Deadline Date: 15 March 2026
The shift to global low-carbon energy systems has boosted the popularization of solar photovoltaic (PV) technology, shifting the power generation landscape. Solar power presents many environmental and economic advantages but integration into the installed base of power systems is extremely challenging from a technical perspective because the solar energy supply is intermittent and variable. These generation output fluctuations can destabilize voltage and frequency, impact power quality, and undermine grid reliability, especially in systems with high solar penetration. To counter these threats, sophisticated numerical techniques have become critical to model, simulate, and optimize the performance of power systems interconnected with distributed and utility-scale solar PV units. This research focus not only enables the credible integration of solar power into contemporary electric grids but also works toward the building of resilient, smart grid structures. Relying on sound numerical approaches guarantees accurate performance projections, design decisions based on solid information, and cost-efficient control schemes that enhance the sustainability and reliability of next-generation energy systems. The integration requires a good knowledge of dynamic system interaction, changes in loads, inverter control strategies, and coordination of energy storage all of which can be easily learned by computational modeling methods.
Numerical simulation and modeling methods, including Finite Element Method (FEM), Finite Difference Method (FDM), and numerical time-domain analysis offer a mathematical formulation to mimic the power flow dynamics, transient stability, harmonic distortion, and voltage fluctuations in grid-tied PV systems. Power flow simulations and stability tests using nonlinear differential equations play a crucial role in comprehending the effects of high PV penetration. Software: Newton-Raphson load flow solvers and dynamic stability programs assist in finding critical operating points that lead to voltage collapse or frequency instability. In addition, multi-objective optimization algorithms, including Genetic Algorithms, Particle Swarm Optimization (PSO), and Sequential Quadratic Programming (SQP) are used more and more to optimize inverter control strategies and optimize the sizing and dispatch of energy storage systems. A novel area of focus is the application of reduced-order models (ROMs) and physics-informed neural networks (PINNs), which yield computationally effective surrogates to the complex grid models without sacrificing the fundamental physical laws. The numerical optimization is also applied to the area of reactive power compensation, fault ride-through, and grid code compliance.
This special issue welcomes high-quality original research, technical reviews, and papers dealing with numerical modeling, algorithmic formulation, and simulation-based optimization of solar power integration into power grids. The emphasis is placed on the use of finite element methods (FEM), finite difference methods (FDM), optimization algorithms, power flow analysis, dynamic system modeling, and control theory to tackle the multi-scale, multi-domain issues involved in PV-grid coupling. We especially encourage submissions that connect theoretical modeling with real-world applications, such as verified simulation platforms, and hardware-in-the-loop (HIL) tests providing real-world grid integration performance demonstration.
The shift to global low-carbon energy systems has boosted the popularization of solar photovoltaic (PV) technology, shifting the power generation landscape. Solar power presents many environmental and economic advantages but integration into the installed base of power systems is extremely challenging from a technical perspective because the solar energy supply is intermittent and variable. These generation output fluctuations can ... show more
Editorial board
