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With the prevalence of coupling engineering systems such as multi-agent systems, wireless networks and the smart grid, solving optimization problems across multiple decision-makers emerges to be of theoretical significance and practical relevance. Resource allocation for systems with limited resources, energy consumption control for electricity users, and economic dispatch among a network of generators in smart grids are typical examples of multi-decision-maker optimization problems. These optimization problems are explored from the perspectives of non-cooperative games and networked optimization in this dissertation. The background, introduction and motivation for this topic are included in the first two chapters. The specific problems considered in the dissertation are summarized as follows. Energy consumption control among a network of electricity users in smart grids is considered. An aggregate game approach is proposed to solve it by noticing that the aggregate energy consumption is unknown to the electricity users during the energy consumption scheduling process. Average consensus based updating strategies are developed to search for the Nash equilibrium of the energy consumption game. A general energy consumption game with possibly multiple Nash equilibria is firstly explored. In this case, the Nash equilibrium is exponentially stable under the given strategy. In particular, energy consumption game (for heating ventilation and air conditioning systems) that admits a unique Nash equilibrium is then investigated. Based on the uniqueness of the Nash equilibrium, a non-local convergence result is Nanyang Technological University Singapore

Distributed optimal coordination across multiple decision-makers and its application to demand response in smart grids