://0-doi-org.brum.beds.ac.uk/10.3390/en15144995 - 08 Jul 2022
Viewed by 1013
Abstract
The optimum planning of the electrical power expansion and, accordingly, controlling the power quality are recent critical issues in power management [...] Full article
(This article belongs to the Special Issue Power System Planning and Quality Control)

Research

Jump to: Editorial

26 pages, 4704 KiB  
Article
Estimation of Grid Reinforcement Costs Triggered by Future Grid Customers: Influence of the Quantification Method (Scaling vs. Large-Scale Simulation) and Coincidence Factors (Single vs. Multiple Application)
by Bernd Thormann and Thomas Kienberger
Energies 2022, 15(4), 1383; https://0-doi-org.brum.beds.ac.uk/10.3390/en15041383 - 14 Feb 2022
Cited by 6 | Viewed by 1602
Abstract
The integration of future grid customers, e.g., electric vehicles, heat pumps, or photovoltaic modules, will challenge existing low-voltage power grids in the upcoming years. Hence, distribution system operators must quantify future grid reinforcement measures and resulting costs early. On this account, this work [...] Read more.
The integration of future grid customers, e.g., electric vehicles, heat pumps, or photovoltaic modules, will challenge existing low-voltage power grids in the upcoming years. Hence, distribution system operators must quantify future grid reinforcement measures and resulting costs early. On this account, this work initially evaluates different methods to quantify future grid reinforcement needs, applied by the current state of research. Thereby, it indicates the significance of large-scale grid simulations, i.e., simulating several thousand low-voltage grids, to quantify grid reinforcements accurately. Otherwise, a selected area’s total grid reinforcement costs might be misjudged significantly. Due to its fast application, deterministic grid simulations based on coincidence factors are most commonly used in the current state of research to simulate several thousand grids. Hence, in the second step, recent studies’ approaches to applying grid customers’ coincidence factors are evaluated: While simplified approaches allow fast simulation of numerous grids, they underestimate potential grid congestion and grid reinforcement costs. Therefore, a fully automated large-scale grid simulation tool is developed in this work to allow the simulation of multiple grids applying grid customers’ coincidence factors appropriately. As a drawback, the applied deterministic framework only allows an estimation of future grid reinforcement costs. Detailed determination of each grid’s grid reinforcement costs requires time-resolved grid simulations. Full article
(This article belongs to the Special Issue Power System Planning and Quality Control)
Show Figures

Figure 1

17 pages, 4898 KiB  
Article
Integration of Renewable Based Distributed Generation for Distribution Network Expansion Planning
by Mulusew Ayalew, Baseem Khan, Issaias Giday, Om Prakash Mahela, Mahdi Khosravy, Neeraj Gupta and Tomonobu Senjyu
Energies 2022, 15(4), 1378; https://0-doi-org.brum.beds.ac.uk/10.3390/en15041378 - 14 Feb 2022
Cited by 15 | Viewed by 1642
Abstract
Electrical energy is critical to a country’s socioeconomic progress. Distribution system expansion planning addresses the services that must be installed for the distribution networks to meet the expected load need, while also meeting different operational and technical limitations. The incorporation of distributed generation [...] Read more.
Electrical energy is critical to a country’s socioeconomic progress. Distribution system expansion planning addresses the services that must be installed for the distribution networks to meet the expected load need, while also meeting different operational and technical limitations. The incorporation of distributed generation sources (DGs) alters the operating characteristics of modern power systems, resulting in major economic and technical benefits, such as simplified distribution network expansion planning, lower power losses, and improved voltage profile. Thus, in this study, an analytical method is used to design the expansion planning of the Addis North distribution network considering the integration of optimal sizes of distributed generations for the projected demand growths. To evaluate the capability of the existing Addis North distribution network and its capability to supply reliable power considering future expansion, the load demand forecast for the years 2020–2030 is done using the least square method. The performance evaluation of the existing and the upgraded network considering the existing and forecasted load demand for the years 2030 is done using ETAP software. Accordingly, the results revealed that the existing networks cannot meet the existing load demand of the town, with major problems of increased power loss and a reduced voltage profile. To mitigate this problem, the Addis North feeder-1 distribution network is upgraded and for each study case, the balanced and positive sequence load flow analysis was executed and the maximum total real and reactive power losses were found at bus 29. The result shows that the upgraded network of bus 29 was the optimal location of DG and its size was 9.93 MW. After the optimal size of DG was placed at this bus, the real and reactive power losses of the upgraded networks were 0.2939 MW and 0.219 MVAr, respectively. At bus 29 the maximum power losses reduction and voltage profile improvements were found. The active and reactive power losses were minimized by 21.285% and 19.633% respectively and the voltage profiles were improved by 8.78%. Thus, in the predicted year 2030, DG power sources could cover 61.12% of the feeder-1 power requirements. Full article
(This article belongs to the Special Issue Power System Planning and Quality Control)
Show Figures

Figure 1

21 pages, 6968 KiB  
Article
A Deep Learning-Based Approach for Generation Expansion Planning Considering Power Plants Lifetime
by Majid Dehghani, Mohammad Taghipour, Saleh Sadeghi Gougheri, Amirhossein Nikoofard, Gevork B. Gharehpetian and Mahdi Khosravy
Energies 2021, 14(23), 8035; https://0-doi-org.brum.beds.ac.uk/10.3390/en14238035 - 01 Dec 2021
Cited by 7 | Viewed by 1825
Abstract
In Generation Expansion Planning (GEP), the power plants lifetime is one of the most important factors which to the best knowledge of the authors, has not been investigated in the literature. In this article, the power plants lifetime effect on GEP is investigated. [...] Read more.
In Generation Expansion Planning (GEP), the power plants lifetime is one of the most important factors which to the best knowledge of the authors, has not been investigated in the literature. In this article, the power plants lifetime effect on GEP is investigated. In addition, the deep learning-based approaches are widely used for time series forecasting. Therefore, a new version of Long short-term memory (LSTM) networks known as Bi-directional LSTM (BLSTM) networks are used in this paper to forecast annual peak load of the power system. For carbon emissions, the cost of carbon is considered as the penalty of pollution in the objective function. The proposed approach is evaluated by a test network and then applied to Iran power system as a large-scale grid. The simulations by GAMS (General Algebraic Modeling System, Washington, DC, USA) software show that due to consideration of lifetime as a constraint, the total cost of the GEP problem decreases by 5.28% and 7.9% for the test system and Iran power system, respectively. Full article
(This article belongs to the Special Issue Power System Planning and Quality Control)
Show Figures

Figure 1

25 pages, 4135 KiB  
Article
Generation Expansion Planning with Energy Storage Systems Considering Renewable Energy Generation Profiles and Full-Year Hourly Power Balance Constraints
by Radhanon Diewvilai and Kulyos Audomvongseree
Energies 2021, 14(18), 5733; https://0-doi-org.brum.beds.ac.uk/10.3390/en14185733 - 11 Sep 2021
Cited by 8 | Viewed by 2779
Abstract
This paper proposes a methodology to develop generation expansion plans considering energy storage systems (ESSs), individual generation unit characteristics, and full-year hourly power balance constraints. Generation expansion planning (GEP) is a complex optimization problem. To get a realistic plan with the lowest cost, [...] Read more.
This paper proposes a methodology to develop generation expansion plans considering energy storage systems (ESSs), individual generation unit characteristics, and full-year hourly power balance constraints. Generation expansion planning (GEP) is a complex optimization problem. To get a realistic plan with the lowest cost, acceptable system reliability, and satisfactory CO2 emissions for the coming decades, a complex multi-period mixed integer linear programming (MILP) model needs to be formulated and solved with individual unit characteristics along with hourly power balance constraints. This problem requires huge computational effort since there are thousands of possible scenarios with millions of variables in a single calculation. However, in this paper, instead of finding the globally optimal solutions of such MILPs directly, a simplification process is proposed, breaking it down into multiple LP subproblems, which are easier to solve. In each subproblem, constraints relating to renewable energy generation profiles, charge-discharge patterns of ESSs, and system reliability can be included. The proposed process is tested against Thailand’s power development plan. The obtained solution is almost identical to that of the actual plan, but with less computational effort. The impacts of uncertainties as well as ESSs on GEP, e.g., system reliability, electricity cost, and CO2 emission, are also discussed. Full article
(This article belongs to the Special Issue Power System Planning and Quality Control)
Show Figures

Figure 1

18 pages, 1228 KiB  
Article
Unbalanced Voltage Compensation with Optimal Voltage Controlled Regulators and Load Ratio Control Transformer
by Akito Nakadomari, Ryuto Shigenobu, Takeyoshi Kato, Narayanan Krishnan, Ashraf Mohamed Hemeida, Hiroshi Takahashi and Tomonobu Senjyu
Energies 2021, 14(11), 2997; https://0-doi-org.brum.beds.ac.uk/10.3390/en14112997 - 21 May 2021
Cited by 13 | Viewed by 2120
Abstract
Penetration of equipment such as photovoltaic power generations (PV), heat pump water heaters (HP), and electric vehicles (EV) introduces voltage unbalance issues in distribution systems. Controlling PV and energy storage system (ESS) outputs or coordinated EV charging are investigated for voltage unbalance compensation. [...] Read more.
Penetration of equipment such as photovoltaic power generations (PV), heat pump water heaters (HP), and electric vehicles (EV) introduces voltage unbalance issues in distribution systems. Controlling PV and energy storage system (ESS) outputs or coordinated EV charging are investigated for voltage unbalance compensation. However, some issues exist, such as dependency on installed capacity and fairness among consumers. Therefore, the ideal way to mitigate unbalanced voltages is to use grid-side equipment mainly. This paper proposes a voltage unbalance compensation based on optimal tap operation scheduling of three-phase individual controlled step voltage regulators (3ϕSVR) and load ratio control transformer (LRT). In the formulation of the optimization problem, multiple voltage unbalance metrics are comprehensively included. In addition, voltage deviations, network losses, and coordinated tap operations, which are typical issues in distribution systems, are considered. In order to investigate the mutual influence among voltage unbalance and other typical issues, various optimization problems are formulated, and then they are compared by numerical simulations. The results show that the proper operation of 3ϕSVRs and LRT effectively mitigates voltage unbalance. Furthermore, the results also show that voltage unbalances and other typical issues can be improved simultaneously with appropriate formulations. Full article
(This article belongs to the Special Issue Power System Planning and Quality Control)
Show Figures

Figure 1

Back to TopTop