Proactive Building Energy Management based on Fuzzy Logic and Expert Intelligence
THE AIM OF THE PROJECT
The main goal of this project is to develop expert intelligence tools to be incorporated in commercial energy management platforms for proactive energy management and optimization of energy savings. To this end, three (3) fuzzy logic powered tools will be deployed to be incorporated in well-known SaaS platforms used for energy management to further improve decision making related to smart fault detection and diagnostics as well as intelligent predictive maintenance of basic equipment.
The first tool, the so-called expertFDD analyser,will be a core fault detection and diagnostics tool related to common building equipment, such as HVACs, lighting, machines, PV plants, pumps, etc., enhancing ongoing monitoring-based commissioning of building systems to save energy and extend equipment life.
The second tool, the so-called HVAC system optimizer, will be based on a fuzzy inference engine for optimizing HVAC system operation in order to increase comfort, reduce energy costs and shift peak demand. The third tool, the so-called maintenance expert, will be a cost-effective maintenance tool to predict future maintenance needs on basic building equipment with the view of further optimizing its operation across time.
OBJECTIVES
The cooperating companies, Meazon and GPM, will use their energy monitoring and analytics platforms to provide LAR with historical raw energy measurements of basic building equipment. Both companies will exchange knowhow and utilize their advanced own products (i.e., gateways and units) for measurements in this project.
Furthermore, on the one hand, Meazon and LAR will closely collaborate to deliver an expert FDD analyser to detect and diagnose faults related to common building equipment and to propose fixes and workarounds, and on the other hand, GPM and LAR will fruitfully cooperate to deliver an HVAC system optimizer to increase comfort, reduce energy costs and shift peak demand. Finally, all partners together will join forces to deliver a maintenance expert to predict future maintenance needs on basic building equipment with the view of further optimizing its operation across time.
STATE OF THE ART TECHNOLOGY
Commercial building owners spend 30% of their operating budget on energy. Costs can be reduced with improved building energy management practices. Optimizing building performance also reduces demand for energy from the grid, lowers carbon emissions from electricity generation and fuels burned on site, and can improve occupant comfort.
Today, buildings can fall anywhere along the continuum of data management and analytics: trending, benchmarking, fault detection and diagnostics, forecasting, customized software applications, cloud computing data analysis.
Fault Detection and Diagnostics (FDD) analysis enables ongoing monitoring-based commissioning of building systems to save energy and extend equipment life. Faults relate to a system’s performance, meaning the system is operating but is performing sub-optimally. FDD tools acquire electricity, gas, steam, temperature, humidity, or chilled water energy consumption data, typically at the building level via an energy management platform, and compare those values to expected baseline energy consumption levels. The tool flags building energy consumption as high when it exceeds the baseline value by a predetermined threshold (to avoid false alarms). Often, the baseline takes into account one or more key explanatory variables, such as outdoor air temperature, building and equipment schedules, time of day or year, temperature set points, and plant configurations. Table 1 describes the broad range of possible baselines for FDD in order of increasing complexity. FDD is an important type of analysis to complete because inefficient equipment operation attributed to inadequate initial commissioning, operational issues, and real time performance degradation can waste an estimated 15 to 30% of energy used in commercial buildings. However, current FDD methods are limited to classification and pattern recognition to detect and diagnose faults.
TECHNOLOGICAL DEVELOPMENTS
The main goal of this project is to develop expert intelligence tools to be incorporated in commercial energy management platforms for proactive energy management in buildings to further optimize energy savings. To this end, three (3) fuzzy logic powered tools will be deployed to be incorporated in well-known SaaS platforms used for energy management to further improve decision making related to smart fault detection and diagnostics as well as intelligent predictive maintenance of basic equipment as follows:
- an expert FDD analyser,
- an HVAC system optimizer, and
- a maintenance expert.
Proactive fault diagnostics is the process of proactively manipulating system inputs to perform a diagnostic test. It consists of a diagnostic part and a proactive testing part. The proactive testing part manipulates/directs the input and the diagnostic part analyses the output to assess the system’s health status. The goal of proactive testing is to control adjustable parameters—for example, set-point, mode, schedule, damper position, fan speed, and so on—to facilitate and complete the diagnostic process. Fuzzy logic has turned out to be a popular choice for these types of problems. The inherent flexibility embedded in fuzzy sets and fuzzy rules make it a suitable solution for reasoning in domains affected by uncertainty and error. In building HVAC systems, fuzzy-based diagnostic mechanisms have been used in several studies. In this project, during the implementation of our expert FDD analyser we will develop fuzzy-based diagnostic routines for fault detection and diagnosis of various units of common building equipment, such as HVACs, PV plants, pumps, etc. In our approach, fuzzy-based inference mechanisms will compare system outputs with the predictions of simplified models at various operating points to draw conclusions about the system health status.
On the other hand, next generation BEMSs will help building owners to better manage the performance of their buildings, anticipate potential for savings or HVAC issues before they happen, and shift operations and maintenance team efforts from reactive to proactive systems management. Besides, solution providers have a specific interest in meeting the needs of smaller facilities. Vendors from the traditional automation and control segment, IT and niche specialty providers have identified HVAC system optimization as a specific avenue through which BEMSs can support smaller facilities. For instance, to decrease the energy consumption researchers in the area of thermal comfort have learned that the required indoor temperature of a building is not a fixed value. In fact, the certain range of temperatures is sufficient to create a comfortable situation. Therefore, the ideal HVAC system works with high efficiency supplying only the amount of heat, cold and air that is necessary to maintain internal conditions at a level providing thermal comfort to room occupants. In this project, users can benefit from more savings with the advanced features of our HVAC system optimizer – based on a fuzzy inference engine -, such as operating set point adjustment, inference control for variable frequency drives, etc.
Finally, when building system components unexpectedly fail, you face costly downtime and unsatisfiedoccupants. With predictive maintenance, you’ll identify potential hidden problems prior to breakdowns and proactively schedule repairs at times that won’t inconvenience you or your building’s occupants. Furthermore, predictive maintenance helps you control energy costs, prolong equipment life and prevent overtime costs for unscheduled repairs. With an expert system the status and past maintenance history of basic building equipment are used to do the work in a thorough and consistent manner. An expert system for predictive maintenance requires several functions to make it usable to a building owner or professional, including configuration ability, site visit types, user interaction, explanations, graphics, context sensitivity, displaying readings, logging conditions, deferring work, reports, comments and display. Whether this expert system is successful or not depends on an additional important factor: to take into account the availability of a real expert in the discipline, familiar with all operations and problems with the building systems services. In this project, our maintenance expert will be a fuzzy logic expert tool to predict future maintenance needs of basic building equipment by leveraging past performance, logging conditions, reports, prior FDD analysis, ESCOs knowledge and support, etc.
EXPECTED RESULTS
The successful implementation of this project will produce a number of useful and innovative results.
Three (3) fuzzy logic powered tools will be deployed to be incorporated in well-known SaaS platforms used for energy management to further improve decision making related to smart fault detection and diagnostics as well as intelligent predictive maintenance of basic equipments.
The first tool, the so-called expertFDD analyser, will be a core fault detection and diagnostics tool related to common building equipment, such as HVACs, PV plants, pumps, etc., enhancing ongoing monitoring-based commissioning of building systems to save energy and extend equipment life.
The second tool, the so-called HVAC system optimizer, will be based on a fuzzy inference engine for optimizing HVAC system operation in order to increase comfort, reduce energy costs and shift peak demand.
The third tool, the so-called maintenance expert, will be a cost-effective maintenance tool to predict future maintenance needs on basic building equipment with the view of further optimizing its operation across time.
In addition some excellent theoretical results are expected. New control mechanisms using fuzzy logic will be developed:
- fuzzy-based diagnostic routines for fault detection and diagnosis of various units of common building equipment, such as HVACs, PV plants, pumps, etc.,
- a fuzzy inference engine for optimizing HVAC system operation, and
- a fuzzy expert system to predict future maintenance needs of basic building equipment
- development of smart building energy management technologies
- implementation of technological advances on FDD of basic building equipment
- deployment of fuzzy techniques for disaggregation of cloud based energy loads into high level consumption categories
- adoption of new trends in HVAC systems’ optimisation
- application of expert reasoning to maintenance issues of basic building equipment
- know-how transfer between the participating companies
Partners of the Project
Exchange knowhow and utilize their advanced own products
Meazon
Meazon, through its involvement in this project, will have the opportunity to work together with highly experienced domestic and international staff in the provision of expert intelligence tools to be incorporated in its commercial energy management platform for proactive energy management in buildings to further optimize energy savings.
Role of Partner
Meazon will be based on its energy meters & sensors products that provide second-accurate, real-time breakdown of energy consumption flows. Its circuit-level meters are ready-set for the ever demanding world of cloud energy efficiency. They are perfectly adapted for limited cabinet space and can be fitted in almost all electrical panels at high density. Besides ZigBee wireless mesh connectivity permits effective positioning of its meters in a building. Furthermore, Meazon will also make use of its energy analytics & monitoringtools. Built on Windows Azure and Big Data technologies, Meazon Bizy Energy Analytics service allows customers to gain critical insights on raw energy consumption data. They enable energy auditing, visualisation, savings calculations, regression analysis and forecasting based on international energy efficiency standards (ASHRAE, IPMVP).
Meazon, through its involvement in this project, will have the opportunity to work together with highly experienced domestic and international staff in the provision of expert intelligence tools to be incorporated in its commercial energy management platform for proactive energy management in buildings to further optimize energy savings. In this perspective, by proliferating and customising its energy management tools in the future, it will broaden its commercial horizons and strengthen its position in the global market as provider of integrated solutions in energy saving for commercial and residential buildings.
Laboratory of Automation & Robotics (LAR),
Laboratory of Automation & Robotics (LAR), having in mind the importance of the Theory of Automatic Control Systems as well as technologies like Artificial Intelligence, Robotics, Fuzzy Logic, Fuzzy Cognitive Maps, Intelligent Hardware Devices, etc. in contemporary culture, intends to capitalize and further improve its experience gained in recent years in developing fuzzy logic algorithms and customising energy simulation tools in building energy management for optimal energy savings.
Role of Partner
Laboratory of Automation & Robotics (LAR) (Department of Electrical and Computer Engineering, University of Patras), having in mind the importance of the Theory of Automatic Control Systems as well as technologies like Artificial Intelligence, Robotics, Fuzzy Logic, Fuzzy Cognitive Maps, Intelligent Hardware Devices, etc. in contemporary culture, have developed activities in the following research areas:
- Smart Energy Management
- Control of Industrial Processes
- Monitoring Tools (robot)
- Intelligent Control
- Knowledge Management
- Modelling and Control of Discrete Event Systems
- Modelling and Control of Hybrid Dynamical Systems
- Hierarchical and Decentralized Control
- Structured Modelling and Control
- Design and Analysis of Nonlinear Systems
- Mechatronic Systems
- Embedded Controllers
- Nano controllers and Intelligent Sensors
LAR’s members (and external experts) are experienced with deep and substantial knowledge of the thematic areas. The scientific supervisor Professor Peter Groumpos is one of the few scientists in the world with high recognition for his contribution to the development of fuzzy logic and fuzzy cognitive maps and their use in a wide range of applications. He is author of book chapters and has published over 120 works (only for fuzzy logic and fuzzy cognitive maps) in international journals as well as in international conferences. He has been recently invited as the main speaker at global conferences and energy forums. Moreover, Professor P. Groumpos and LAR had undertaken a series of projects funded by Greece and/or the European Union with research activities in the field of energy management, intelligent control, intelligent decision making and management systems. LAR was involved in the last years in a Greece – Italy project, which main objective was to develop educational programs for the use of renewable energies systems. Moreover, two years ago LAR was project leader in a LEADERA (FP7) project, which main objective was to study the energy efficiency of commercial buildings using renewable energies systems. Through this proposal LAR intends to capitalize and further improve its experience gained in recent years in developing fuzzy logic algorithms and customising energy simulation tools in building energy management for optimal energy savings.
GPM
GPM, founded in 2008, has a clear mission of researching and developing a unique strategy in reducing peak demand and saving money on electrical bills. The company is highly specialised in HVAC efficiency control, presenting the only integrated solution on the market today that uses a revolutionary technology to store, analyse and maximize the efficiency of energy consumption using cutting edge technology, algorithms and IoT.
Role of Partner
GPM, founded in 2008, has a clear mission of researching and developing a unique strategy in reducing peak demand and saving money on electrical bills. Due to the high energy consumption in peak hours, most systems for light industrial and commercial industrial market, consume more energy on peak hours, the price for electricity is high, the waste of resources is tremendously high and are not able to manage energy in an affordable manner.
The company is highly specialised in HVAC efficiency control presenting the only integrated solution on the market today that uses a revolutionary technology to store, analyse and maximize the efficiency of energy consumption using cutting edge technology, algorithms and IoT. GreenOS™ is a comprehensive innovative solution that enables businesses to slash their electric bills by 10-40% by storing thermal energy in the buildings’ infra-structure, instead of in huge and costly ice tanks. Using a series of simple sensors and controllers, proprietary learning algorithms and a user friendly interface, GreenOS™ follows the thermal behaviour of the users, calculates the thermal capacity of the building, analyses the thermal behaviour and capacity, builds optimized operating profiles for efficient operation, stores thermal energy in the buildings’ infra-structure, optimizes operations and, in effect, cuts the electricity bills.
GreenOS™ applications include, among others, office buildings, logistic centres and warehouses, refrigeration rooms, etc. GPM, participating in this project, will have the opportunity to work together with highly experienced international staff in the provision of expert intelligence tools to be incorporated in its commercial energy management platform for proactive energy management in buildings to further optimize energy savings. From this viewpoint, by strengthening its energy management tools for optimal HVAC system operation in the future, it will broaden its commercial horizons and empower its position in the global market as provider of integrated solutions in energy saving for commercial and residential buildings.
Research Team
Stelios Koutroubinas
John Gionas
Titos Betsos
Aimilia Papagiannakis
Paraskevas Deligiannis
Dimitrios Balios
Vasilios Adamopoulos
Spyros Kleftoyiannis
Evangelos Kalomiris