This paper investigates interaction among residential electricity users and utility company in a distribution network with the capability of two-way communication provided by smart grid. The energy consumption scheduling of electricity users is formulated as a game-theoretic problem within a group where all players are not totally selfish. Considering altruistic behavior of human decision-making, altruistic player action to other players actions can be influenced by recognizing the well being of others. The proposed model captures the empathy of electricity users in energy consumption scheduling and how this behavior affect peak demand and electricity prices. Numerical results demonstrate that both residential users and utility company can benefit through the channel of empathy.
By the introduction of smart grid, the access to potential capabilities of DR programs becomes much more viable because of two-way exchange of information between users and utility company. In such environment, the utility and users can interact by exchange of supply and demand information in order to make mutually beneficial decisions @cite_24 . Different approaches have been employed to study demand response in smart gird paradigm and game theory is one of the most promising approaches due to the dynamic nature of interactive decision-making between users and utility. In the following, we explore several studies related to game-theoretic DR within three different groups. However, first we introduce some terms which are used frequently hereafter: denote decision makers of the game such as electricity users and utility. describe expected benefits that each player obtains which could be maximizing revenue for utility or minimizing billing cost for user. are decisions made by each player like scheduling energy consumption for user and setting electricity prices for utility company.
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The smart grid is widely considered to be the informationization of the power grid. As an essential characteristic of the smart grid, demand response can reschedule the users' energy consumption to reduce the operating expense from expensive generators, and further to defer the capacity addition in the long run. This survey comprehensively explores four major aspects: 1) programs; 2) issues; 3) approaches; and 4) future extensions of demand response. Specifically, we first introduce the means tariffs that the power utility takes to incentivize users to reschedule their energy usage patterns. Then we survey the existing mathematical models and problems in the previous and current literatures, followed by the state-of-the-art approaches and solutions to address these issues. Finally, based on the above overview, we also outline the potential challenges and future research directions in the context of demand response.