Abstract
Nowadays, the increasing penetration of renewable energies often leads to system frequency variation due to the intermittent outputs, which limits the utilization of renewable electricity and brings higher requirements to frequency regulation. Aggregated electric vehicles (EVs) are suggested to be used as good regulation resources because of the vehicle-to-grid (V2G) capability and quick response characteristic. However, the participation of EVs inevitably leads to cyber delays due to their underlying communication infrastructure and scheduling, which may cause instability. To guarantee the system stability, this paper investigates the stability of a grid frequency regulation system with electric vehicle (EV) aggregators embedded by cyber delays in the cyber system. A comprehensive stability assessment method is proposed in this paper based on the discrete spectrum iteration. A stability assessment method flow is designed with only five stages: 1) system initialization and modeling; 2) spectrum transformation; 3) Chebyshev discretization; 4) Krylov subspace projection dimension reduction; 5) Newton correction. Comprehensive case studies are performed on the cyber regulation systems with single, double, and three EV aggregators to extract the stability region and to validate the proposed approach. It is revealed that the controller gain, the ratio between the participation ratios of each aggregator, and that between EV and grid are important factors for determining the stability of the regulation system at a given controller gain. Besides, the criterion of the stability region changing with the three factors is proposed. It is found that the mass utilization of electric vehicles in the frequency control disrupts system stability due to the aggregation delay and thus the stability region can be divided into several intervals and presents periodicity. It is expected that the proposed criteria can help to guide the determination of delay requirements for EV aggregators participating in frequency regulation service.
Highlights
Nowadays, electric vehicles (EVs) have been paid attention in immense amounts of researches due to growing environmental pollutions, gradual depletion of fossil resources, and intermittent renewable energy sources such as wind power and PV solar
The method consists of four core techniques: Spectrum transformation, Chebyshev discretization, Krylov subspace projection dimension reduction, and Newton correction
(1) A time-delay stability analysis model for a grid frequency regulation system with EV aggregators embedded by cyber delays in the cyber system is derived, which facilitates model-based investigations for the global stability of the cyber system; (2) This paper presents a comprehensive stability region extraction assessment method based on the discrete spectrum iteration, a computation framework integrating spectrum transformation, Chebyshev discretization, Krylov subspace projection dimension reduction, Newton correction has been established for analyzing cyber system
Summary
Electric vehicles (EVs) have been paid attention in immense amounts of researches due to growing environmental pollutions, gradual depletion of fossil resources, and intermittent renewable energy sources such as wind power and PV solar. Newton’s method is applied to correct the critical eigenvalues of the cyber system calculated from the approximant matrix Another issue discussed in this paper is the stability of a grid frequency regulation system with electric vehicle (EV) aggregators embedded by cyber delays in the cyber system. When electric vehicles are connected to a power grid, the bidirectional energy exchange can be achieved by charging/discharging devices It only makes sense for a large number of EVs to participate in frequency regulation, so the way of ‘‘decentralized access, hierarchical control’’ is applied to enable coordinated charging and discharging management, and the EV aggregator is introduced as the essential enabler in making the V2G concept realizable in practical terms, With the EV aggregator, the distributed EV1, . The communication delay from an EV aggregator to the EVs and the scheduling delay in the EV aggregator are modeled by an exponential transfer function of e−sτ , where τ is the cyber delay taken for receiving control signals from the EV aggregator over industrial Ethernet as well as the scheduling delay in the EV aggregator
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