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Development of a Triple Level Distributed Control for Demand Response Management, Intelligent Scheduling of Loads and Optimized Choices in Electricity Bidding for a Smart Microgrid

Project Incharge : Dr. Manjula G. Nair

Development of a Triple Level Distributed Control for Demand Response Management, Intelligent Scheduling of Loads and Optimized Choices in Electricity Bidding for a Smart Microgrid

The electric power system is undergoing wide range of transformations to ensure reliable and clean power supply to the customers by incorporating new information and communication technologies (ICT). Smart grid is the modernized version of conventional grid which combines electrical network and digital communication technologies. Smart grid is a self-healing network which monitors, controls, and analyses the grid conditions. It is an essential technology allows integration of renewable sources into grid and ensure consumer participation. Smart micro grids are small scale version of smart grid which can generate, distribute, and regulate electricity flow but do so locally. To reduce the complexity in controlling the grid through a centralized approach we are classifying the control levels in a smart grid into three; primary, secondary, and tertiary levels. In this work a method is suggested to design an integrated model for a smart micro grid by incorporating primary, secondary, and tertiary level controls. The proposed distributed control network will be capable of performing intelligent demand response by the secondary and tertiary controllers, the intelligent scheduling of loads by the primary controller and the support and the control is given to the various prosumers to participate in electricity markets.

To reduce the complexities, in this work the control levels in a smart microgrid are classified into three tiers: primary, secondary, and tertiary levels. Here the term smart is used for the units which can take decisions and hence intelligent.

Primary control pertains to control of a smart meter in the consumer premises. Secondary control is related to a local microgrid controller (LMC), which is an intermediate controller between primary and tertiary controllers. Tertiary controller interacts with the main microgrid controller (MMC), installed in the generating stations or power plants. This research has a collaboration with University of Trento, Italy under the Erasmus Mundus scheme.

Research Progress

The simulations that have been performed to analyze the theoretical facts are provided along with the results obtained. A Micro grid was modelled with 25kV source and 110kW purely resistive load and simulated. The system mainly focuses on the interaction between the primary and the secondary controllers. This is demonstrated using Simulink function in MATLAB. Few specific functions of primary and secondary level controllers are demonstrated using MATLAB Simulink.

Title: A novel strategy of generating synthetic load profiles using Machine learning from the available smart meter data of Irish Consumers

Prof. David Macii,

Ph.D., Associate Professor, University of Trento Dept. of Industrial Engineering

Via Sommarive 9, 38123, Trento, Italy

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