Three‐stage receding horizon‐based voltage control and electric vehicle charge scheduling of active distribution networks
Abstract In this article, a three‐stage, two‐level voltage regulation scheme based on receding horizon control (RHC) principles is proposed for active distribution networks. The distribution system consists of photovoltaic (PV) generators, electric vehicles (EVs), and electrical loads. Electric vehicle aggregators (EVA) act as intermediary between the prosumers and the network operators. The devised framework aims to coordinate various voltage control equipment according to their slow response (1 st stage) or fast (2 nd stage) response to voltage variations. In the 3 rd stage, the electric vehicle charge scheduling is accomplished and all these stages constitute to form upper‐level operation. Further, an effort has been made to maximize the profit of EVA for performing ancillary services during EV charge scheduling. Moreover, EVAs incorporate demand response programs to enhance network stability. While 1 st and 2 nd stages are formulated as non‐linear programming problems, the 3 rd stage is formulated as a mixed‐integer non‐linear problem. The problems are optimized using the CPLEX solver in the general algebraic modeling system (GAMS) environment. The lower control level is implemented by following a few rules that adjust the local Q(V) characteristics embedded in the power electronics interfaced devices. The obtained results exhibit that the devised framework not only helps in voltage regulation but also the EV owners and the EVA. Later, the profit earned by EVAs is computed for slow and fast charging schemes.
Authors
- Arunima Dutta (ORCID: https://orcid.org/0000-0003-0776-476X)
- Sanjib Ganguly (ORCID: https://orcid.org/0000-0002-7939-7308)
- Chandan Kumar
Institutions
- Indian Institute of Technology Guwahati (IN)
Publication Details
- Journal
- IET Renewable Power Generation
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1049/rpg2.12977
- Citations
- 2
- Primary Topic
- Electric Vehicles and Infrastructure
- Type
- article
- Field-Weighted Citation Impact
- 0.42