Dynamic Protocol for the Demand Management of Heterogeneous Resources with Convex Cost Functions (Informatica, 2017)
Increasing demand of resources has driven research towards design of mechanisms that address resource-demand management, which usually focus on balancing peak demand and optimal device scheduling. While balancing homogeneous sources is well known, the goal of this paper is to balance the demand of heterogeneous resources with a convex cost function as well as to encourage consumers to reduce their demand. We propose a novel dynamic protocol achieving both goals using a serial cost-sharing pricing mechanism. The pricing-mechanism design is strategy proof and budget balanced, whereas the protocol does not require the consumers to reveal their utility functions, and supports hierarchical organization of consumers. We initially applied the proposed approach to a multi-agent system, where the consumers are smart house devices controlled by a corresponding agent, which in turns negotiates the electricity price with a smart city. Experimental results show that the proposed protocol successfully reduces the total consumption and lowers the peaks while all the consumers in equilibrium are given a fair price. We further provide experimental results indicating advantages of serial cost-sharing pricing and tariff pricing mechanisms over the average cost-pricing mechanism that is commonly used in the resource-demand management.