Open AccessCongestion management of integrated transmission and distribution network with RES and ESS under stressed condition
Author(s) -
Prajapati Vijaykumar K.,
Mahajan Vasundhara,
Padhy Narayan Prasad
Publication year - 2021
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/2050-7038.12757
Subject(s) - solver , transmission (telecommunications) , renewable energy , load profile , power (physics) , electric power system , computer science , transmission system , engineering , automotive engineering , reliability engineering , mathematical optimization , electrical engineering , electricity , mathematics , physics , quantum mechanics
Summary In this article, the multi‐objective optimization‐based congestion management approach for integrated transmission and distribution system under stressed condition is presented. The congestion is managed by optimized charging and discharging of energy storage systems (ESSs). The coordination among transmission system operator (TSO) and distribution system operator (DSO) takes place for the economic and optimum exchange of power. The main intent of this study is to minimize the amount of load shedding (MW) and its cost ($/ MWh ) by minimizing the generation cost ($/ MWh ) . These are conflicting objectives as for less load shedding, the system has to have more generation and hence higher cost. The negotiable solution among conflicting objectives is obtained by using the fuzzy min‐max approach. The ESS charging and discharging are optimized for their maximum contribution. This increases the available power (MW), thereby reducing the uncertainty of renewable energy sources and hence lesser load shedding. The analysis is conducted for constant load modeling (CLM) and voltage‐dependent load modeling. The results show that CLM has less load shedding. The proposed approach is implemented on a modified IEEE‐30‐bus test system integrated with the nine‐bus distribution network. Simulations and validations are done using General Algebraic Modeling Solver.