With the power grid becoming even more dynamic, there is a need for not only microgrids, but microgrids that can adapt to a changing topology. With the addition of Electric Vehicles (EV) and the need to adapt to failures due to fire and weather, the layout of a microgrid, and the availability of resources, may change relatively quickly.
This creates many operational challenges that need to be addressed in the design of communication, control, and protection systems. Different grid scales also require different solutions, with transmission networks having significantly different requirements than substation-level microgrids. Architecting the multiple layers so that they work together without conflict is essential. The grid infrastructure needs efficient, advanced communications, control and metering infrastructure at all levels. At the edge, microgrids need to not only be able to operate independently for at least short periods of time, but also need to provide services to the larger networks including power generation, power quality control, voltage and frequency support, and load balancing. As resources at the edge change over time, being able to plug-and-play Distributed Energy Resources (DERs) and properly share the current state among them is critical. This is where RTI Connext has a critical role. This Case + Code provides a framework and reference architecture for grid edge interoperability and distributed intelligence. The framework consists of business-driven, top-down business case, use case, data modeling and implementation approaches.
The following diagram illustrates communication within and between the different components.
The grid of the future will require treating data differently; leveraging metadata and performing analysis locally to process the mountain of new data available from new technologies. Traditional headend systems have relied on relatively few sources of field information. New asset classes on the grid (AMI, smart inverters, PMUs, etc.) have added large amounts of data that can quickly and accurately describe the state of the power system. Traditional headend systems were not designed to process this increased volume of information as quickly as is needed to react to current operational scenarios and fully realize the benefits of these new grid edge assets.
Information no longer needs to go to the central system to enable decision making. Federated local data can be made securely available between assets at the grid edge to complement and enhance operations. As resources come online and go offline, this data can be used to maintain microgrid viability and even network groups of microgrids together when disconnected from the main grid.
Solar Simulator (Solar PV)
The solar simulator publishes the PV system power (PV output), PV system information, and PV system status. The solar simulator subscribes to control topics for connection and output (curtailment). There is also a subscription to a solar irradiance topic used for simulation.
ESS Simulator (EnergyStorage)
The ESS (Energy Storage System) Simulator publishes the power it is absorbing or generating, status, system information and VF Device capability. The status includes the system's SOC (State of Charge) and whether or not the system is acting as a VF Device. The ESS Simulator, along with the Generator Simulator can act as a VF device in island mode and includes code that simulates this behavior. The ESS simulator subscribes to control topics for connection and output. There is also a subscription to a topic used to manually establish SOC for simulation.
Generator Simulator (Generator)
The Generator Simulator publishes the power it is generating, status, system information and VF Device capability. The status includes whether or not the system is acting as a VF Device. The Generator Simulator, along with the ESS Simulator can act as a VF device in island mode and includes code that simulates this behavior. In the case of the generator simulator, a delay is included that does not allow the device to output power if it is disabled.
Load Simulator (Load)
The Load Simulator publishes the power it is absorbing, status and system information. The simulator subscribes to a Control message that allows the Load to be connected or disconnected from the grid independently. There is also a subscription to a topic used to manually set load for simulation.
Recloser Simulator (MainInerconnect)
The Recloser Simulator publishes the power flow through the main interconnection between the microgrid and the main grid. This is the device that is responsible for islanding and resyncing the microgrid from and to the main grid, as well as managing the active VF Device. The Recloser Simulator publishes the power flowing through it, along with device status, device information and microgrid status. The simulator subscribes to a topic that allows for planned islanding, planned resynchronization and immediate islanding.
Power Flow Simulator (PowerFlowSim)
The Power Flow Simulator takes information from each device on the network and generates the powerflow through the main interconnection. The simulator subscribes to all measurement topics and publishes to a topic used by the main interconnection for its power measurement topic.
The Controller handles setpoints for devices during islanded mode, along with decisions regarding the active VF Device. It publishes to device control topics and VF Control. The simulator also subscribes to all measurement topics in order to help balance the system during islanded operation. The optimizer also sets up VF Control transfer between the simulated ES and Generator systems.
The Visualizer allows visibility to all elements of the system, as well as control for solar irradiance, state of charge and manual device control. It publishes to the solar irradiance, state of charge and device control topics. It subscribes to all measurement, status, and information topics for presentation. The visualization uses GTK for generating the GUI, making it relatively cross-platform.