Discipline: Technology and Engineering
Subcategory: Computer Engineering
Sarah Mosqueda - California State University, Bakersfield
Energy management systems (EMS) are essential for micro-grids to properly operate independently using renewable resources and storage units. EMS rely on a central control unit, which manages all the units in the system. The objective of this control unit is to match energy consumption and generation. It sends commands to each individual unit on how to adjust its energy exchange to achieve the system level goal. However, relying on such control unit introduces lack of robustness to the EMS. Failure in the control unit can cause improper operation of the EMS or in worse cases failure of the whole EMS . Besides, access to the central control unit for all the units limits the application of micro-grids, for instance when the units are geographically scattered. This project proposes an EMS that does not rely on a central control unit to manage the energy system and instead relies on distributed control. Such a system allows each individual unit to acquire certain information through communication with its neighboring units. In order to create an EMS without a central unit, the system must be connected in a way so that each unit, in this case referred to as a node, can access necessary information to perform control tasks while receiving information from a limited number of neighboring nodes. To achieve such system, the theory of consensus is used. Through consensus, information is broadcast to all the nodes without the need for a central broadcasting/control unit. A layer of consensus is used to broadcast each piece of information to all the nodes. The Laplacian dynamics is used in all the layers to converge the nodes to consensus . Through consensus, each agent can estimate the following three characteristics of the system: total number of agents, net energy exchange, and total number of edges. After reaching consensus, each node will know how the total energy consumption in the system compares with the available resources using the net energy exchange value. The node then uses control logic to adjust its energy exchange to help with balancing the overall energy exchange. During preliminary implementations, systems of various sizes and interconnections are simulated while the proposed consensus scheme is implemented. The consensus algorithm successfully estimates the number of nodes, net energy exchange, and the number of edges in the EMS under normal operation and also under several contingencies. In short, this study proposes the use of graph theory and consensus along with control theory to achieve an EMS structure that does not rely on a central control unit.
References:  J. Lagorse, M. G. Simoes and A. Miraoui, ‘A Multiagent Fuzzy-Logic-Based Energy Management of Hybrid Systems,’ IEEE Transactions on Industry Applications, vol. 45, no. 6, pp. 2123-2129, 2009.
 M. Mesbahi and M. Egerstedt, Graph Theoretic Methods in Multiagent Networks, Princeton: Princeton University Press, 2010.
Funder Acknowledgement(s): This material is based upon work supported by, or in part by, the U. S. Army Research Laboratory and the U. S. Army Research Office under contract/grant number W911NF1510498.
Faculty Advisor: Saeed Jafarzadeh, email@example.com
Role: My contributions to this project include completing elements of its entirety. I performed research on the subject of energy management systems and micro-grid applications. I learned how to use the software program to create and run my simulation. I designed each element of the simulation, including defining functions as well as connections between nodes. I also found and analyzed the results of the simulation.