Abstract
In this paper, the charging loads of electric vehicles were controlled to avoid their impact on distribution networks. A centralized control algorithm was developed using unbalanced optimal power flow calculations with a time resolution of one minute. The charging loads were optimally reallocated using a central controller based on non-linear programming. Electric vehicles were recharged using the proposed control algorithm considering the network constraints of voltage magnitudes, voltage unbalances, and limitations of the network components (transformers and cables). Simulation results showed that network components at the medium voltage level can tolerate high uptakes of uncontrolled recharged electric vehicles. However, at the low voltage level, network components exceeded their limits with these high uptakes of uncontrolled charging loads. Using the proposed centralized control algorithm, these high uptakes of electric vehicles were accommodated in the network under study without the need of upgrading the network components.
Highlights
Electric vehicles (EVs) have an important role to play in supporting the UK target of an 80%reduction in CO2 emissions by 2050s relative to CO2 emissions in 1990s [1,2]
These meters are used to upload readings of measured phase currents using two‐way communications. When these readings are received by the centralized control algorithm, unbalanced power flow calculations ground-mounted distribution transformer) serves 384 customers distributed across 4 low voltage (LV) feeders
(with smart as modeled in Section 4.3. allocation): 384 EVs at T8 were charged with the centralized control algorithm
Summary
Electric vehicles (EVs) have an important role to play in supporting the UK target of an 80%. The performance of the proposed control algorithm is tested with the real daily profiles of EV charging loads acquired from the smart meters during trials of the Customer-Led Network Revolution (CLNR) project These profiles were used to synthesize stochastic charging durations for each EV with one-minute time resolution considering unbalanced EV charging loads across the three phases. It develops the centralized control algorithm to reallocate EV charging loads with one-minute time resolution considering the predefined constraints. This algorithm can be integrated into existing power system control paradigms.
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