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Energies
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Optimal Home Energy and Active Management Strategy in Smart Grids
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Optimal Home Energy and Active Management Strategy in Smart Grids

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

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 10516

Special Issue Editor

Dr. Kodjo Agbossou

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Hydrogen Research Institute, University of Quebec at Trois-Rivières, Trois-Rivières, QC G8Z 4M3, Canada
Interests: distributed energy resources; renewable energy; smart microgrids; transactive energy; active network management; market participation; distributed control; multi-agents systems; home energy management systems

Special Issue Information

Dear Colleagues,

Active management (AM) is a promising technique to boost the integration and operation of distributed energy resources (DER), which include generators, loads, and storage. Under the smart-grid paradigm, active distribution grids are designed to enhance reliability, interoperability, security, flexibility, and efficiency, as well as facilitating market participation, the heterogeneity of new energy services, and cooperative working with large-scale power grids. Because of the complex dynamic and bidirectional energy flow of active grids, they require decentralized control systems. These systems exploit the data, provided by advanced information and communication infrastructures, which take advantage of smart meter technologies, and Internet of things (IoT) devices. In active grid structures, multi-agent systems play a crucial role in establishing adequate mechanisms for supervision, operational planning, and automatic negotiation between grid actors. Additionally, in this structure, urban context brings about a diversity of opportunities and challenges, including electrical vehicles integration and residential customers participation in power grid services, such as proactive participation in the emergent demand response programs. Nevertheless, active grids require further efforts to improve their performance and make their transition from conventional to self-optimized feasible.

I would like to cordially invite you to submit your manuscript to this Special Issue. Your contribution will assist in developing cutting-edge energy systems.

Thank you very much!

Dr. Kodjo Agbossou
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.

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

  • Distributed control for active grids
  • Urban generation of renewable energy
  • Smart grid security and privacy
  • Distributed energy resources
  • Multi-agent systems for energy trading
  • Smart grid analytics
  • Transactive demand side management
  • Home energy management systems
  • Grid-connected microgrids
  • Real-time energy management
  • Vehicle-to-grid

Published Papers (4 papers)

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Research

28 pages, 8686 KiB  
Article
Balancing Energy Efficiency with Indoor Comfort Using Smart Control Agents: A Simulative Case Study
by Iakovos T. Michailidis, Roozbeh Sangi, Panagiotis Michailidis, Thomas Schild, Johannes Fuetterer, Dirk Mueller and Elias B. Kosmatopoulos
Energies 2020, 13(23), 6228; https://doi.org/10.3390/en13236228 - 26 Nov 2020
Cited by 9 | Viewed by 1834
Abstract
Modern literature exhibits numerous centralized control approaches—event-based or model assisted—for tackling poor energy performance in buildings. Unfortunately, even novel building optimization and control (BOC) strategies commonly suffer from complexity and scalability issues as well as uncertain behavior as concerns large-scale building ecosystems—a fact [...] Read more.
Modern literature exhibits numerous centralized control approaches—event-based or model assisted—for tackling poor energy performance in buildings. Unfortunately, even novel building optimization and control (BOC) strategies commonly suffer from complexity and scalability issues as well as uncertain behavior as concerns large-scale building ecosystems—a fact that hinders their practical compatibility and broader applicability. Moreover, decentralized optimization and control approaches trying to resolve scalability and complexity issues have also been proposed in literature. Those approaches usually suffer from modeling issues, utilizing an analytically available formula for the overall performance index. Motivated by the complications in existing strategies for BOC applications, a novel, decentralized, optimization and control approach—referred to as Local for Global Parameterized Cognitive Adaptive Optimization (L4GPCAO)—has been extensively evaluated in a simulative environment, contrary to previous constrained real-life studies. The current study utilizes an elaborate simulative environment for evaluating the efficiency of L4GPCAO; extensive simulation tests exposed the efficiency of L4GPCAO compared to the already evaluated centralized optimization strategy (PCAO) and the commercial control strategy that is adopted in the BOC practice (common reference case). L4GPCAO achieved a quite similar performance in comparison to PCAO (with 25% less control parameters at a local scale), while both PCAO and L4GPCAO significantly outperformed the reference BOC practice. Full article
(This article belongs to the Special Issue Optimal Home Energy and Active Management Strategy in Smart Grids)
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16 pages, 3805 KiB  
Article
Multi-Objective Optimization of Home Appliances and Electric Vehicle Considering Customer’s Benefits and Offsite Shared Photovoltaic Curtailment
by Yeongenn Kwon, Taeyoung Kim, Keon Baek and Jinho Kim
Energies 2020, 13(11), 2852; https://doi.org/10.3390/en13112852 - 03 Jun 2020
Cited by 15 | Viewed by 2808
Abstract
A Time-of-Use (TOU)-tariff scheme, helps residential customers to adjust their energy consumption voluntarily and reduce energy cost. The TOU tariff provides flexibility in demand, alleviate volatility caused by an increase in renewable energy in the power system. However, the uncertainty in the customer’s [...] Read more.
A Time-of-Use (TOU)-tariff scheme, helps residential customers to adjust their energy consumption voluntarily and reduce energy cost. The TOU tariff provides flexibility in demand, alleviate volatility caused by an increase in renewable energy in the power system. However, the uncertainty in the customer’s behavior, causes difficulty in predicting changes in residential demand patterns through the TOU tariff. In this study, the dissatisfaction model for each time slot is set as the energy consumption data of the customer. Based on the actual customer’s consumption pattern, the user sets up a model of dissatisfaction that enables aggressive energy cost reduction. In the proposed Home Energy Management System (HEMS) model, the efficient use of jointly invested offsite photovoltaic (PV) power generation is also considered. The optimal HEMS scheduling result considering the dissatisfaction, cost, and PV curtailment was obtained. The findings of this study indicate, that incentives are required above a certain EV battery capacity to induce EV charging for minimizing PV curtailment. Full article
(This article belongs to the Special Issue Optimal Home Energy and Active Management Strategy in Smart Grids)
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Graphical abstract

27 pages, 5107 KiB  
Article
Research on Home Energy Management Method for Demand Response Based on Chance-Constrained Programming
by Xiangyu Kong, Siqiong Zhang, Bowei Sun, Qun Yang, Shupeng Li and Shijian Zhu
Energies 2020, 13(11), 2790; https://doi.org/10.3390/en13112790 - 01 Jun 2020
Cited by 11 | Viewed by 2267
Abstract
With the development of smart devices and information technology, it is possible for users to optimize their usage of electrical equipment through the home energy management system (HEMS). To solve the problems of daily optimal scheduling and emergency demand response (DR) in an [...] Read more.
With the development of smart devices and information technology, it is possible for users to optimize their usage of electrical equipment through the home energy management system (HEMS). To solve the problems of daily optimal scheduling and emergency demand response (DR) in an uncertain environment, this paper provides an opportunity constraint programming model for the random variables contained in the constraint conditions. Considering the probability distribution of the random variables, a home energy management method for DR based on chance-constrained programming is proposed. Different confidence levels are set to reflect the influence mechanism of random variables on constraint conditions. An improved particle swarm optimization algorithm is used to solve the problem. Finally, the demand response characteristics in daily and emergency situations are analyzed by simulation examples, and the effectiveness of the method is verified. Full article
(This article belongs to the Special Issue Optimal Home Energy and Active Management Strategy in Smart Grids)
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15 pages, 881 KiB  
Article
Optimal Parameters of Volt–Var Function in Smart Inverters for Improving System Performance
by Hyeong-Jin Lee, Kwang-Hoon Yoon, Joong-Woo Shin, Jae-Chul Kim and Sung-Min Cho
Energies 2020, 13(9), 2294; https://doi.org/10.3390/en13092294 - 06 May 2020
Cited by 24 | Viewed by 3157
Abstract
This paper proposes a method to improve the performance of a distribution system by optimizing volt–var function of a smart inverter to alleviate the voltage deviation problem due to distributed generation connection. In order to minimize voltage deviation and line losses which represent [...] Read more.
This paper proposes a method to improve the performance of a distribution system by optimizing volt–var function of a smart inverter to alleviate the voltage deviation problem due to distributed generation connection. In order to minimize voltage deviation and line losses which represent the performance of a distribution system, this paper proposes an algorithm that optimally sets the parameters of the volt–var function. In the process of optimizing the parameters of the volt–var function, the algorithm proposed in this paper considers minimizing the contribution of the reactive power in order not to affect the output of the distributed generation. In order to apply to the field, the distribution system in South Korea considering the configuration and operation regulation was selected as a test model for algorithm verification. As a result, the system performance was successfully improved by optimally setting the volt–var function of the smart inverter which is an effective way to solve the over-voltage problem caused by distributed generation connection. This paper verified the proposed method through OpenDSS, a quasi-static time-series simulation, for the test model considering the characteristics of the distribution system in South Korea. Full article
(This article belongs to the Special Issue Optimal Home Energy and Active Management Strategy in Smart Grids)
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