Abstract
Due to the increasing utilization of electric vehicles (EVs), future power grids may face challenges of system peak load that are usually solved by means of grid reinforcements. By providing flexibility, acquired from flexible consumers, such as EVs, the need for grid reinforcements can be avoided or postponed. Therefore, in order to solve the peak load problem, this paper focuses on the provision of flexibility services through the local market. It presents a framework for the participation of aggregated electric vehicles in the local market, considering the operating constraints of the grid. In the proposed framework, aggregators interact in a transactive, market-based manner, with a transactive energy (TE) operator and distribution system operator (DSO) to resolve operational problems. For the market-based operation, a bidding model is proposed and formulated as an optimization problem that minimizes the total cost of DSO for acquiring flexibility services from EVs. The proposed model uses EVs as flexible loads to illustrate the method, and it is tested with case-studies conducted on two IEEE test systems.
Highlights
With the increasing integration of distributed energy resources (DER), like electric vehicles, the ever-evolving power system needs enhanced and flexible operation [1], especially at the distribution system level, since the increasing penetration of DERs is raising challenges from an operational point of view
WORK A market-based control framework is presented to facilitate the interaction of the AGR, the distribution system operator (DSO), and the transactive energy (TE) operator
An optimization problem is formulated that models the total cost incurred by DSO while respecting the network constraints
Summary
With the increasing integration of distributed energy resources (DER), like electric vehicles, the ever-evolving power system needs enhanced and flexible operation [1], especially at the distribution system level, since the increasing penetration of DERs is raising challenges from an operational point of view. Their aim is to minimize the operating cost of consumers by generating the aggregated optimal energy power schedule for the complete scheduling period, and to participate in the local market During these operations, the DSO’s network security constraints should not be violated that is ensured by enabling control techniques such as the transactive-energy approach. After receiving the energy profile from an aggregator, the DSO performs risk analysis and checks the possibility of network violation due to the charging schedule provided by aggregators during the following day of operation If such risk is predicted (i.e. operational limits of the network are violated), the DSO sends the request of flexibility needs (i.e. flexibility call is activated) by announcing the power quantity to be reduced (i.e. refrain electric vehicles from charging at a certain time for the certain duration). The DSO’s operational objective is presented where a bidding model is formulated as an optimization problem to minimize the cost of DSO for acquiring flexibility service from flexible consumers, to reduce the system peak load
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