xPatterns - Energy

For a really smart grid

Electricity is not the only resource flowing through our power lines. The other is data itself. The smart grid is a data-driven concept. It will hinge on our ability to respond in real time to the information that describes our use and sources of power. Replacing the one-way communication between utilities and their customers with a dynamic, efficient, demand-driven dialogue means grasping all the possible inputs and exchanges that shape this "conversation" at any given moment.

The opportunity to improve our production and use of energy is vast, and the need is urgent. It's estimated that as much as 10% of electricity generated today is lost in transmission, at a cost of approximately $25 billion every year; meanwhile, the demand for power continues to rise. For Atigeo, helping develop ways to generate, distribute, and use energy more efficiently is one of the most significant contributions the xPatterns platform can make:

Synchronizing non-continuous generating units, such as wind and solar, with traditional generating units
Providing the tools needed to develop micro-contracts very quickly
Providing incentives in the face of physical and regulatory constraints
Filling the gap in tool availability with respect to resilience planning

To discuss how we can assist your Smart Grid implementation, contact us at sales@atigeo.com

Impacts of the xPatterns smart grid solution:

Issue	Impact
Renewables cannot effectively be incorporated in current power grid	Incorporation of non-synchronous source in synchronous grid
Power-grid reliability	xPatterns rules-based, hybrid solution leads to more reliable generation, delivery and consumption of power
Power-grid efficiency	Enable handling of disparate voltage generation in two connected grid nodes
Expressed rules currently cannot be incorporated in the decision process	The xPatterns solution expresses incentives as rules for rescheduling activities during less expensive off-peak hours and addresses comprehensive constraints: Governmental regulations Contract agreements Incentives Capacity planning
Uncertainty Management Structural uncertainty Exogenous uncertainty	The xPatterns solution has mechanisms for learning and repair, and it also can help forecast variability in demand and supply Inductive cidentification of microlocal state model dynamics via learned rules from sensory history Unbiased State estimation and forecating
Outages such as: Brownouts Blackouts	Improves grid resilience Dynamic Reconfiguration by riticaliity of loads, Recovery sequencing to avoid overloads Minimum recovery time, optimal recovery sequencing without overloads
Programmable Metrics	For example, minimizing heat dissipation in power plants
Maximize: Revenue, Quality Of Service (QOS), Reliability Minimize: Cost, Brownouts, Reconfiguration	Multi-objective optimization
Cricality Metric	Manages over-capacity dynamic loads
State Feedback Contol	Integration of real-time communication and Control Protocols
Dynamics Synchronization	Integration of bulk power systems with distributed energy resources
Security	Mitigation of cyber intrusion
Current methods require ad-hoc heuristics and human operator adjustments at the substation level	The xPatterns solution uses formal methodologies based on rules-based control; decoupling of economic dispatch model from distribution and from transmission
Extensibility as the smart grid grows	In the xPatterns solution, rules are data; whereas in conventional systems, they are programmable elements