The increased gap between the peak load and valley load of power grids prevailing due to uncoordinated charging load of large-scale electric vehicles can be alleviated by employing proper charging pricing mechanism for electric vehicles. This helps to achieve load valley filling for the power grid. The two scenarios such as non-cooperative scenario and cooperative scenario for flattening the power load profiles are considered in the study.
Each electric vehicle in the non-cooperative scenario, possess its own charging power without any cooperation with other electric vehicles whereas in the cooperative scenario, there is an aggregator controlling all the electric vehicles together. Zechun Hu and colleagues from Tsinghua University in China proposed coordinated charging strategies by deriving appropriate conditions of the valley-filling pricing mechanisms for both the non-cooperative and cooperative scenarios.
If electric vehicles are properly controlled, they can highly reduce network losses, balance renewable energy fluctuation and bring frequency regulation. Application of load valley filling in the electric vehicle ensures low cost in power load servings. This makes electric charging load an ideal source by providing flexibilities in selecting the period of charging vehicles.
In the non-cooperative scenario, EV owners optimize their charging schedules to minimize their individual charging costs. Game theory is applied to reach Nash equilibrium in order to gain extra profits. Thus cost is minimized by changing the charging schedule unilaterally. It is proved that the price function is a strictly increasing function of the total load implies the price function is valley-filling.
Fig. 1 Load profiles (left) and valley-filling price curve (right) in the non-cooperative scenario
In the cooperative scenario, the charging processes of all electric vehicles are coordinated through an aggregator to minimize the total charging cost. The function of aggregator involves checking for newly arrived electric vehicles to be charged and updating their information such as state of charge, arrival time and expected departure time. The sufficient and necessary condition of valley-filling price is derived and proved.
Fig.2. Load profiles (left) and three different price curves (right) in the cooperative scenario (2476 EVs).
With a proper guidance to price mechanism design, the cooperative and non-cooperative charging strategies are proposed to reduce communication burden and guarantees quick convergence. The valley-filling pricing mechanism was designed in such a way that it maximizes social benefit and minimizes load variance. It depends on the electric vehicle owners to charge their vehicles depending on the market electric price signal. A dynamic load pricing strategy is chosen to avoid heavy peak loads during high population of electric vehicles. The application of such optimization methods and strategies ensure effective load valley profile along with reduced cost.
Zechun Hu1, Kaiqiao Zhan2, Hongcai Zhang1, Yonghua Song1, Pricing mechanisms design for guiding electric vehicle charging to fill load valley, Applied Energy, Volume 178, 2016, Pages 155–163.Show Affiliations
- Department of Electrical Engineering, Tsinghua University, Beijing, People’s Republic of China.
- Electric Power Research Institute, China Southern Grid, Guangzhou, People’s Republic of China.
Go To Applied Energy