Charles H. Wells, PE, OSIsoft, LLC
Few doubt that rising levels of renewable energy will play a pivotal role in the electric grid over the coming years. To help drive down carbon emissions, 29 states have already enacted renewable portfolio standards (RPS) that require more than 20 percent renewable generation by 2020. The major issue is that utilities generally restrict distributed generation to less than 15 percent.
Despite the best intentions of U.S. policymakers to increase the use of renewable energy, one fact remains: our aging electric grid cannot handle the current high volume of requests for distributed generation systems like solar photovoltaic, fuel cells and electric vehicle charging systems.
The power grid in place today was designed for power to flow from large fixed-generation sources to radially distributed loads. Typically these distribution networks were designed to carry power to loads using lowest cost wires and transformers necessary to meet power quality and protection standards for unidirectional power flow. So even if utilities could build large-scale solar generators overnight, the power could not be delivered to market without new transmission lines that could take more than 20 years to build or commission. In addition, given the increasing shortage of experienced power engineers, the manpower simply isn’t available to meet the RPS or increased power demand.
One of the more attractive potential solutions to this problem is the increased use of microgrids. More than simply a small grid, microgrids feature a single point of connection to an area electric power system (EPS) and can seamlessly connect and disconnect to the larger grid. Microgrids offer a number of attractive advantages:
- They can play a unique role in the integration of renewable power sources into the grid by giving power companies a defined method to integrate larger percentages of renewable energy in the current electric power system.
- They can help regulate the main grid by providing the “shock absorbers” necessary to accommodate electric vehicles and large grid-scale renewable energy sources such as wind and solar.
- They can improve electric power reliability and security by offering the ability to disconnect from the main grid during extreme weather events while continuing to provide power to critical loads inside the microgrid.
- And, perhaps most importantly, they give microgrid owners and operators a new source of revenue. By providing local frequency and voltage control at the point of common coupling between the microgrid and the area EPS, microgrids allow utilities to purchase ancillary services such as frequency regulation, voltage regulation, demand response, spinning reserve, black start support, curtailment and carbon credits. In some areas microgrids may sell excess power into energy markets.
The electric power industry believes that the integration of microgrids is one of the key steps needed to meet current challenges, but to understand the dynamic behavior of their microgrids system designers and operators will need both historical and real-time data. With that data operators can control their systems to regulate both the internal intermittent generation and load variations as well as the disruptions from the connected grid.
IEEE standards 2030.7 and 1547.4 define microgrids as a group of interconnected loads and distributed energy sources within clearly defined electrical boundaries that act as a single controllable entity with respect to the grid. They must offer the ability to automatically connect to and disconnect from the grid to enable it to operate in either grid-connected or “islanded” mode.
The IEEE standards state that a microgrid must be capable of operating autonomously from the electric grid by supplying all of its generation to critical loads for a defined interval. They must be characterized as having a controller capable of automatically integrating and coordinating the generation, storage, controllable loads and grid integrity equipment within the microgrid to interact with the larger grid as an aggregated single system. The controller must provide control functions that can manage itself, operate autonomously or grid-connected, and seamlessly connect to or disconnect from the main distribution grid for the exchange of power and management functions. Typically the microgrid controller must have both real-time control and energy management functions.
To address the needs of the electric power industry as it integrates microgrids into the electric grid, the energy surety system (ESS) depicted above offers three distinct levels of control.
The unresolved issues related to this new grid architecture include:
- Intermittent renewable power generation integration increases the complexity of the power system, such as when clouds cover solar panels and the immediate loss of power must be supplied from other sources.
- Cybersecurity issues increase design complexity due to increasing attacks on national power grids.
- Obligation fulfillment with energy service companies offering power purchase agreements may increase control system requirements.
- Energy surety for critical loads when operating in island mode can be difficult to provide.
- Island mode operation with intermittent renewables can be difficult and requires a more agile control system.
- Microgrid control with increasing levels of electric vehicle charging systems presents new challenges.
- Integration of a wide variety of energy storage systems including batteries, thermal storage, ultra-capacitors, pumped storage and compressed air storage increases the complexity of the microgrid storage system.
Few, and possibly none, of the microgrids in use today meet the definitions outlined in the IEEE standards and no control systems are capable of resolving all the problems outlined above. The system described below offers a potential solution, however. This energy surety system (ESS) integrates three levels of control to deliver energy surety to critical loads inside the microgrid, income from ancillary services contracts with the same area electric power system, and revenue from carbon credits created inside the microgrid. The three-level ESS depicted on page 32 offers rapid response to real and reactive power commands from fast regulation markets providing enhanced grid stability to the distribution utility. That, in turn, enables high penetrations of solar and electric vehicles while supporting fast restoration after natural disasters. This system also is capable of participating in autonomous fast regulation markets.
The first level of the controller features fast feedback controls that send real and reactive power changes to four quadrant inverters associated with the distributed energy resources (DER) inside the microgrid. The system maintains voltage and voltage angle setpoints using a patented decoupled controller that sends real and reactive power commands at 60 hertz (Hz) to the inverters. The voltage and voltage angle setpoint of each DER is determined by a second level supervisory controller. One of the DER control loops is designated the “regulation” controller, while the others are “state” controllers. Typically each DER is located on separate branches of the network and has independent voltage and angle setpoints.
The second level controller is a fast feedback decoupled real and reactive power controller operating at one Hz rate. This control loop supervises the voltage and voltage angle setpoints of the “regulation” controller and will automatically spillover to another DER controller when the current regulation controller saturates. This architecture is analogous to the “cascade control” systems used extensively in other industries.
The third level controller optimizes the microgrid by using a network flow model to determine the optimal state variables in the system. The state of the system is defined as the voltage magnitude and angle at each branch of the microgrid. The system includes a state estimator with the angles referenced to the GPS clock so that no slack bus is required. A user specified objective function is maximized and typically defined as profit subject to network flow constraints in the system. This objective function can also include internal energy losses so that the controller could determine the optimal voltage setpoints for conservation voltage reduction. The model executes at one second intervals and includes commands issued from the connected distribution system operator’s (DSO) or independent system operator’s (ISO) grid requesting fast regulation, demand response, curtailment, spinning reserves or black start support.
ESS software is built into the system using commercial products configured with the IEC 61970 Common Information Model tool. Inexperienced staff can use this software package to build a standard CIM XML file directly from the one-line diagram representing the microgrid. This file becomes the master configuration file and can be used to load both the real time infrastructure system (PI-AF) and the network flow model. All three controllers get their data directly from the PI System. The ISO/DSO communicates directly with the PI System using an encrypted secure link such as an openADR.
The ESS includes five unique asset framework templates for unwrapping angles, angle differencing, event detection independent of threshold settings, grid failure detection using moving window fast Fourier transforms and automatic system dynamic parameter identification.
Dual substation hardened PCs are used as the computer platform for the master control system software. This redundant system allows programmers to create software patches while on closed loop control. The redundant PI System has been tested by Idaho National Laboratory’s SCADA testing facility and found to follow best current cyber secure practices. The system is fully virtualized allowing the network flow model and interfaces to run in independent virtual machines.
Over the last few years the electric power industry has begun to recognize the advantages microgrids offer as a way to support increased use of renewable energy on the grid. To reach this goal, however, microgrids will require sophisticated control systems built around a real-time data infrastructure to collect high speed, time-synchronized data from a variety of sources. The ESS outlined above offers a three-level solution capable of meeting many of these requirements.
Charles H. Wells, Ph.D., PE, is Industry Principal at OSIsoft LLC and is a visiting scholar at the University of California in San Diego (USDC). He has more than 30 years of experience in real-time control and monitoring, has published over 50 technical papers, holds 10 U.S. patents, and is co-author of two textbooks. At UCSD he is involved in microgrid research involving phasor measurement units as applied to control and monitoring. He is also working with multiple energy storage systems on campus providing peak shifting and regulation functions. He has a Ph.D. in electrical engineering, and Master’s and Bachelor’s degrees in chemical engineering and is a registered professional engineer.