Multi-objective optimization framework for optimal power flow problem of hybrid power systems considering security constraints
The hybrid model of the power system infrastructure is an essential part of the sophisticated
technology of the electrical network. Generally, for the Optimal Power Flow (OPF) problem …
technology of the electrical network. Generally, for the Optimal Power Flow (OPF) problem …
Many-objective gradient-based optimizer to solve optimal power flow problems: analysis and validations
The growing energy demand and environmental consciousness provoke the conventional
single-objective optimization framework no longer satisfies new power system planning and …
single-objective optimization framework no longer satisfies new power system planning and …
Evolutionary constrained multiobjective optimization: Scalable high-dimensional constraint benchmarks and algorithm
Evolutionary constrained multiobjective optimization has received extensive attention and
research in the past two decades, and a lot of benchmarks have been proposed to test the …
research in the past two decades, and a lot of benchmarks have been proposed to test the …
Chaotic sine–cosine algorithm for chance‐constrained economic emission dispatch problem including wind energy
One of the most effective approaches to reduce carbon emissions is the integration of
renewable energy sources into electrical power networks. Currently, wind turbines are the …
renewable energy sources into electrical power networks. Currently, wind turbines are the …
Multi-agent-based collaborative regulation optimization for microgrid economic dispatch under a time-based price mechanism
L Wang, X An, H Xu, Y Zhang - Electric Power Systems Research, 2022 - Elsevier
The economic optimal dispatch of a microgrid is a challenging task with significant economic
and social implications. Under a time-based price mechanism, this paper proposes a multi …
and social implications. Under a time-based price mechanism, this paper proposes a multi …
Low-carbon optimal scheduling for multi-source power systems based on source-load matching under active demand response
J Ye, L **e, L Ma, Y Bian, C Cui - Solar Energy, 2024 - Elsevier
To reduce the source-load uncertainty and carbon emission levels of the power system, this
study proposes a novel low-carbon economic stochastic optimization scheduling model …
study proposes a novel low-carbon economic stochastic optimization scheduling model …
New optimization algorithm inspired by kernel tricks for the economic emission dispatch problem with valve point
R Dong, S Wang - IEEE Access, 2020 - ieeexplore.ieee.org
With the increasing concern over environment protection, Economic Emission Dispatch
(EED) problem has received much attention. It is essentially a Multi-objective Optimization …
(EED) problem has received much attention. It is essentially a Multi-objective Optimization …
Eco-environmental dispatch of power system with high penetration wind farms considering demand/source side uncertainties
A Heydari, R Ebrahimi, M Ghanbari - Electric Power Systems Research, 2024 - Elsevier
In this paper, a stochastic economic-emission dispatch (EE-D) of a power system with wind
farms and flexible loads is proposed. The EE-D is defined as a stochastic multi-objective …
farms and flexible loads is proposed. The EE-D is defined as a stochastic multi-objective …
MOEA/D with many-stage dynamical resource allocation strategy to solution of many-objective OPF problems
J Zhang, X Zhu, P Li - International Journal of Electrical Power & Energy …, 2020 - Elsevier
As people's electricity demand and environmental awareness increase, single-objective
optimization of power systems can no longer meet the requirements of modern power …
optimization of power systems can no longer meet the requirements of modern power …
Constraints separation based evolutionary multitasking for constrained multi-objective optimization problems
Constrained multi-objective optimization problems (CMOPs) generally contain multiple
constraints, which not only form multiple discrete feasible regions but also reduce the size of …
constraints, which not only form multiple discrete feasible regions but also reduce the size of …