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Energies
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Building-to-Grid Integration through Intelligent Optimization and Control
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Building-to-Grid Integration through Intelligent Optimization and Control

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 (9 October 2020) | Viewed by 6433

Special Issue Editor

Dr. Kyri Baker

E-Mail Website
Guest Editor
Department of Civil, Environmental, and Architectural Engineering, University of Colorado, Boulder, CO, USA
Interests: building-to-grid; power systems; smart buildings; renewable energy integration; data-driven optimization

Special Issue Information

Dear Colleagues,

Buildings are responsible for the majority of electricity end-use in the power grid. Coordination of the demand and supply side of the electric power grid is becoming increasingly valuable to unlock additional flexibility from a wider set of controllable assets. Utilizing opportunities within intelligent residential, commercial, and industrial buildings provides additional resources to help to provide grid stability, integrate higher penetrations of renewable energy, and lower electricity costs. However, much additional work must be performed in the area of building-to-grid integration in order to make their interaction with the electric power grid seamless and reliable. Current solutions for direct load control and demand response have the potential to be greatly improved to better reflect both grid and building-level goals, as they currently provide a limited impact on overall power system efficiency and reliability.

This Special Issue invites research in the broad area of building-to-grid integration, with a specific focus on operational strategies for optimizing and controlling building loads and grid assets to facilitate a seamless coordination between both supply and demand. Research topics addressing either demand-side control and optimization or grid-side demand response programs or signals, or control or design strategies that encompass both buildings and the grid, are encouraged. Single-building or aggregate community control and optimization strategies may be proposed.

Dr. Kyri Baker
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

  • grid interactive buildings
  • demand response
  • dynamic pricing
  • renewable energy integration
  • intelligent buildings and communities
  • peer-to-peer energy trading
  • home energy management systems
  • load shifting

Published Papers (2 papers)

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Research

40 pages, 5847 KiB  
Article
Hierarchical, Grid-Aware, and Economically Optimal Coordination of Distributed Energy Resources in Realistic Distribution Systems
by Mads Almassalkhi, Sarnaduti Brahma, Nawaf Nazir, Hamid Ossareh, Pavan Racherla, Soumya Kundu, Sai Pushpak Nandanoori, Thiagarajan Ramachandran, Ankit Singhal, Dennice Gayme, Chengda Ji, Enrique Mallada, Yue Shen, Pengcheng You and Dhananjay Anand
Energies 2020, 13(23), 6399; https://doi.org/10.3390/en13236399 - 3 Dec 2020
Cited by 10 | Viewed by 3086
Abstract
Renewable portfolio standards are targeting high levels of variable solar photovoltaics (PV) in electric distribution systems, which makes reliability more challenging to maintain for distribution system operators (DSOs). Distributed energy resources (DERs), including smart, connected appliances and PV inverters, represent responsive grid resources [...] Read more.
Renewable portfolio standards are targeting high levels of variable solar photovoltaics (PV) in electric distribution systems, which makes reliability more challenging to maintain for distribution system operators (DSOs). Distributed energy resources (DERs), including smart, connected appliances and PV inverters, represent responsive grid resources that can provide flexibility to support the DSO in actively managing their networks to facilitate reliability under extreme levels of solar PV. This flexibility can also be used to optimize system operations with respect to economic signals from wholesale energy and ancillary service markets. Here, we present a novel hierarchical scheme that actively controls behind-the-meter DERs to reliably manage each unbalanced distribution feeder and exploits the available flexibility to ensure reliable operation and economically optimizes the entire distribution network. Each layer of the scheme employs advanced optimization methods at different timescales to ensure that the system operates within both grid and device limits. The hierarchy is validated in a large-scale realistic simulation based on data from the industry. Simulation results show that coordination of flexibility improves both system reliability and economics, and enables greater penetration of solar PV. Discussion is also provided on the practical viability of the required communications and controls to implement the presented scheme within a large DSO. Full article
(This article belongs to the Special Issue Building-to-Grid Integration through Intelligent Optimization and Control)
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29 pages, 13475 KiB  
Article
Optimal Renewable Resource Allocation and Load Scheduling of Resilient Communities
by Jing Wang, Kaitlyn Garifi, Kyri Baker, Wangda Zuo, Yingchen Zhang, Sen Huang and Draguna Vrabie
Energies 2020, 13(21), 5683; https://doi.org/10.3390/en13215683 - 30 Oct 2020
Cited by 18 | Viewed by 2561
Abstract
This paper presents a methodology for enhancing community resilience through optimal renewable resource allocation and load scheduling in order to minimize unserved load and thermal discomfort. The proposed control architecture distributes the computational effort and is easier to be scaled up than traditional [...] Read more.
This paper presents a methodology for enhancing community resilience through optimal renewable resource allocation and load scheduling in order to minimize unserved load and thermal discomfort. The proposed control architecture distributes the computational effort and is easier to be scaled up than traditional centralized control. The decentralized control architecture consists of two layers: The community operator layer (COL) allocates the limited amount of renewable energy resource according to the power flexibility of each building. The building agent layer (BAL) addresses the optimal load scheduling problem for each building with the allowable load determined by the COL. Both layers are formulated as a model predictive control (MPC) based optimization. Simulation scenarios are designed to compare different combinations of building weighting methods and objective functions to provide guidance for real-world deployment by community and microgrid operators. The results indicate that the impact of power flexibility is more prominent than the weighting factor to the resource allocation process. Allocation based purely on occupancy status could lead to an increase of PV curtailment. Further, it is necessary for the building agent to have multi-objective optimization to minimize unserved load ratio and maximize comfort simultaneously. Full article
(This article belongs to the Special Issue Building-to-Grid Integration through Intelligent Optimization and Control)
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