Game theoretic optimization of DC micro-grids without a communication infrastructure

This paper proposes an algorithm to optimize the steady-state operating point in Small Scale Power Systems (SSPS) without the need for communication channels. The approach follows a game theoretic framework with a modification of objectives inside the SSPS. The players are able to minimize a modified objective which gives a improved cost for their initial local objectives. This modified objective is a function of initial local objectives and augmented non-cooperative game. The new game has multiple Nash equilibriums (NE) and therefore players get the opportunity to shift their operating point to a better one while keeping the game condition non-cooperative and without the need for a communication infrastructure. Further, the modified objective is a simple function of players\u27 initial local objectives. Therefore, this method can be easily implemented in the hardware system even with player higher nonliner objectives

Optimal transient control of microgrids using a game theoretic approach

Small scale power systems (SSPS) are collections of interconnected electrical energy sources and loads. However, the analysis and control of SSPS are different from the more traditional large scale power system techniques because in SSPS the generation has minimal inertia with little if any spinning reserve. A differential game-theoretic framework is helpful in designing the control structures for SSPS for efficient and reliable operation with simultaneous player movement. Defining both loads and sources as players in a SSPS and forming a game between them is the key to modeling in this framework. This paper presents a modeling approach to find the optimum trajectory for the load players to reach a desirable operating point from an arbitrary initial condition given a transient system event. The players follow the optimum trajectory in the movement. In addition, the load modeling is proposed for the power electronic converter end load during transient. Further, this paper defines the suitable modifications needed to drive the optimum trajectory to an unknown static set point. This modification is important while system moves from nominal equilibrium to a new equilibrium due to sudden load or source changes. Example cases are presented with nine bus dc power system with load players

Game theoretic bus selection in DC power systems

Direct current power systems can be made more reliable by using multiple buses for redundancy. A multi-buss system provides multiple configuration options, giving the loads multiple choices. This paper proposes the game theory based analysis to choose and control the optimum bus selection for a given load. The modeling is based on the local information of the player and does not need a centralized controller. The first section of the paper shows how the single input player optimizes its local objectives and obtains a Nash equilibrium. Then next section shows how the global objectives can be integrated with minimal communication. It also illustrates how to integrate different objective priorities in to the analysis. Lastly, the analysis is extended to dual power input player situations. This is practically important when the Nash equilibrium does not exist under the payoff matrix modeling pure strategies

A game theoretic bus selection method for loads in multibus DC power systems

DC power systems with multiple buses for redundancy are more reliable and provide reconfiguration options. A game-theoretic-based modeling approach for bus selection is proposed in this paper, which is based on local information of the player and does not require a centralized controller. The initial section provides the modeling and optimization of a single-input player. This modeling mainly follows on the players\u27 local objectives and discrete choices of bus connections. Therefore, in this case, the controller obtains Nash equilibrium (NE) for the pure strategy game. Then, the approach is extended for the integration of global objectives with minimal communication. In addition, different objective priorities are integrated into the optimization routine. Next, the analysis is extended to multi-input player situations which are related to the class of mixed and continuous strategy games. This modeling is important, since the payoff matrix approach does not find an NE in all cases. Finally, the bus selection modeling is carried out by taking the system dynamics into account. This is important for the cases where the system has sudden load or source fluctuations. Experimental results are obtained, which validate the theory. © 1982-2012 IEEE

Optimal team communication structures in microgrids

This paper presents a team player based modeling approach to communication structures in microgrids. The modeling follows a game theoretic framework by forming teams inside the Small Scale Power Systems (SSPS). The team players are able to minimize the common objective when there is communication, and shift to the individual objectives when communication fails. The paper also presents analysis to determine the minimal performance standards for the given level of communicated information. The last part of the paper shows how the Stackelberg concept can be integrated to the micro-grid for a leader-follower modeling approach. Example systems are simulated to explain each case

Game-theoretic cold-start transient optimization in DC microgrids

© 2014 IEEE. An interconnected electrical network that has electrical sources and loads makes a small-scale power system (SSPS). These systems have low inertia, which makes the modeling and controlling of them dissimilar to that of traditional large-scale power systems. A differential game-theoretic framework allows for the design of the distributed control structures for SSPS with player dynamics under simultaneous player movement. Under this approach, both loads and sources are defined as players in the system to form a game of energy between them. Game-theory-based modeling is necessary in this case since it optimizes the multiobjective optimization problem based on local control without the need for a communication channel. In this paper, a differential game-theoretic approach is used for path optimization of load players during a cold start that minimizes losses and achieves a desired steady-state operating point. Example simulation cases are obtained for a dc power system that has nine buses and dynamic load players. This power system is used to show the applicability, effectiveness, and performances of the proposed concepts. However, this method can be easily applied to other types of larger dc or ac networks. Finally, experimental results are yielded to validate the theoretical results and show that the proposed controller has higher performance compared with the traditional proportional-integral controller during transients

Game-theoretic communication structures in microgrids

This paper presents a game-theoretic communication structure, which is a network constructed among distributed controllers in the microgrid. This helps to share local controller information, such as control input, individual objectives among controllers, and finds a better optimized cost for the individual objectives. The modeling follows a game-theoretic framework for the energy conversion and control elements inside small-scale power systems (SSPS) or microgrids. These elements form teams to optimize performance and operation based on available information and communication. The team players are able to minimize a common objective when there is communication, and shift to the individual local objectives when communication fails. This paper also presents analysis to determine the minimal performance standards for the given level of communicated information. Then it shows optimal information mixing for team player modeling. In addition, a Stackelberg model is proposed for the microgrid with a leader-follower modeling approach. The last part of this paper shows possible examples with network contingency study with team player participation. © 1986-2012 IEEE