Abstract
Distribution networks with high electric vehicle (EV) penetration levels can experience transformer overloading and voltage instability issues. A charge scheduling approach is proposed to mitigate against these issues that suits smart home settings in residential areas. It comprises measurement systems located at distribution transformers that communicate directly with fuzzy logic controller (FLC) systems embedded within EV supply equipment (EVSE). This realizes a reduction in data processing requirements compared to more centralized control approaches, which is advantageous for distribution networks with large numbers of transformers and EV scheduling requests. A case study employing the proposed approach is presented. Realistic driver behavior patterns, EV types, and multivariate probabilistic modeling were used to estimate EV charging demands, daily travel mileage, and plug-in times. A Monte Carlo simulation approach was developed to obtain EV charging loads. The effectiveness of mitigation in terms of reducing distribution transformer peak load levels and losses, as well as improving voltage stability is demonstrated for a distribution network in Jakarta, Indonesia.
Highlights
Societal improvements will increasingly become apparent as electric vehicle (EV) uptake levels rise.These will range from reductions in transport-related carbon emissions, to the use of EV battery systems for the provision of grid services
fuzzy logic controller (FLC) utilizes multivalued logic for which variables can belong by several membership functions at the same time
The FLC input for the transformer load is categorized into three membership functions (MFs), which are low (L), medium (M), and high (H). Another input is the EV state of charge (SOC), which is divided into MFs, which are very low (VL), low (L), medium (M), high (H), and very high (VH)
Summary
Societal improvements will increasingly become apparent as electric vehicle (EV) uptake levels rise These will range from reductions in transport-related carbon emissions, to the use of EV battery systems for the provision of grid services. One example particular to distribution transformers and that employs a fuzzy logic controller (FLC) is given in [8] This approach comprises four main inputs, including the EV battery state of charge (SOC), required SOC for the trip, estimated time of EV departure, and customer comfort level. An approach to realize smart charging control of the EV charging loads to prevent distribution transformer overloading is proposed This is achieved using an FLC that accepts the local distribution transformer loading level as a primary input.
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