An Expert-based Approach for Grid Peak Demand Curtailment using HVAC Thermostat Setpoint Interventions in Commercial Buildings
| dc.contributor.author | Ramdaspalli, Sneha Raj | en |
| dc.contributor.committeechair | Rahman, Saifur | en |
| dc.contributor.committeemember | Pipattanasomporn, Manisa | en |
| dc.contributor.committeemember | Southward, Steve C. | en |
| dc.contributor.committeemember | De La Reelopez, Jaime | en |
| dc.contributor.committeemember | Yu, Guoqiang | en |
| dc.contributor.department | Electrical Engineering | en |
| dc.date.accessioned | 2022-12-24T07:00:11Z | en |
| dc.date.available | 2022-12-24T07:00:11Z | en |
| dc.date.issued | 2021-07-01 | en |
| dc.description.abstract | This dissertation explores the idea of inducing grid peak demand curtailment by turning commercial buildings into interactive assets for building owners during the demand control period. The work presented here is useful for both ab initio design of new sites and for existing or retrofitted sites. An analytical hierarchy process (AHP)-based framework is developed to curtail the thermal load effectively across a group of commercial buildings. It gives an insight into the amount of peak demand reduction possible for each building, subject to indoor thermal comfort constraints as per ASHRAE standards. Furthermore, the detailed operation of buildings in communion with the electric grid is illustrated through case studies. This analysis forms an outline for the assessment of transactive energy opportunities for commercial buildings in distribution system operations and lays the foundation for a seamless building-to-grid integration framework. The contribution of this dissertation is fourfold – (a) an efficient method of developing high-fidelity physics-based building energy models for understanding the realistic operation of commercial buildings, (b) identification of minimal dataset to achieve a target accuracy for the building energy models (c) quantification of building peak demand reduction potential and corresponding energy savings across a stipulated range of thermostat setpoint temperatures and (d) AHP-based demand curtailment scheme. By careful modeling, it is shown that commercial building models developed using this methodology are both accurate and robust. As a result, the proposed approach can be extended to other commercial buildings of diverse characteristics, independent of the location. The methodology presented here takes a holistic approach towards building energy modeling by accounting for several building parameters and interactions between them. In addition, parametric analysis is done to identify a useful minimal dataset required to achieve a specified accuracy for the building energy models. This thesis describes the concept of commercial buildings as interactive assets in a transactive grid environment and the idea behind its working. | en |
| dc.description.abstractgeneral | This dissertation titled "An Expert-based Approach for Grid Peak Demand Curtailment using HVAC Thermostat Setpoint Interventions in Commercial Buildings" tackles two important challenges in the energy management domain: –electric grid peak demand curtailment and energy savings in commercial buildings. The distinguishing feature of the proposed solution lies in addressing these challenges solely through demand-side management (DSM) strategies, which include HVAC thermostat setpoint interventions and lighting control. We present a methodology for developing highly accurate building energy models that serve as digital twins of actual buildings. These digital replicas can be used to quantify the impact of various interventions and reflect the realistic operation of commercial buildings across varied conditions. This enables building owners to control demand intelligently and transact energy effectively in the electricity market. The development of Internet of Things (IoT) market and advanced technologies such as smart meters and smart thermostats allows for the design of novel strategies that address traditional challenges faced by electric grid operators. This dissertation elaborates on how smart buildings can leverage IoT-based solutions to participate in the electricity market during demand control periods. We also developed an expert opinion-based demand curtailment allocation scheme resulting in grid peak demand reduction. The numerical results obtained reinforce the effectiveness of the proposed solution across varied climatic conditions. | en |
| dc.description.degree | Doctor of Philosophy | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:31353 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/112997 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Building energy modeling | en |
| dc.subject | Physics-based models | en |
| dc.subject | Commercial buildings | en |
| dc.subject | HVAC thermostat setpoint intervention | en |
| dc.subject | Peak demand reduction | en |
| dc.subject | Energy savings | en |
| dc.subject | Analytical hierarchical process | en |
| dc.title | An Expert-based Approach for Grid Peak Demand Curtailment using HVAC Thermostat Setpoint Interventions in Commercial Buildings | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Electrical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |