This paper presents an electric vehicle charging demand management method by modeling the demand dispatch calculation. Despite the demand shift owing to the price signal, the signal is occasionally inaccurate because of the load variability. The electricity rate has features that can shift the electric vehicle charging priorities; the application of the load fluctuation criterion is sufficient for the management plan. We expect that there is a point, wherein, both the electric vehicle users (saving costs) and the system operators (relieving loads) are satisfied with the mutually beneficial arrangements. Our method determines the balanced state in which the loads and costs are considered simultaneously with the proposing criteria. The method allows the discordance between the electrical prices and the system load fluctuations to be managed, While the time-of-use pricing and load deviation indices are accounted for. We focus on the gap corresponding to the load variation and the charging price in a daily scheme. In contrast to the typical valley filling strategies, the aim of this study is to determine and solve the mismatches in the different goals of the costs and loads, if the state is not mutually beneficial. Therefore, to ensure a system operator perspective selectively, we introduce the load weight and ranking method concepts for dispersing the charging loads, lowering the system marginal prices, and investment avoidance because electricity rates cannot describe the load curves accurately. The charging demand calculation is investigated based on the determination of the charging patterns and daily demands using the priority comparison method. The balancing strategy first fills the mutual benefit points with respect to the changing priorities and then, competes to find the balanced points. The significance of the method is that it is based on the unique relationship between two comprehensive competitive strategies. Thus, we determine that valley filling, flat load management, and regulated deviation are insufficient to describe the user and operator behaviors simultaneously. (C) 2016 Published by Elsevier Ltd.