An Improved Methodology for the Hierarchical Coordination of PEV Charging

Abstract

This paper proposes an improved methodology for the hierarchical coordination of daily Plugin Electric Vehicle (PEV) charging. The aim is to limit the power supplied by the primary distribution transformer (PDT) while minimizing the energy costs of the aggregators. This methodology consists of an iterative optimization of the total aggregated power at the PDT level, considering the local power constraints of the aggregators and the PEVs with a reduced number of decision variables and constraints which only depend on the number of time intervals. Moreover, it defines the energy boundaries of the optimization problem in each iteration through a proposed method for simulating early charging and delayed charging, considering the power constraints of the aggregators. Otherwise, it evenly distributes the total power among the aggregators, and the local power of each aggregator among the PEVs, maximizing the feasible region of the optimization problem. The proposed methodology is applied to two case studies. The uncertainties related to the charging scenarios are considered by means of Monte-Carlo simulations. The results obtained show that the total power profile is effectively limited, while the profits of the aggregators are not significantly affected by the coordinated approach that is expected to be performed by the Distribution System Operator (DSO). Additionally, to demonstrate the reduction of the impact of PEV charging on the distribution system, the voltage profile, the transformer loss of life and the power and energy losses are reported.

A Framework for Determining a Prediction-Of-Use Tariff Aimed at Coordinating Aggregators of Plug-In Electric Vehicles

“…Taking into account this disadvantage, V2G mode is not considered, as in references [6,[10][11][12][13] which only address PEV recharging. In [6], an approach to coordinate the charging of PEV is proposed. The objective is to minimize the charging cost under a TOU tariff, considering a power constraint imposed by the distribution transformers.…”

“…The available power of the aggregator is determined to be the difference between the nominal SDT power and its respective base load. The maximum power for the PEV charging of each aggregator is calculated through (6).…”

“…This work uses the same case study described in [6], where the Institute of Electrical and Electronics Engineers (IEEE) 33-bus test distribution grid [28] is considered for that case study. A total of 32 SDTs have been added, each with 12.66/0.38 kV.…”

“…This prediction aims at incentivizing the aggregator to follow the probable optimal load curves obtained in the first stage and to penalize any deviation from them.The framework proposed in this article aims to enhance the operation of the grid by flattening its supply power profile. The results of the proposed methodology, based on POU tariff, are compared with those obtained through the approach reported in [6], which is based on a time-of-use tariff (TOU), that uses the same case study. This case considers a power distribution system with 32 aggregators whose coordination is managed by the DSO.Finally, the voltage profile, the aging of the PDT and the power/energy losses during a day of operation under both TOU and POU are compared, in order to analyze the impact of the strategy proposed in this work on the studied distribution system.…”

“…The framework proposed in this article aims to enhance the operation of the grid by flattening its supply power profile. The results of the proposed methodology, based on POU tariff, are compared with those obtained through the approach reported in [6], which is based on a time-of-use tariff (TOU), that uses the same case study. This case considers a power distribution system with 32 aggregators whose coordination is managed by the DSO.…”