PERSICO project: energy efficiency

Intervention carried out by using funding POR - Objective "Increase in business innovation activity" Part ERDF European regional development fund 2014-2020. 

ACTION 1.1.4 “Support for collaborative R&D activities for the development of new sustainable technologies, products and services”.

Challenges on energy efficiency

The issue of energy efficiency of plants and more generally energy optimization intended as a reduction of waste and consumption is becoming increasingly important, both in terms of reducing emissions into the atmosphere and in terms of the consumption of resources and the reduction of management costs. Often, however, waste and consumption are exaggerated as most of the time there is no complete knowledge of the environment. Since all environments linked to human activities are now equipped with technological systems (lighting, air conditioning, etc.), adapt the operation of these systems based on dynamic rules that take into account all possible environmental variables (presence, times of activities, weather conditions , etc), possibly also in a forecasting manner, can significantly reduce the use of energy resources necessary for the operation of the plants themselves. 

How to manage the problem of energy efficiency in the residential and large-scale retail sector? 

The PERSICO project aims in particular to manage the problem of energy efficiency in the residential and large-scale retail sector (GDO). 

In fact, it aims to create a platform capable of performing the aforementioned functions and consisting of:

→ a cloud system for managing the infrastructural part;

→ a web platform for the management of the application part;

→ by a data collection and control unit for interfacing with the sensors installed in the system.

This integrated solution will allow both system control based on automatic decision rules, artificial intelligence rules, and direct control by the operators who manage or use the system itself.

The project idea therefore provides for improving energy efficiency in various areas (residential and commercial) through the use of ICT and electronic technologies thanks to distributed networks of sensors that collect data analyzed by artificial intelligence algorithms, which then allow to act on the system to improve its energy yield. 

The IoT project for energy efficiency

The project includes two phases: the 1st phase (from 05-08-2019 to 15-07-2020), completed, and the 2nd phase (from 16-07-2019 to 01-02-2021) still in progress realization. 

 The project includes the following condensed structure of Work Package (WP):

1. WP1 - DEFINITION OF REQUIREMENTS AND SPECIFICATIONS;
2. WP2 - REALIZATION OF PROTOTYPES (creation of multi-protocol platform, Cloud platform);
3. WP3 - PROTOTYPE TEST in the residential scenario, large retailers and in other application areas.

1. It is first of all necessary to know the status of the systems in order to check their consumption, the operating modes and a set of other parameters; it is also necessary to know the installation context in which they are located, the operating methods by the users and other environmental factors that can contribute to the good or bad functioning of the systems themselves. In fact, these aspects can have a not negligible influence on energy consumption since human actions on the regulation of the system, apparently not related to consumption, can in any case affect the non-negligible way on the dynamics of operation.
2. Starting from this deterministic knowledge base it is possible to model the systems and using artificial intelligence techniques it is possible to identify the intervention points in order to improve their energy yield in terms of consumption, use and maintenance. In many cases, however, especially in the case of older systems, it is not possible to find this information in a simple way: often the systems have only a local control unit that is not connected to the network sensors that allow to acquire the values ​​of the operating parameters. Furthermore, especially in large plants, part of the data is available but supplied by components that communicate with different communication protocols to which it is necessary to add what is acquired through the single data collection system that allows interfacing with the plant by managing the various communication protocols and enriching the plant data with information from other sources that also allow to increase knowledge of the environment.
3. Finally, it is important to test the prototype in a physical environment capable of reproducing the residential and large-scale retail scenario and also draw up a final report with the analysis of the test results for the evaluation of the impact of the new product on other scenarios as well as those already highlighted. 

Conclusions and challenges towards sustainability

The innovativeness of the PERSICO project concerning the classification techniques used for data analysis is provided by their application in the problem of optimizing energy efficiency. These techniques are not normally used in the world of control engineering, but several studies at the University of Verona have made it possible to obtain excellent results in this field as well.

1. In addition, the use of artificial intelligence techniques allows to highlight correlations of data from different sources and typically not conventionally used in the context of plant maintenance.
2. The use of integrated sensors with data export to the cloud also allows the correlation of information that is normally unrelated to each other or even not available in a simple and aggregated way for consultation and interpretation.
3. Integration with the company ERP provides an additional database to refine knowledge and the subsequent optimization of the operation of the systems.

For example, consider the ways in which customers flow into a large-scale retail outlet based on both historical and operational data available on the ERP (presence of promotions, seasonality of products and their storage, peak times) combined with monitoring and control in real time of the systems allows to adapt the functioning of the same in a dynamic way thus allowing a considerable saving of resources, both in terms of energy and wear.

The system that will be obtained at the end of PERSICO's activities can be applied (with appropriate adjustments) to other industrial sectors that present similar needs; in addition to energy efficiency, it is however conceivable that the precise knowledge of environmental parameters can contribute to a better quality of life inside both residential and industrial buildings.

It is also conceivable that the system, by varying the automatic decision rules and the part of sensors / actuators, can find application, for example in the agricultural field, allowing for example to optimize irrigation based on both meteorological and environmental parameters

in the industrial field, as well as for the energy efficiency part, also for what concerns the quality of the working environment. 

The project, launched in August 2019, involves three companies and the University of Verona: EDALAB Srl (leader), MANUTHERM Srl, TEKSERVICE Srl.

The project was awarded a total contribution of € 289,460.20 against an expense of € 299,460.20 for the duration of the entire project expected to be 18 months. 

Tags: Financing EU project R&S Regione Veneto