ISSN 2196-5625 CN 32-1884/TK
2022, 10(2):316-327.DOI: 10.35833/MPCE.2021.000685
Abstract:With the development of renewable energy and the changes in the characteristics of power grid, it is becoming increasingly difficult to balance power supply and demand in space and time. In addition, the requirement for improved dispatching capability of power grid is increasing. Therefore, the potential of flexible load dispatching should be realized, which can promote the large-scale consumption of renewable energy and the construction of new power grid. Based on the analysis of existing load dispatching studies and the differences in the characteristics of domestic and foreign load dispatchings, a technical architecture and several key technologies are proposed for load resources to participate in power grid dispatching under the new situation, i.e., the autonomous collaborative control system of load dispatching. This system implements the multi-layer coordinated control of main, distribution and micro grids (load aggregators). Adjustable load resources are aggregated through an aggregator operation platform and connected with a dispatcher load regulator platform to realize real-time data interaction with dispatching agencies as well as the monitoring, control, and marketing of aggregators. It supports the load resources to participate in network-wide dispatching optimization via continuous power adjustment. Several key technologies such as the control mode, load modeling, dispatching strategy, and safety protection are also elaborated. Through the closed-loop control of orderly charging piles and energy storage clusters in the North China Power Grid, the feasibility of the proposed architecture and key technologies is verified. This route has successively supported multiple adjustable load aggregators to participate in the ancillary services market of North China Power Grid for peak-shaving. Finally, the technical challenges of load resources participating in power grid dispatching under the dual carbon goals are discussed and prospected.
2020, 8(3):412-425.DOI: 10.35833/MPCE.2018.000802
Abstract:Plug-in electric vehicle (PEV) load modeling is very important in the operation and planning studies of modern power system nowadays. Several parameters and considerations should be taken into account in PEV load modeling, making it a complex problem that should be solved using appropriate techniques. Different techniques have been introduced for PEV load modeling and each of them has individual specifications and features. In this paper, the most popular techniques for PEV load modeling are reviewed and their capabilities are evaluated. Both deterministic and probabilistic methods are investigated and some practical and theoretical hints are presented. Moreover, the characteristics of all techniques are compared with each other and suitable methods for unique applications are proposed. Finally, some potential research areas are presented for future works.
2020, 8(5):1015-1023.DOI: 10.35833/MPCE.2019.000296
Abstract:Composite load model of Western Electricity Coordinating Council (WECC) is a newly developed load model that has drawn great interest from the industry. To analyze its dynamic characteristics with both mathematical and engineering rigors, a detailed mathematical model is needed. Although composite load model of WECC is available in commercial software as a module and its detailed block diagrams can be found in several public reports, there is no complete mathematical representation of the full model in literature. This paper addresses a challenging problem of deriving detailed mathematical representation of composite load model of WECC from its block diagrams. In particular, we have derived the mathematical representation of the new DER_A model. The developed mathematical model is verified using both MATLAB and PSS/E to show its effectiveness in representing composite load model of WECC. The derived mathematical representation serves as an important foundation for parameter identification, order reduction and other dynamic analysis.