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Control and Optimization for Energy Management in Smart Grids and...
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Control and Optimization for Energy Management in Smart Grids and Renewable Energy Systems

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 April 2022) | Viewed by 5485

Special Issue Editor

Prof. Dr. Fredy Ruiz

E-Mail Website
Guest Editor
Dipartimento di Elettronica Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy
Interests: control and optimization; smart-grids; power electronics; robotics and bio-technology; demand response; demand side management; data-driven techniques

Special Issue Information

Dear Colleagues,

The energy sector, in particular electricity, is evolving toward a more sustainable model, supported by renewable sources, storage systems and active demand, in a distributed configuration. However, their performance, reliability, cost operation and market penetration depend on several interrelated factors, such as component sizing, scheduling, control strategies and the environment. To properly operate this complex and uncertain system, adequate management policies must be developed. Within this framework, optimization techniques and automatic control are key tools to produce novel strategies for the planning and operation of modern energy systems. Among these new tools there are agents such as aggregators, energy communities, virtual power plants, among many other entities, conceived to provide energy systems with more flexibility and resiliency.

This Special Issue will gather together recent results in the active area of optimization-based energy management and control. Topics of interest include, but are not limited, to the following:

  • Learning-based and data-driven control strategies for energy management;
  • Optimal microgrids operation under uncertainty;
  • Distributed and consensus-based optimization in energy systems;
  • Control strategies for charging stations, electric vehicles and fleets;
  • Storage systems operation under uncertainty and aging constraints;
  • Control of virtual power plants and flexible loads for the integration of renewable sources;
  • Demand side management programs and contracts design for the involvement of “prosumers” in the grid.

Prof. Dr. Fredy Ruiz
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

  • energy management
  • demand side management
  • virtual power plants
  • renewable energy resources
  • e-mobility
  • electric vehicles
  • flexible loads
  • energy storage
  • aggregators
  • model predictive control
  • mechanism design
  • distributed optimization
  • Bi-level programming
  • stochastic optimization
  • scenario approach
  • robust optimization

Published Papers (2 papers)

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Research

20 pages, 908 KiB  
Article
Flower Greenhouse Energy Management to Offer Local Flexibility Markets
by Juan Sebastian Roncancio, José Vuelvas, Diego Patino and Carlos Adrián Correa-Flórez
Energies 2022, 15(13), 4572; https://0-doi-org.brum.beds.ac.uk/10.3390/en15134572 - 23 Jun 2022
Cited by 3 | Viewed by 1433
Abstract
Electricity access is strongly linked to human growth. Despite this, a portion of the world’s population remains without access to energy. In Colombia, rural communities have energy challenges due to the National Interconnected System’s (NIS) lack of quality and stability. It is common [...] Read more.
Electricity access is strongly linked to human growth. Despite this, a portion of the world’s population remains without access to energy. In Colombia, rural communities have energy challenges due to the National Interconnected System’s (NIS) lack of quality and stability. It is common to find that energy services in such locations are twice as costly as in cities and are only accessible for a few hours every day due to grid overload. Implementing market mechanisms that enable handling imbalances through the flexible load management of main loads within the grid is vital for improving the rural power grid’s quality. In this research, the energy from the rural grid is primarily employed to power a heating, ventilation, and air-conditioning (HVAC) system that chills flowers for future commerce. This load has significant consumption within the rural grid, so handling HVAC consumption in a suitable form can support the grid to avoid imbalances and improve the end-user access to energy. The primary responsibilities of the flower greenhouse operator are to reduce energy costs, maximize flexibility, and maintain a proper indoor temperature. Accordingly, this research proposes a flexible energy market based on the bi-level mixed-integer linear programming problem (Bi-MILP), involving the Agricultural Demand Response Aggregator (ADRA) and the flower greenhouse. ADRA is responsible for assuring the grid’s stability and quality and developing pricing plans that promote flexibility. A flower greenhouse in Colombia’s Boyacá department is used as an application for this research. This study looked at the HVAC’s flexibility under three different pricing schemes (fixed, time-of-use, and hourly) and graded the flower greenhouse’s flexibility as a reliable system. Full article
(This article belongs to the Special Issue Control and Optimization for Energy Management in Smart Grids and Renewable Energy Systems)
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21 pages, 42590 KiB  
Article
Grid-Connected PV System with Reactive Power Management and an Optimized SRF-PLL Using Genetic Algorithm
by Bashar Aldbaiat, Mutasim Nour, Eyad Radwan and Emad Awada
Energies 2022, 15(6), 2177; https://0-doi-org.brum.beds.ac.uk/10.3390/en15062177 - 16 Mar 2022
Cited by 13 | Viewed by 3330
Abstract
This paper presents a two-stage grid-connected PV system with reactive power management capability. The proposed model can send phase-shifted current to the grid during a low-voltage ride through (LVRT) to recover the voltage levels of the grid’s feeders. The novelty of the proposed [...] Read more.
This paper presents a two-stage grid-connected PV system with reactive power management capability. The proposed model can send phase-shifted current to the grid during a low-voltage ride through (LVRT) to recover the voltage levels of the grid’s feeders. The novelty of the proposed algorithm, unlike the common methods, is that it does not need to disable the maximum power point tracking (MPPT) state while managing active and reactive power injection simultaneously. Moreover, the new method promotes a safety factor by offering overcurrent protection to the PV inverter. The phase-locked loop based on the synchronous reference frame (SRF-PLL) is optimized using a genetic algorithm (GA). The settling time of SRF-PLL’s step response is minimized, and the frequency dynamics are improved to enhance synchronization during LVRT. The system’s performance is tested and verified using MATLAB/Simulink simulations. The obtained results prove the effectiveness of the proposed control algorithm in managing reactive power interventions. The optimized phase-locked loop shows robust performance and is compared to the conventional low-gain PLL to spot the enhancement. Full article
(This article belongs to the Special Issue Control and Optimization for Energy Management in Smart Grids and Renewable Energy Systems)
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