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Minimization of real power losses and voltage deviations in distribution systems with optimal scheduling of Electric Vehicles

DR. P.V.V RAJA GOPAL, ATTALURI DINESH, POLAVARAPU LAKSHMI SRIKANTH

Abstract


All over the world, the problem of environmental pollution and energy crisis is increasing rapidly. Transportation and fuel based electric utilities are the major sources of Green House Gas (GHG) emissions. To reduce GHG emissions and energy crisis, employing Electric Vehicles (EVs) with integration of renewable sources are the promising solutions. The current growth of EVs is slow due to the issues such as slow charging time, range anxiety, lack of charging infrastructure, higher cost and capacity fading of the EV battery. Uncoordinated EV charging can result in increased losses, voltage limit violations, overloading of transformers and distribution lines. Therefore, scheduling strategies are imperative in order to coordinate the charging demand of EVs for efficient use of grid capacity and available power generation.

The integration of EVs is implemented on the distribution end of power system. Therefore, the main objective of this thesis is to study in detail the impact of scheduling strategies including different vehicle to grid (V2G) services available from EVs. Furthermore, the coordination of scheduling strategies with existing operative tools in distribution system is also studied. It is necessary to use proper EV’s charging/discharging scheduling model that is able to simultaneously consider economic and environmental goals as well as technical constrains of distribution system for the widespread of Electric Vehicles. This project proposes the optimal scheduling of electrical vehicles integrated to distribution systems and the minimization of the losses. This minimizes the total operational costs and emissions.

Actual patterns of drivers and vehicle to Grid (V2G) capacity is considered to generate Pareto-optimal solutions. A 24-hour or one-day timeframe is used to examine the efficacy of the suggested resource scheduling technique on distribution systems with 33 and 69 buses. A strategy of arranging EV charging based on grid limits has been proposed. This technique creates an individual charging schedule for each vehicle, avoiding distribution network congestion while meeting the needs of individual vehicle owners. The results revealed that peak demand can be lowered by implementing the proposed control approach for electric vehicles. The impact of different voltage-dependent load models and stochastic EV charging demand is investigated on modified IEEE 123-bus distribution system. Results reveal that the exponential load model is the better representation of EV fast charging load and EV charging demand depends on location and time of charging. Also, different load models affect the energy demand, energy losses and voltage profile of the system. Therefore, load models play an important role in assessing the true energy demand and energy losses incurred due to fast charging of EVs.


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