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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

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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

Open AccessArticle

Hierarchical, Grid-Aware, and Economically Optimal Coordination of Distributed Energy Resources in Realistic Distribution Systems

Sai Pushpak Nandanoori

Thiagarajan Ramachandran

and

Energies 2020, 13(23), 6399; https://doi.org/10.3390/en13236399 - 03 Dec 2020

Cited by 5 | Viewed by 1992

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 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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Open AccessArticle

Optimal Renewable Resource Allocation and Load Scheduling of Resilient Communities

and

Energies 2020, 13(21), 5683; https://doi.org/10.3390/en13215683 - 30 Oct 2020

Cited by 12 | Viewed by 1787

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 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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