Development and application of smart algorithms for control and management in buildings, towards zero energy buildings

The scope of the present doctoral thesis is to develop and integrate building optimization and control algorithms which: (1) safeguard the comfort of occupants, (2) reduce the energy consumption of the HVAC equipment, (3) embody and manage the energy production from RES, (4) can be integrated in existing and new BEMS and (5) facilitate the transformation of any building towards a zero energy building. The main characteristics of the developed BOC algorithms are to:•Integrate predictive models for outdoor and indoor conditions to facilitate calculation of the performance of the HVAC systems.•Incorporate optimization algorithms which predict the optimum operation of the HVAC systems in the near future.•Apply close loop control which minimizes the difference between the set-points and the actual values.•Combine the calculations from the optimization with human interference, when required, in order to guarantee that potential failure of a subsystem is not affecting the whole BOC structure.The different sub-systems which compose the BOC algorithms are:A closed loop control algorithm for safeguarding the comfort conditions and reduce the energy consumption from waste energy.A predictive algorithm for outdoor conditions which affect the buildings’ fabric and the operation of the HVAC systemsA predictive algorithm for indoor conditions which estimate the indoor conditions under the predicted outdoor conditions and the use of the HVAC systemAn optimization algorithm which sets the set-point of the AHU for the near future in order to exploit the thermal mass of the buildings’ fabric.An override sequence which bypasses all the system and allows authorized/trained personnel to send commands directly to the HVAC and artificial lights.Thermal and lighting models of hospital facilities are developed and validated with collected measurements. The thermal models are used to preliminary estimate energy requirements of buildings and the comfort of occupants. Furthermore, the thermal modes are used for the fine-tuning of the control algorithms and the estimation of their energy efficiency potential. The thermal models incorporate the geometry of the buildings, the construction characteristics and the internal gains. The thermal models are connected with the BOC algorithms development software. The thermal models point the direction the developed algorithms should follow to transform the energy consuming buildings to zero energy ones.Advanced control algorithms for AHU and artificial lights are designed and fine-tuned to safeguard the comfort level and reduce the energy losses from wasted energy. The control algorithms use the knowledge from the users in the form of rules and their parameters are easily fine-tuned, if required. The reduction of the energy losses contribute to the target of zero energy buildings.Innovative identification algorithms are developed in order to estimate in advance the conditions of the facilities in order to adjust the usage of the HVAC equipment. The identification algorithms predict indoor and outdoor conditions. The a priori knowledge assists the definition of plans which can reduce the energy consumption of the next hours of operation, reducing the power demand for specific hours of the day.Furthermore, optimization algorithms using genetic techniques are used to select the most “profitable” operation of the HVAC system in the next hours. The solution selected from the optimization algorithm minimizes the operational cost of the HVAC system over the next hours while the comfort level can be maintained. The optimization algorithms can integrate additional energy efficiency technologies such as RES and swift the loads when RES provide power.The BOC algorithms are integrated in specific facilities of the two Hospitals (Hospital of Chania and Hospital of Ancona, Italy) and the energy efficiency are calculated at 57% and 55% for the Air handling Units and the artificial lights respectively for the hospital of Chania and 75 % for the artificial lights in the hospital of Ancona.The present thesis provides a completed innovative optimization and control system which can be applied to existing BEMS or new ones in order to maximize the energy efficiency of the systems. The optimization and control system has achieved significant energy efficiency in both pilot hospitals, without compromising the comfort (visual or thermal) of patients. Another significant advantage the new control algorithms is the ability to be accessed and monitored from distance by means of a Web-EMCS internet platform.Ο στόχος της παρούσας διδακτορικής διατριβής είναι η παρουσίαση της ανάπτυξης και ενσωμάτωσης σύγχρονων αλγορίθμων ελέγχου και βελτιστοποίησης σε κτίρια οι οποίοι: (1) διασφαλίζουν την άνεση των χρηστών, (2) μειώνουν την κατανάλωση ενέργειας των κτιρίων, (3) ενσωματώνουν και διαχειρίζονται την παραγωγή ενέργειας από ΑΠΕ, (4) μπορούν να ενσωματωθούν σε υπάρχοντα συστήματα διαχείρισης ενέργειας κτιρίων και (5) συμβάλουν στην μετατροπή ενός κτιρίου σε κτίριο μηδενικής ενεργειακής κατανάλωσης.Τα κύρια χαρακτηριστικά των αλγορίθμων ελέγχου και βελτιστοποίησης οι οποίοι αναπτύχθηκαν είναι:•Η ενσωμάτωση προβλεπτικών αλγορίθμων για εξωτερικές και εσωτερικές συνθήκες που συμβάλουν στον υπολογισμό της ενεργειακής συμπεριφοράς των συστημάτων θέρμανσης ψύξης και αερισμού.•Η χρήση αλγορίθμων βελτιστοποίησης οι οποίοι υπολογίζουν την βέλτιστη χρήση των συστημάτων θέρμανσης ψύξης και αερισμού για τα επόμενα χρονικά βήματα.•Η εφαρμογή κλειστών βρόγχων ελέγχου οι οποίοι ελαχιστοποιούν την διαφορά μεταξύ των επιθυμητών και πραγματικών τιμών.•Ο συνδυασμός των υπολογισμών από το σύστημα βελτιστοποίησης και την ανθρώπινη παρέμβαση, όταν αυτή χρειάζεται, έτσι ώστε πιθανό σφάλμα σε ένα από τα υποσυστήματα δεν θα επηρεάζει το σύνολο του αλγορίθμου βελτιστοποίησης.Τα διαφορετικά υποσυστήματα που ενσωματώνονται στους αλγόριθμους ελέγχου και βελτιστοποίησης είναι:•Υποσύστημα κλειστού βρόγχου για τη διασφάλιση της άνεσης και της μείωσης των απωλειών ενέργειας λόγω σπατάλης.•Υποσύστημα πρόβλεψης της εξωτερικής θερμοκρασίας, διότι αυτή επηρεάζει τη θερμική άνεση του κτηρίου, καθώς και της κατανάλωσης των συστημάτων θέρμανσης ψύξης και αερισμού.•Υποσύστημα πρόβλεψης της εσωτερικής θερμοκρασίας το οποίο αξιοποιεί την πρόβλεψη της εξωτερικής θερμοκρασίας και την κατάσταση λειτουργίας των συστημάτων θέρμανσης ψύξης και αερισμού.•Υποσύστημα αλγορίθμου βελτιστοποίησης που υπολογίζει τη ρύθμιση του θερμοστάτη για τα επόμενα χρονικά βήματα.•Υποσύστημα παράκαμψης για τα παραπάνω υποσυστήματα, ώστε προσωπικό του κτιρίου, με χρήση κωδικού πρόσβασης και κατάλληλη εκπαίδευση να μπορεί να ενεργοποιεί/ απενεργοποιεί εξ’ αποστάσεως τα κλιματιστικά και τα φώτα.Αναπτύχθηκαν κατάλληλα μοντέλα προσομοίωσης της θερμικής και της οπτικής συμπεριφοράς του κτιρίου, τα οποία επικυρώθηκαν με μετρήσεις πεδίου. Τα θερμικά μοντέλα χρησιμοποιούνται για την αρχική αξιολόγηση της ετήσιας κατανάλωσης των κτιρίων καθώς και την θερμική άνεση των ενοίκων. Τα θερμικά μοντέλα συνδέονται με τους αλγόριθμους ελέγχου. Επιπλέον, τα επικυρωμένα θερμικά μοντέλα αξιοποιούνται για την επιβεβαίωση της συμπεριφοράς των αλγορίθμων ελέγχου κλειστού βρόγχου και για την εκτίμηση της ετήσιας εξοικονόμησης ενέργειας. Τα θερμικά μοντέλα ενσωματώνουν την γεωμετρία των κτηρίων, τα κατασκευαστικά χαρακτηριστικά τους καθώς και τα εσωτερικά κέρδη. Τα αποτελέσματα των θερμικών μοντέλων υποδεικνύουν την κατεύθυνση που πρέπει να ακολουθήσουν οι αλγόριθμοι ελέγχου ώστε να μετατραπεί ένα ενεργοβόρo κτήριο σε κτήριο μηδενικής ενεργειακής κατανάλωσης.Σχεδιάστηκαν ευφυείς αλγόριθμοι ελέγχου για τις κλιματιστικές μονάδες και τα τεχνητά φώτα και ρυθμίστηκαν κατάλληλα με στόχο να συμβάλλουν στη διατήρηση της θερμικής άνεσης και στη μείωση των ενεργειακών απωλειών λόγω σπατάλης ενέργειας. Οι αλγόριθμοι ελέγχου αξιοποιούν τη γνώση των διαχειριστών του συστήματος συντάσσοντας κανόνες, ενώ οι υπόλοιπες παράμετροι προσαρμόζονται εύκολα. Η συμβολή των αλγορίθμων ελέγχου στη μείωση της εξοικονόμησης ενέργειας συμβάλει στη μετατροπή του κοινού κτιρίου σε κτίριο μηδενικής ενεργειακής κατανάλωσης (zero energy building).Αναπτύχθηκαν καινοτόμοι προβλεπτικοί αλγόριθμοι για την εκ προοιμίου εκτίμηση της συμπεριφοράς των συστημάτων θέρμανσης ψύξης και αερισμού. Οι προβλεπτικοί αλγόριθμοι εκτιμούν τις εσωτερικές και εξωτερικές συνθήκες. Η εκ των προτέρων γνώση, βοηθάει στην ανάπτυξη δράσεων που μπορούν να μειώσουν τη μέγιστη ζήτηση ισχύος σε συγκεκριμένες ώρες την μέρα. Με τον τρόπο αυτό μειώνεται η εξάρτηση του κτιρίου από το ηλεκτρικό δίκτυο.Επιπλέον, αναπτύχθηκαν εξελικτικοί αλγόριθμοι βασισμένοι στην γενετική εξέλιξη, ώστε να επιλεχθεί η πιο «συμφέρουσα» λύση για την χρήση των συστημάτων θέρμανσης και ψύξης για τις επόμενες ώρες. Η έξοδος των γενετικών αλγορίθμων μειώνει το συνολικό κόστος χρήσης των κλιματιστικών μονάδων, ενώ παράλληλα διασφαλίζει τη θερμική άνεση. Τέλος, οι αλγόριθμοι βελτιστοποίησης μπορούν επιπλέον να λαμβάνουν υπόψη την παραγωγή από ανανεώσιμες πηγές ενέργειας, ώστε να μετακινούν την μέγιστη ζήτηση ενέργειας όταν οι ΑΠΕ παράγουν την μέγιστη δυνατή ισχύ. Έτσι μειώνεται η μέγιστη ζήτηση ισχύος από τον πάροχο και το κτήριο τείνει προς την μηδενική ενεργειακή κατανάλωση.Οι προτεινόμενοι αλγόριθμοι ελέγχου και βελτιστοποίησης ενσωματώθηκαν στα υπάρχοντα συστήματα διαχείρισης ενέργειας δύο επιλεγμένων Νοσοκομείων (Νοσοκομείο των Χανίων και Νοσοκομείο της Ανκόνα, Ιταλία). Η εξοικονόμηση ενέργειας που επιτεύχθηκε από τη χρήση τους στο Νοσοκομείο των Χανίων είναι 57 % και 55 % για θέρμανση/ψύξη και ηλεκτρικό φωτισμό, ενώ για το Νοσοκομείο της Ανκόνα προέκυψε εξοικονόμηση 75 % για φωτισμό .Η παρούσα εργασία παρουσιάζει ένα ολοκληρωμένο και καινοτόμο σύστημα βελτιστοποίησης και ελέγχου το οποίο μπορεί να ενσωματωθεί είτε σε υπάρχοντα συστήματα διαχείρισης ενέργειας ή σε νέα και μπορεί να μεγιστοποιήσει την εξοικονόμηση ενέργειας. Η χρήση των αλγορίθμων ελέγχου και βελτιστοποίησης έδειξε ότι επιτυγχάνεται σημαντική εξοικονόμηση ενέργειας χωρίς να υποβαθμίζεται η άνεση (θερμική και οπτική) των ασθενών και των ιατρών. Ένα σημαντικό χαρακτηριστικό των νέων αλγορίθμων είναι η δυνατότητα πρόσβασης και παρακολούθησης της συμπεριφοράς τους εξ αποστάσεως μέσω της διαδικτυακής πλατφόρμας Web-Energy Management Control Systems (EMCS)

Development and application of smart algorithms for control and management in buildings, towards zero energy buildings

Summarization: The scope of the present doctoral thesis is to develop and integrate building optimization and control algorithms which: (1) safeguard the comfort of occupants, (2) reduce the energy consumption of the HVAC equipment, (3) embody and manage the energy production from RES, (4) can be integrated in existing and new BEMS and (5) facilitate the transformation of any building towards a zero energy building. The main characteristics of the developed BOC algorithms are to: • Integrate predictive models for outdoor and indoor conditions to facilitate calculation of the performance of the HVAC systems. • Incorporate optimization algorithms which predict the optimum operation of the HVAC systems in the near future. • Apply close loop control which minimizes the difference between the set-points and the actual values. • Combine the calculations from the optimization with human interference, when required, in order to guarantee that potential failure of a subsystem is not affecting the whole BOC structure. The different sub-systems which compose the BOC algorithms are: A closed loop control algorithm for safeguarding the comfort conditions and reduce the energy consumption from waste energy. A predictive algorithm for outdoor conditions which affect the buildings’ fabric and the operation of the HVAC systems A predictive algorithm for indoor conditions which estimate the indoor conditions under the predicted outdoor conditions and the use of the HVAC system An optimization algorithm which sets the set-point of the AHU for the near future in order to exploit the thermal mass of the buildings’ fabric. An override sequence which bypasses all the system and allows authorized/trained personnel to send commands directly to the HVAC and artificial lights. Thermal and lighting models of hospital facilities are developed and validated with collected measurements. The thermal models are used to preliminary estimate energy requirements of buildings and the comfort of occupants. Furthermore, the thermal modes are used for the fine-tuning of the control algorithms and the estimation of their energy efficiency potential. The thermal models incorporate the geometry of the buildings, the construction characteristics and the internal gains. The thermal models are connected with the BOC algorithms development software. The thermal models point the direction the developed algorithms should follow to transform the energy consuming buildings to zero energy ones. Advanced control algorithms for AHU and artificial lights are designed and fine-tuned to safeguard the comfort level and reduce the energy losses from wasted energy. The control algorithms use the knowledge from the users in the form of rules and their parameters are easily fine-tuned, if required. The reduction of the energy losses contribute to the target of zero energy buildings. Innovative identification algorithms are developed in order to estimate in advance the conditions of the facilities in order to adjust the usage of the HVAC equipment. The identification algorithms predict indoor and outdoor conditions. The a priori knowledge assists the definition of plans which can reduce the energy consumption of the next hours of operation, reducing the power demand for specific hours of the day. Furthermore, optimization algorithms using genetic techniques are used to select the most “profitable” operation of the HVAC system in the next hours. The solution selected from the optimization algorithm minimizes the operational cost of the HVAC system over the next hours while the comfort level can be maintained. The optimization algorithms can integrate additional energy efficiency technologies such as RES and swift the loads when RES provide power. The BOC algorithms are integrated in specific facilities of the two Hospitals (Hospital of Chania and Hospital of Ancona, Italy) and the energy efficiency are calculated at 57% and 55% for the Air handling Units and the artificial lights respectively for the hospital of Chania and 75 % for the artificial lights in the hospital of Ancona. The present thesis provides a completed innovative optimization and control system which can be applied to existing BEMS or new ones in order to maximize the energy efficiency of the systems. The optimization and control system has achieved significant energy efficiency in both pilot hospitals, without compromising the comfort (visual or thermal) of patients. Another significant advantage the new control algorithms is the ability to be accessed and monitored from distance by means of a Web-EMCS internet platform

Prediction of outdoor air temperature using neural networks: application in 4 european cities

Summarization: The aim of this paper is to present the development and evaluation of neural network based identification algorithms for the prediction of outdoor air temperature using acquired data from four European cities (Ancona - Italy, Chania - Greece, Granada - Spain and Mollet - Spain). Different neural network topologies (feed forward, cascade and elman) have been tested to identify the most suitable for each city. The efficiency of the prediction is validated by comparing predicted and measured outdoor air temperature. Furthermore, statistical tools such as R2, and root mean square error (rmse) are used to evaluate the annual performance of the neural network. The comparison of measured and predicted outdoor air temperature (R2 > 0.9, rmse <2 °C) confirms the accurate training of the neural network for all four European cities. All work has been contacted using Matlab's environment.Presented on: Energy and Building

Guidelines on retrofitting of shopping malls

publishedVersio

Guidelines on how to approach the energy-efficient retrofitting of shopping centres

Special architectural conditions and needs are common in almost all shopping centres. The main retrofit drivers are: (i) improve the indoor environmental quality and functionality, to enhance the customers experience; (ii) reduce the energy consumption; (iii) optimize the building operation and relative maintenance costs and (iv) improve the overall sustainability level reducing the environmental, social, and economic impact. Shopping centres vary in their functions, typologies, forms and size, as well as the (shopping) trip purpose. To consider the shopping centre building stock as one segment with its own boundaries and trends, the EU FP7 CommONEnergy project set a shopping centre definition1: “A shopping centre is a formation of one or more retail buildings comprising units and ‘communal’ areas, which are planned and managed as a single entity related in its location, size and type of shops to the trade area that it serves.” The European wholesale and retail sector is the big marketplace of Europe, contributing with around 11% of the EU’s GDP2. Therefore, sustainability of the retail sector may significantly contribute to reaching the EU long-term environmental and energy goals. Within the retail sector, shopping centres are of particular interest due to: their structural complexity and multi-stakeholders’ decisional process, their high energy savings and carbon emissions reduction potential, as well as their importance and influence in shopping tendencies and lifestyle. A shopping centre is a building, or a complex of buildings, designed and built to contain many interconnected activities in different areas. Next to public spaces, there are areas related to work spaces, with different use and location and according to the shopping centre type. They have different opening hours and entrances than the shopping centre. Today, in addition to the mere commercial function, a shopping centre responds to several customer needs: it exhibits recreational attractions …publishedVersio

The use of algorithms for light control

Summarization: Because light directly influences human health, requirements on lighting levels must be constantly fulfilled. The lighting control market represents, therefore, an innovative sector that empowers a start-up's potential and where customers are highly looking for solutions that have low costs and high life expectancy, and that are least intrusive. Consequently, the control algorithms implemented are crucial in order to maximize efficiency while satisfying all the aforementioned specifications. This chapter introduces light-control algorithms as enabler of differentiation, which is a key requirement for a successful start-up rollout. Moreover, the proposed control lighting systems are customized and implemented in three real operational environments: two hospitals and one office building, all located in the Mediterranean area. The implementations show significant energy savings with low up-front and installation costs: this demonstrates the importance of control algorithms in lighting systems as high energy savings are achieved and lighting requirements fulfilled.Appearing in: Start-Up Creation: The Smart Eco-Efficient Built Environmen

Retrofitting an office building towards a net zero energy building

Δημοσίευση σε επιστημονικό περιοδικόSummarization: Energy consumption in buildings for heating, cooling and lighting is required to be reduced in all European countries in order for the goals set by the latest European Directives for reducing energy consumption by 20% and increasing the introduction of renewable energy sources by 20% to be achieved. The present paper focuses, initially, on the reduction of energy consumption of an office building in the campus of the Technical University of Crete as well as on the cover of minimized energy demands with renewable energy sources. The approach is simulation based. Firstly, the current heating and cooling demands of the building are estimated. Subsequently, some basic energy conservation techniques are applied and a detailed analysis is performed about the new energy requirements. Finally, renewable energy sources are implemented in order to provide energy to the building or directly into the grid, thus having a net zero energy building.Παρουσιάστηκε στο: Advances in Building Energy Researc

Urban gardens as a solution to energy poverty and urban heat island

Summarization: In a highly structured environment, as an urban center, there are impacts for both humans and the environment. The urban heat island effect and energy poverty are impacts of this situation. A common way to deal with the last two impacts is to reduce the temperature by using bioclimatic design. This research is the subject of a project at the Technical University of Crete about the use of urban gardens as a way to reduce the air and surface temperature in Chania, and more specifically in the district of Chalepa. The threats to biodiversity and the relevant legislative framework are presented. In this research, a scenario with absence of vegetation, the current state and two scenarios with different vegetation in urban gardens are analyzed. The first scenario involves horticulture species and the second one the cultivation of aromatic and medicinal species. These scenarios were examined using the numerical model Envi-met after the collection of data needed such as the height of buildings, vegetation characteristics, the location of the area etc. Finally, the scenarios of urban gardens decreased the surface temperature by 10 °C from the scenario with absence of vegetation and 5° C from the current state in days of high temperature. However, the differences between these two scenarios were not of great importance.Keywords: Energy saving, Urban Heat Island, Environmental planning, Urban green space, Community Gardening.Παρουσιάστηκε στο: Sustainable Cities and Societ

Neuro-fuzzy model based predictive algorithm for environmental management of buildings

Summarization: This paper presents an algorithm used for predicting indoor environmental conditions in buildings considering outdoor conditions such as outdoor temperature and humidity as well as window position and operating conditions of an air conditioning unit. Sensors which are part of an existing Building Energy Management System (BEMS) read necessary data in real time and the values are also stored in database for further analysis. The pre-mentioned algorithms are based on an Adaptive-Network-Based Fuzzy Inference System (ANFIS) which are trained and validated with historical data stored in the database. The results of predicting indoor environmental conditions over a considerable predictive horizon are presented and discussed. Further development is planned on the development of smaller systems based on microcomputers to store data from sensors, run the main control algorithms and actuate the necessary componentsΠαρουσιάστηκε στο: 3rd International Conference on Industrial and Hazardous Waste Managemen

Building optimization and control algorithms implemented in existing BEMS using a web based energy management and control system

Δημοσίευση σε επιστημονικό περιοδικόSummarization: The aim of the present paper is to analyze a building optimization and control (BOC) algorithm which is implemented in the existing building energy management system (BEMS) of the Saint George Hospital in Chania, Greece. The developed algorithm consists of predicted models for outdoor/indoor air temperature using artificial neural networks, multi-step optimization using genetic algorithms and Real Time control using fuzzy techniques. The algorithm is developed in Matlab™ environment and is implemented to the existing BEMS of the Hospital, using a specialized web-based energy management and control system (Web-EMCS). The implementation of the BOC algorithm is realized by developing a “.net assembly” code, which interconnects the Web-EMCS with the existing conventional hospital's BEMS, without the need of Matlab™. The annual primary energy efficiency achieved is almost 36%.Παρουσιάστηκε στο: Energy and Building