Meet the Grid Foresight Lab | Driving power grid transformation

Quantum Computing and the Future of Power-System Optimisation: Promise, Hype, and the Road Ahead

BlogBy Ahmed Al-Shafei January 26, 2026

Quantum computing has been marketed as the next great computational revolution. A technology capable of reshaping materials science, leading to drug discovery, disrupting cryptography, helping in discovering new batteries, climate mitigation strategies, optimizing global energy systems [1-6], or supposedly cracking optimization problems that have resisted decades of classical computing, if you believe the brochures. Quantum…

How Wildfire Smoke Disrupts Voltage Stability in PV-Rich Distribution Grids

BlogBy Ala’a Al Sharif December 8, 2025

Wildfire smoke is no longer just an air-quality concern; it’s becoming a real operational factor for modern electric grids. As photovoltaic (PV) systems continue to integrate into distribution networks, feeder performance becomes increasingly dependent on weather and environmental conditions. Under clear skies, PV panels inject substantial power into the grid and reshape how voltages behave…

Agents for Optimizing Power Distribution Systems – Is this the Future?

Blog, Journal articleBy Shoaib Hussain October 29, 2025

The Optimal Power Flow (OPF), as an optimization problem, is indispensable for the economic and secure operation of power distribution networks. The OPF is crucial for achieving a multitude of operational objectives including: Solution techniques for the OPF problem have traditionally gravitated around classical deterministic and stochastic mathematical programming methods. These methods allow practitioners to…

Solar panels, wind turbines, and an energy storage system under a bright sky, representing renewable generation and energy storage integration.

Emissions Response through Energy Storage System: A Path Toward Smarter, Cleaner Grid Operations

BlogBy Vahid Hakimian October 28, 2025

Across the energy sector, storage has long been recognized as a cornerstone of grid reliability and renewable integration. Yet, the conversation about its environmental role often overlooks how they can actively contribute to carbon reduction. Our recent research, accepted for presentation at the Hawaii International Conference on System Sciences (HICSS) 2026, introduces a framework for…

Physics-Informed Neural Networks for Grid-Connected Batteries

BlogBy Fatemeh ShakeriHosseinabad September 7, 2025

A Physics-Informed Neural Network (PINN) is a machine learning architecture designed to solve scientific problems by harmonizing data with physical laws. Its core innovation lies in training a neural network not only to fit observed data but also to adhere to known governing equations, typically ordinary or partial differential equations. This is achieved by incorporating…

Designing for Flexibility: Navigating Imperfections in Competitive Electricity Markets

BlogBy Manuel Zamudio López August 26, 2025

Competitive electricity markets are inherently complex. They require the integration of technically feasible operations, grounded in physical laws, with economically viable solutions that incentivize investments. These interactions aim to ensure a reliable, efficient, and technologically flexible market design. However, the operation of these markets is neither trivial nor perfect. Over time, they are exposed to…