Optimizing Industrial Consumer Demand Response Trough DIsaggregation, Hour-Ahead Pricing, and Momentary Autonomous Control

Abdulaal, Ahmed (2017) Optimizing Industrial Consumer Demand Response Trough DIsaggregation, Hour-Ahead Pricing, and Momentary Autonomous Control. PhD thesis, University of Miami.

[img] PDF (Optimizing Industrial Consumer Demand Response Trough DIsaggregation, Hour-Ahead Pricing, and Momentary Autonomous Control)
Ahmed Abdulaal.pdf - Accepted Version
Restricted to Repository staff only

Download (6MB) | Request a copy

Abstract

The work in this study addresses the current limitations of the price-driven demand response (DR) approach. Mainly, the dependability on consumers to respond in an energy aware conduct, the response timeliness, the difficulty of applying DR in a busy industrial environment, and the problem of load synchronization are of utmost concern. In order to conduct a simulation study, realistic price simulation model and consumers’ building load models are created using real data. DR action is optimized using an autonomous control method, which eliminates the dependency on frequent consumer engagement. Since load scheduling and long-term planning approaches are infeasible in the industrial environment, the proposed method utilizes instantaneous DR in response to hour-ahead price signals (RTP-HA). Preliminary simulation results concluded savings at the consumer-side at the cost of increased supplier-side burden due to the aggregate effect of the universal DR policies. Therefore, a consumer disaggregation strategy is briefly discussed. Finally, a refined discrete-continuous control system is presented, which utilizes multi-objective Pareto optimization, evolutionary programming, utility functions, and bidirectional loads. Demonstrated through a virtual testbed fit with real data, the new system achieves momentary optimized DR in real-time while maximizing the consumer’s wellbeing.

Item Type: Thesis (PhD)
Additional Information: It has been accepted for inclusion in Open Access Dissertations by an authorized administrator of Scholarly Repository. For more information, please contact
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
T Technology > TJ Mechanical engineering and machinery
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Comparative
Depositing User: Emmanuel Ndorimana
Date Deposited: 11 Jun 2018 12:42
Last Modified: 11 Jun 2018 12:42
URI: http://thesisbank.jhia.ac.ke/id/eprint/4785

Actions (login required)

View Item View Item