ESB: Battery dispatch optimisation for grid flexibility
Context Battery storage plays a critical role in supporting system stability and enabling higher penetration of renewable energy as part of the Net Zero transition. Challenge Optimising how battery assets are used across different system conditions is complex, requiring coordination between system needs, renewable generation, and operational objectives. AI Solution The solution embeds AI-driven optimisation […]
ESB: Wind turbine performance monitoring
Context Wind generation assets require continuous performance monitoring to ensure optimal output and detect deviations early. Challenge Identifying underperformance or inefficiencies at the turbine level is difficult without continuous comparison against expected performance benchmarks. AI Solution The solution creates turbine-specific reference power curves for each turbine in the fleet. The AI model compares how much […]
Siemens: Visual detection of low voltage (LV) switching states
Context Switching operations in low‑voltage networks are commonly performed by plugging and unplugging fuses in cable distribution cabinets. Challenge There is limited visibility into the actual switching status of low‑voltage networks, as switching activities are often not documented or not documented accurately. Lack of reliable information leads distribution system operators to make incorrect assumptions during […]
Siemens: AI‑assisted power quality monitoring
Context Power quality conditions and grid incidents affect operational continuity in electrical distribution and transmission grids and in industrial distribution grids. Challenge Power quality disturbances can lead to outages, equipment damage, and associated costs across distribution and transmission grids, including industrial distribution networks.Continuous monitoring is needed to detect and diagnose power‑quality incidents early and support […]
Schneider Electric: Agentic AI for major event readiness and climate resilience
Context Utilities today operate in an environment where severe weather events and wildfire exposure are an integral part of day‑to‑day system operations and planning. Challenge Utilities need to anticipate and manage severe weather and wildfire-related risks earlier, while coordinating multiple data sources, teams, and decisions across preparation, prevention, response, and recovery workflows. AI Solution The solution uses […]
Schneider Electric: Distributed Energy Resources (DER) congestion forecasting and flexibility for grid constraint
Context Networks are experiencing growing levels of distributed energy resource (DER) connection and intermittency, which increases the likelihood of local network constraints such as congestion, voltage excursions, and overloads. The operational environment requires earlier visibility of where and when constraints may emerge, alongside more coordinated planning and operational decision-making to maintain stable and flexible system […]
Schneider Electric: Grid AI assistant for Advanced Distribution Management System (ADMS) operations
Context Utilities operate complex Advanced Distribution Management System (ADMS) environments that often require users to rely on extensive documentation and a limited pool of experienced specialists to find the right functionality, configure features, and complete tasks efficiently. Challenge Complex ADMS environments can slow workflows, extend onboarding, and make knowledge access more difficult as experienced personnel retire and institutional know-how […]
Kaluza: Demand flexibility orchestration engine
Context Millions of distributed assets such as EVs (electric vehicles), heat pumps, batteries, and smart appliances could provide electricity system flexibility, but only if they are coordinated in real time across tariff structures, grid constraints, and customer preferences. Challenge The operational need is to coordinate large volumes of distributed assets in real time while accounting […]
Kaluza: Historical consumption estimation & forecasting
Context Many regions continue to rely on traditional meters or smart meters that communicate infrequently, creating a need to estimate customer electricity consumption to enable timely billing by energy retailers. Challenge Current heuristic, benchmark-based estimation approaches have a stated performance ceiling, leading to bill shock, customer churn, increased cost to serve, and revenue leakage worth […]
Hyosung: ARMOUR+ Power Facility Asset Management Platform
Context Power facilities rely on high equipment availability, and continuous monitoring supports more proactive asset management and maintenance decisions. Challenge Unplanned downtime and limited visibility into equipment condition can reduce reliability and increase operating costs across power facilities. AI Solution ARMOUR+ uses AI and machine learning to analyse real-time and historical data from power facilities. […]