TY - JOUR
T1 - Optimal Design of an Islanded Microgrid with Load Shifting Mechanism between Electrical and Thermal Energy Storage Systems
AU - Mohandes, Baraa
AU - Acharya, Samrat
AU - Moursi, Mohamed Shawky El
AU - Al-Sumaiti, Ameena Saad
AU - Doukas, Haris
AU - Sgouridis, Sgouris
N1 - Funding Information:
Manuscript received April 1, 2019; revised September 26, 2019 and December 11, 2019; accepted January 19, 2020. Date of publication January 27, 2020; date of current version June 22, 2020. This work was supported by the Khalifa University of Science and Technology under Award CIRA-2018-37. This work was also supported in part by the EU-GCC Clean Energy Technology Network, European Commission FPI service under Contract PI/2015/370817. Paper no. TPWRS-00469-2019. (Corresponding author: Mohamed Shawky El Moursi.) B. Mohandes, S. Acharya, and A. S. Al-Sumaiti are with the Electrical Engineering and Computer Science Department, Khalifa University, Abu Dhabi 127788, UAE (e-mail: [email protected]; [email protected]; [email protected]). M. S. E. Moursi is with the Advanced Power and Energy Center, EECS FacultyofEngineering,MansouraUniversity,Mansoura35516,Egypt(e-mail:Department,KhalifaUniversity,AbuDhabi127788,UAE,andonleavefromthe C OMMERCIAL building microgrids are gaining attention [email protected]). due to the growing interest in clean and sustainable fu-H.DoukasiswiththeManagement&DecisionSupportSystemsLaboratory, ture energy. Renewable Energy System (RES) deployment is (e-mail:[email protected]).SchoolofECE,NationalTechnicalUniversityofAthens,15780,Athens,Greece growing rapidly in the power generation portfolio because of S. Sgouridis is with the Dubai Electricity and Water Authority’s R&D Center, the technological breakthroughs and the fall in RES cost. RES Dubai,U.A.E.(e-mail:[email protected]). adoption rate is also expected to accelerate in the foreseeable athttp://ieeexplore.ieee.org.Colorversionsofoneormoreofthefiguresinthisarticleareavailableonline future [1]. However, RES variability remains a standing issue, Digital Object Identifier 10.1109/TPWRS.2020.2969575 and engineers are compelled to deploy energy buffers. Demand 0885-8950 © 2020 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.
Publisher Copyright:
© 1969-2012 IEEE.
PY - 2020/7
Y1 - 2020/7
N2 - This paper investigates an optimal sizing strategy for an islanded building microgrid. The microgrid composites a rooftop Photovoltaic (PV) system, a Battery Energy Storage System (BESS), an ice-Thermal Energy Storage System (ice-TESS), and loads. The loads are divided into two sets based on their ability to participate in demand response: i) Plugged Loads (PL) such as lights, and ii) Cooling Loads (CL) such as air-conditioners. The microgrid is islanded and loads must be supplied with local generation resources. Therefore, the BESS is deployed to offset the PV output's variability, and the absence of PV power supply at night time. However, relying only on the BESS incurs high stress and shortens the BESS's lifetime. Hence, we propose an optimal sizing strategy of the microgrid constituents, where the BESS coordinates with the ice-TESS to maintain the balance between generation and load in the microgrid. Nevertheless, the dispatch commands cannot swing freely between the two ESSs because of the difference in the type of energy delivery. Specifically, the BESS stores electric energy and can supply both PL and CL. On the other hand, the TESS can only supply the CL. Hence, the BESS-TESS coordination is also aided by a customer-friendly shifting and curtailment mechanism of CL. The design incorporates the effect of weather uncertainty on the PV output. Weather variations are imitated using Recurrent Neural Networks trained on 19-years of contiguous hourly weather data. After optimizing the sizes of the microgrid constituents, the optimal sizes are used in a detailed dynamic model of the system for a real-time simulation on the OPAL-RT platform. The validation results demonstrate the successful coordinated operation of the microgrid constituents which are cost-effective in sizing.
AB - This paper investigates an optimal sizing strategy for an islanded building microgrid. The microgrid composites a rooftop Photovoltaic (PV) system, a Battery Energy Storage System (BESS), an ice-Thermal Energy Storage System (ice-TESS), and loads. The loads are divided into two sets based on their ability to participate in demand response: i) Plugged Loads (PL) such as lights, and ii) Cooling Loads (CL) such as air-conditioners. The microgrid is islanded and loads must be supplied with local generation resources. Therefore, the BESS is deployed to offset the PV output's variability, and the absence of PV power supply at night time. However, relying only on the BESS incurs high stress and shortens the BESS's lifetime. Hence, we propose an optimal sizing strategy of the microgrid constituents, where the BESS coordinates with the ice-TESS to maintain the balance between generation and load in the microgrid. Nevertheless, the dispatch commands cannot swing freely between the two ESSs because of the difference in the type of energy delivery. Specifically, the BESS stores electric energy and can supply both PL and CL. On the other hand, the TESS can only supply the CL. Hence, the BESS-TESS coordination is also aided by a customer-friendly shifting and curtailment mechanism of CL. The design incorporates the effect of weather uncertainty on the PV output. Weather variations are imitated using Recurrent Neural Networks trained on 19-years of contiguous hourly weather data. After optimizing the sizes of the microgrid constituents, the optimal sizes are used in a detailed dynamic model of the system for a real-time simulation on the OPAL-RT platform. The validation results demonstrate the successful coordinated operation of the microgrid constituents which are cost-effective in sizing.
KW - Battery storage
KW - demand side management
KW - islanded system
KW - load shifting
KW - real-time simulation
KW - thermal storage systems
KW - weather scenarios
UR - http://www.scopus.com/inward/record.url?scp=85086997569&partnerID=8YFLogxK
U2 - 10.1109/TPWRS.2020.2969575
DO - 10.1109/TPWRS.2020.2969575
M3 - Article
AN - SCOPUS:85086997569
SN - 0885-8950
VL - 35
SP - 2642
EP - 2657
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 4
M1 - 8970322
ER -