Next Article in Journal
Modelling the Costs and Benefits of Modern Energy Cooking Services—Methods and Case Studies
Next Article in Special Issue
Enabling Optimal Energy Management with Minimal IoT Requirements: A Legacy A/C Case Study
Previous Article in Journal
Modeling and Analysis of the Power Conditioning Circuit for an Electromagnetic Human Walking-Induced Energy Harvester
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Energies
Volume 14
Issue 12
10.3390/en14123369
energies-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Model Predictive Control for the Energy Management in a District of Buildings Equipped with Building Integrated Photovoltaic Systems and Batteries

by
Maria C. Fotopoulou
*,
Panagiotis Drosatos
,
Stefanos Petridis
,
Dimitrios Rakopoulos
,
Fotis Stergiopoulos
and
Nikolaos Nikolopoulos
Chemical Process and Energy Resources Institute, Center for Research and Technology Hellas, 6th km Charilaou-Thermi Road, GR-57001 Thermi, Thessaloniki, Greece
*
Author to whom correspondence should be addressed.
Energies 2021, 14(12), 3369; https://doi.org/10.3390/en14123369
Submission received: 5 May 2021 / Revised: 4 June 2021 / Accepted: 5 June 2021 / Published: 8 June 2021
(This article belongs to the Special Issue Innovative Solutions towards Autonomous Modular Facade Systems)
Browse Figures
Versions Notes

Abstract

This paper introduces a Model Predictive Control (MPC) strategy for the optimal energy management of a district whose buildings are equipped with vertically placed Building Integrated Photovoltaic (BIPV) systems and Battery Energy Storage Systems (BESS). The vertically placed BIPV systems are able to cover larger areas of buildings’ surfaces, as compared with conventional rooftop PV systems, and reach their peak of production during winter and spring, which renders them suitable for energy harvesting especially in urban areas. Driven by both these relative advantages, the proposed strategy aims to maximize the district’s autonomy from the external grid, which is achieved through the cooperation of interactive buildings. Therefore, the major contribution of this study is the management and optimal cooperation of a group of buildings, each of which is equipped with its own system of vertical BIPV panels and BESS, carried out by an MPC strategy. The proposed control scheme consists of three main components, i.e., the forecaster, the optimizer and the district, which interact periodically with each other. In order to quantitatively evaluate the benefits of the proposed MPC strategy and the implementation of vertical BIPV and BESS, a hypothetical five-node distribution network located in Greece for four representative days of the year was examined, followed by a sensitivity analysis to examine the effect of the system configuration on its performance.
Keywords: model predictive control; battery energy storage systems; energy management; district level; vertical photovoltaics; optimization; energy community model predictive control; battery energy storage systems; energy management; district level; vertical photovoltaics; optimization; energy community

Share and Cite

MDPI and ACS Style

Fotopoulou, M.C.; Drosatos, P.; Petridis, S.; Rakopoulos, D.; Stergiopoulos, F.; Nikolopoulos, N. Model Predictive Control for the Energy Management in a District of Buildings Equipped with Building Integrated Photovoltaic Systems and Batteries. Energies 2021, 14, 3369. https://doi.org/10.3390/en14123369

AMA Style

Fotopoulou MC, Drosatos P, Petridis S, Rakopoulos D, Stergiopoulos F, Nikolopoulos N. Model Predictive Control for the Energy Management in a District of Buildings Equipped with Building Integrated Photovoltaic Systems and Batteries. Energies. 2021; 14(12):3369. https://doi.org/10.3390/en14123369

Chicago/Turabian Style

Fotopoulou, Maria C., Panagiotis Drosatos, Stefanos Petridis, Dimitrios Rakopoulos, Fotis Stergiopoulos, and Nikolaos Nikolopoulos. 2021. "Model Predictive Control for the Energy Management in a District of Buildings Equipped with Building Integrated Photovoltaic Systems and Batteries" Energies 14, no. 12: 3369. https://doi.org/10.3390/en14123369

APA Style

Fotopoulou, M. C., Drosatos, P., Petridis, S., Rakopoulos, D., Stergiopoulos, F., & Nikolopoulos, N. (2021). Model Predictive Control for the Energy Management in a District of Buildings Equipped with Building Integrated Photovoltaic Systems and Batteries. Energies, 14(12), 3369. https://doi.org/10.3390/en14123369

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop