Necessity for energy of the modern people and hence the importance of the power system increases day-by-day, despite the limited energy resources. This project aims to develop a scalable autonomous resource (electric energy and water) management system for distribution systems, and two intelligent field units for electric and water systems. The proposed system provides situational awareness and decision support, and performs autonomous control. The intelligent field unit for the power system provides field data/information and performs autonomous control, and the intelligent field unit for water system collects field data and analysis results. The proposed management system will utilize not only the electrical data but also transportation system and water system data that are highly related to the energy consumption, and also provide decision support and diagnostic results for water system.

During the normal power system operation, the proposed system will autonomously utilize the electrical energy in an optimum manner by control of the battery storage units (BSS), controllable loads, electric vehicle charge (EV), vehicle-to-grid concept (V2G), controllable solar power inverters (PV) and distribution system topology. Moreover, situational awareness and decision support functions will assist the system operator for critical actions and/or anomalies in the system. Those functions will help diagnosing the current problems of the power system (malfunction of components, non-technical losses, etc.), and also provide prognostic support. During an emergency or interruption of the major power source (i.e. transmission grid) the proposed controller will maximize the continuity of the service for the critical loads with minimum interruption of the non-critical loads.

The proposed system is designed as a multi-layer autonomous energy monitoring and control system. First layer is a supervisory model predictive controller, which will work once in every hour, to provide predications/forecasts to the lower-level controllers, and perform some major controls for the upcoming one hour based on the model predictions. The second layer will be a multi-agent sub-system controller, which will communicate with neighboring sub-systems, the supervisory controller and the field components. This controller will work more frequently (e.g. in the order of a few minutes). The third layer control will be realized by the intelligent field components (based on edge machine learning) in real time, design of which is also included in the scope of the project.

The proposed multi-layer optimization structure will enable optimal operation during the normal operating state of the system. During an emergency, and loss of the supervisory controller, the multi-agent sub-system controllers and intelligent field units will be capable of running the system to satisfy the objective, which will yield a resilient system operation, and minimize the expected interruptions.

The proposed field units will make use of the collected data (from PVs, EVs, BSS, water system), using edge machine learning, and without any frequent communication burden it will perform the required predictions. Those predictions and collected data will also be transferred to higher level controllers. Based on the obtained predictions and actual situation of the connected components, real-time decision will be given by the field unit. This will significantly reduce the communication and computation burden.

In the project, as communication has a critical role for continuous and reliable operation of the proposed system, the cyber security layer will also be investigated. Secure communication mechanisms and cyber-attack and anomaly detection and identification methods for the inter and intra system communication tools will be developed.

The academic part of the international project team consists of researchers in the fields of power systems, environmental engineering, systems engineering, cyber security and power electronics. One of the industrial partners of Turkey side is an expert on IoT technology, and the other is a distribution utility company. The Qatar side research end user will provide expertise on the practical aspects of the considered systems.