1
Background & Problem Statement:
The widespread Distributed Energy Resources (DER) proliferation has introduced critical challenges to the energy industry over the years. As the deployment of renewable energy resources accelerates, the complexity and uncertainty of the management system grow exponentially. Aged infrastructures and control solutions are limiting the utilities in providing more efficient and robust systems. Ranial Systems, partnered with Power Edison from New Jersey, addressed these issues with its innovative solutions and delivered the world’s largest mobile energy storage system to one of the largest utilities in the Northeast US. The fleet of storage and integrated CognitEMS™ platform is designed to deliver an agile solution for peak shaving, balance, and optimizing the distribution grid in real time while reducing voltage excursions and maintaining system reliability and power quality across the network
2
Approach
The patented solution offered by Ranial Systems addresses the limitations of the existing DER management systems (DERMS) available in the market. The existing DERMS rely on predetermined setpoint values and responses to the events that have already occurred in the system. This reactive approach requires 24/7 manual intervention and results in high operating costs, low efficiency, and considerable energy wastage. Moreover, this fail-safe operation practice will diminish the asset’s life-time-value. Mission critical operations performed through cloud native DERMS are not reliable in terms of addressing the critical need in a timely fashion.
Ranial Systems introduced a proactive control strategy using hybrid system:
- Site controllers can be integrated with OT systems and Utility SCADA applications to offer real-time operational intelligence and ubiquitous control operations and,
- The cloud system offers real-time monitoring of the DER systems, managing alarms, rules and AI models deployed at the edge controller, based on the operational needs. It also provides various business intelligence reports based on the real-time performance metrices.
However, most of the mission critical operations and intelligent controls are executed at the site controller level to maximize responsiveness. The deployment topology of the mobile energy storage system could leverage the real-time predictive operations, gain situational awareness, and instantly act on operational needs.
3
Solution
The CognitEMS™ offers modular system components. The Edge application is compliant with Sunspec information model specification 1.9 (4000 + instruction sets supporting 6 types of DER assets) and offer Modbus and OPC interfaces to integrate SCADA/ ADMS systems. Such integration facilitates operator and NOC operations through a seamless integration of utility O&M systems. The prebuild AI powered models and rules can intercept the sensory feeds and execute intelligent operations in:
- Enhancing system resiliency and reliability by detecting anomies
- Predictive operations to shift load away to achieve best price performance. • Prescriptive load shaping to Improving load factor.
- Minimizing system losses through phase balancing and improved power factor (Volt/ VAR, Watt/VAR optimization, Constant VAR, and power factor correction)
- Prescriptive insights to managing voltage profiles -, voltage and frequency ride through. • Managing congestion and circuit overloads, which defers capital expenditures. • Economic dispatch and other grid services to bulk power and electricity markets • Intelligent services to facilitate Supervisory charge/ discharge, Renewable Ramping/ smoothing operations.
The following diagram depicts the solution architecture and deployment topology of Ranial’s Integrated Asset and Energy Management platform:
The cloud platform is designed to monitor and manage multiple sites/ plats, logging Alarms/ notifications, configuring remote DER assets. It also offers historians and self-service dashboards to curate various KPIs as needed. The Real time AI models offer unique set of KPIs to facilitate real-time predictive maintenance and condition-based monitoring:
- Circuit loading and voltage assessment by each phase for real-time situational awareness, circuit condition and load forecasting, and “what-if” analysis.
- Proactive indicators on coordinated scheduling and optimization of DER asset operations for resiliency, reliability, and economic objectives.
- Optimized dispatch for Circuit and feeder load relief and Volt/VAR management • DR-DER dispatch and control for both individual and aggregated assets. • Proactive intelligence on Active and reactive power dispatch and scheduling, phase balancing, and loss minimization.
- Realtime visibility and centralized operation to manage Supply of capacity, energy, ancillary services, and frequency regulation using DR and DER assets.
- Direct, two-way communication with DER assets to provide measurement, monitoring, control, scheduling, dispatch, settlement, and reporting.
- Intelligent models to aggregate DR/DER assets into Virtual Power Plants (VPPs) that can be used to provide new bulk power services like load following/ramping and Primary Frequency Response (PFR).
-
Dynamic rule engine to provision custom monitoring rules on the edge/ site controllers to facilitate need-based monitoring functions.
The muti-tenant CognitEMS™ cloud platform offers single pane of glass to manage multiple sites, model microgrid operations and deploy intelligent autonomous sequencing, controlling and monitoring.
4
Implementation
The following depicts the integration approach of the utility scale DER / BESS fleets supporting 6 MW mobile BESS deployment for a major utility company located at Northeast USA. The dynamic controls and DER/ microgrid operations can be achieved by these systems on demand by relocating the trailers to specific substation or a remote renewable plant.
The designed solution is an easy to integrate and detach unit of systems containing a PCS (power conditioning system) trailer and two BESS trailers connected to the PCS trailer. The PCS trailer contains large scale inverter (serve up to 1.5 MW), transformer (1.5 MW) and other protection equipment that integrate utility feeder circuit.
5
Result
Ranial provisioned the system and performed initial training of the models in 3.5 months. The implementation could achieve ~ 22% more operating efficiency by deploying intelligent proactive monitoring and control functions. The design and integration of ADMS and remote monitoring could reduce 33% of O&M overheads