Optimal Sizing and Management of Distributed Energy Resources in Smart Buildings

This article investigates optimal sizing and realtime control of electrical and thermal distributed energy resources (DERs) in smart buildings. Initially, a comprehensive system architecture is presented considering both electrical and thermal DERs. Then, the DERs are optimally sized through a planning optimization problem with respect to minimization of the total initial investment cost, replacement cost, operations-and-management cost and environmental cost normalized by energy delivered from renewables and controllable non-renewables. Finally, the DERs are optimally controlled in a realtime through a one-slot-look-ahead (OSLA) optimization technique with respect to minimization of load scheduling delay cost, energy procurement cost, energy storage degradation cost, DERs operations-and management cost, and environmental deterioration cost. The proposed OSLA based technique has the following distinct features and benefits: (i) it introduces a customer-oriented specific duration based modelling that makes it useful for practical customer energy needs and available budget limitation; (ii) it relies on the current states of the system inputs only making it applicable in general scenarios; (iii) it employs special techniques of problem modification, transformation, approximation and separation with a significantly lower computational complexity making it useful for practical implementation. Performance of the proposed approach is validated through simulations. Results show that the proposed algorithm can reduce the monthly energy consumption bill of BEMS customers by 20.53%. Also, it can execute 88.15% of customer load tasks accurately accounting for realtime changes in system inputs.(c) 2022 Elsevier Ltd. All rights reserved.

Automated summary

This article investigates the optimal sizing and real-time control of electrical and thermal distributed energy resources (DERs) in smart buildings. It proposes a comprehensive system architecture and utilizes planning optimization problems and one-slot-look-ahead (OSLA) optimization technique to optimize the sizing and control of DERs. The proposed approach considers various costs and provides customer-oriented modeling, making it practical and applicable in general scenarios. Simulation results show significant cost reduction and accurate load task execution.