An Optimal Strategy to Determine the Electricity Tariff During Different Operational Conditions

Abstract

Apart from the objective of optimizing electricity bills by enhancing consumption patterns, the implementation of dynamic pricing for electric energy can facilitate the redistribution of demand from peak hours to non-peak hours. This strategic approach aims to effectively manage congestion issues and enhance the overall stability of the system. Therefore, it becomes crucial to determine tariff rate modifications by taking into account the demand side's elasticity and devising a strategy that maximizes the profitability for all stakeholders. In this study, two distinct time-of-use (ToU) tariffs, specifically a two-level and three-level structure, are utilized alongside the modeling of consumers' elastic behavior. The primary goal is to design an optimal tariff rate scheme that simultaneously maximizes the company's profits and minimizes the consumers' electric energy bills. To accomplish this, a genetic algorithm is employed to derive the most favorable tariff structure. The evaluation of the proposed strategy is con-ducted on the 24-bus IEEE system. To capture the diversity in consumers' consumption patterns, all loads are categorized into five distinct groups, with three categories representing residential loads and two categories representing industrial loads. The results obtained from the analysis demonstrate that by implementing an appropriate three-level ToU tariff and considering operational constraints, a substantial shift of more than 4.7% for residential loads and over 5% for industrial loads during peak hours can be achieved, redirecting them towards off-peak hours.