|Changes to the grid require changes to the control systems that manage it
The electric power control systems of the past were designed to manage the flow of power from central generators through transmission lines to distribution substations, then on through distribution lines to consumers.
They were designed before wholesale and retail electricity markets were created, before the smart grid, and before consumers began deploying solar panels and electric vehicles.
The electric power industry is spending billions of dollars on the smart grid, primarily deploying smart meters and advanced metering infrastructure (AMI), to enable dynamic pricing and customer participation in markets and operations.
The fact that consumers are producing and storing electricity combined with the simple idea that those consumers will adjust their power usage – either reducing it, changing their usage to move peak usage off peak times, or allowing utilities to temporarily shed certain loads when necessary to reduce their electricity costs – has created a need for massive changes to the systems used to manage power by the electricity markets and utilities.
Those systems have to cope with the possibility of electricity flowing in directions which existing power grid equipment and control room applications were not designed to handle.
Further changes are required due to the significant increase in the penetration of intermittent wind and solar generation resources, which create challenges in the areas of forecasting, scheduling, trading, balancing, regulation and settlement. This is further enforced by the fact that virtually every element of the power system will incorporate sensors, increased communications and computational abilities.
|Traditional power control systems were designed before the smart grid and consumer renewables
These changes to the grid require changes to the control systems used to manage the grid. Traditionally, managing power transmission networks consisted of using the Supervisory Control and Data Acquisition (SCADA) functionality of Energy Management Systems (EMS – sometimes called transmission management systems or TMS) to use phone lines – and IP networks later – to telemeter data from field devices through data concentrators called remote terminal units (RTUs), and to control devices by routing remote controls through those RTUs.
EMS/TMS systems had a suite of advanced applications incorporating detailed models of the transmission circuits/devices, central generation and electrical loads on the transmission grid to track how close equipment was operating to physical limits, identify congestion paths, model system behaviour for a variety of pre-defined failure contingencies, and recommend optimal ways of managing the power flow and operating generation assets in an economically optimal manner.
During the push for utility deregulation during the 1990s and early 2000s, many utilities split the management of generation assets away from the management of transmission assets, with a corresponding split of the EMS system into two systems – a generation management system (GMS) with SCADA functionality and applications, and a transmission management system (still called EMS or TMS).
Managing power distribution networks consisted mainly of performing planned switching and restoring systems after unplanned outages, using manual paper-based methods. Given the changing characteristics of the distribution networks today, a number of systems have been introduced for more effective management and control, including SCADA, outage management (OMS), distribution automation (DA), and distribution management (DMS), along with supporting technologies such as geographic information systems (GIS).
Since these systems overlap to a degree, operators also often need multiple graphical user interfaces (GUIs) to monitor, control and optimize networks. Incremental changes have been made to the EMS systems used to manage the transmission grid and at the distribution level there has been a convergence of SCADA, OMS, DA, and DMS to create advanced distribution automation systems (ADMS) with a common database and user interface for all distribution users.
Vertically integrated utilities often use a single system to manage both transmission and distribution grids, though typically using a separate system for distribution outage management.
Most utilities have installed systems from different vendors, or employed systems that were heavily customized, limiting the ability of the various systems to easily interact. The electricity markets (ISOs, power pools) are creating additional ancillary services in response to the increasing impacts of unpredictable wind and solar power and the increasing need to be able to manage load through aggregated demand response.
As part of the smart grid implementation, utilities have been deploying smart meters, AMI, and meter data management systems (MDMS). While primarily focused on customer billing, these technologies also enable two-way communications with customers.
Combined with customer-facing portals to support the registration and interaction required, these technologies create the initial framework for utilities to enable customers to see how their energy usage impacts their electric bill and how they can alter their usage to reduce their electricity costs, and to sign up for demand response programmes in exchange for a reduction in their electric bill.
The smart meters and associated infrastructure offer utilities a view of the true electrification of the distribution network they’ve never had before, because they can see whether or not each smart meter is getting electricity.
Prior to this, while larger-scale losses of power were visible to them, the loss of electricity at one customer – or even a group of customers tied together through a common transformer or fuse – was visible to the utility only when someone called in and reported it.
The utility can also remotely connect or disconnect customers through the smart meter, avoiding the recurring cost of sending trucks and crews to customer sites each time they have to enable or disable service to a site. Integrating the meter data and remote control of meters with the ADMS systems used in the control room will enhance distribution control room operations.
Given these changes to the nature of power flow on the grid and the integration of markets and consumers, a new generation of highly flexible control systems (therefore the name Gen X for flexibility) must be developed—incorporating a holistic view of the changes described above and providing utilities a system with strong cyber security and the ability to improve economic productivity, maximize efficiency, and minimize environmental impact.
The Gen X control system will have an architecture that will extend from ISO/RTO functionality all the way down to residential customer premises including HANs, capable of visualizing, controlling, and optimizing power usage on any level of network.
|The modern control system will be modular
The system will be modular, will allow only the required functionality to be deployed for a given entity (e.g., ISO, RTO, utility, etc), will bring together the physical and information infrastructures of electricity/gas management, and will address at least the following shortcomings of existing control systems:
- Limited support for grid-connected renewables:
- Understanding the variability/volatility in different geographies;
- Higher resolution and improved forecasting (load and generation);
- Market clearing, dispatch, and AGC – risk-based dispatch, integrated short-term forecasting, etc.
- Lack of support for dispatchable energy storage;
- Limited support of distributed energy resources:
- Modeling of virtual power plants;
- Modeling and control of microgrids;
- Visibility and control of demand response resources;
- Telemetry of data (beyond AMI);
- Control of end devices (not AMI);
- Cyber security;
- Market integration.
- Lack of ability to scan large numbers of devices (including IEDs and PMUs) at the fidelity required to provide operators adequate visibility into the electric network;
- Lack of ability to store high-frequency data and integrate access/visualization of that data with existing operator functionality;
- Limited support for fibre-connected substations using IEC 61850 protocol messaging;
- Lack of support for on-line advanced sensors, advanced condition monitoring and centralized software tools with condition monitoring analytics;
- Lack of the high-resolution generation/load forecast (e.g., 30-second forecasts over the next hour) required to handle the unpredictable nature of renewables, and integration of the results with control applications;
- Lack of visualization of renewables, storage and demand response availability – limiting operators’ capability to engage these resources as needed (e.g., to support outage restoration);
- Lack of adequate analytic capability to support complex calculations using very large data samples;
- Lack of intelligent alarm processing that utilizes an understanding of network topology and equipment characteristics to minimize and prioritize the presentation of alarms to operators;
- Poor integration between transmission and distribution level planning/operations data models and applications;
- Poor integration of asset information, network model information, and SCADA parameters within data engineering tools;
- Limited use of stochastics/probabilistic analysis in operations and planning;
- Limited integration with physical security at substations (e.g., video feeds);
- Limited use of service-oriented architecture (SOA) to enable integration of control system components;
- Limited support for decentralized and hybrid control of grid devices;
- Limited use of phasor measurement unit (PMU or synchrophasor) data for wide area monitoring and protection;
- Limited support for “self-healing” grids .
The disparate nature of data used by operational and non-operational applications has led utilities to deploy two primary ‘systems’ in their control room – an operations system and a non-operations system.
In some cases they share a communications infrastructure to substations and field devices, but collect different types of data to be used for different purposes. In most cases they have independent communications infrastructures.
Usually, the non-operational data (fault recordings, IED/PMU data like waveforms, etc) is collected by applications that are not integrated, serving individual purposes.
In the future the operational and non-operations applications will be decoupled from the telemetry and control of devices, with SCADA platforms capable of collecting both operational and non-operational data responsible for the device interfaces of both.
The SCADA platform will publish the data to all applications that register to receive it, including a common data warehouse, and will issue controls to devices or send data to other control systems when told to do so by authorized applications.
The applications included in current EMS/TMS, GMS and ADMS systems will be a next generation version of the systems of today, updated to address the missing functionality described above. In addition, a widely increased use of data analytics packages will be used to analyze combinations of operational and non-operational data to optimize planning, real-time operations, maintenance and revenue collection.
As the proliferation of renewables, energy storage, smart meters, electric vehicles and power market ancillary services make the smart grid a reality, updating the control systems used to manage them is a must.
Taking a holistic view and designing the control system of the future with modern architectural concepts, adding missing functionality from today’s vaguely-coupled operational and non-operational systems, will improve the operational and financial performance of the utilities, improve the experience of utility customers, and give those customers the opportunity to reduce their electric bills through quality interaction with their electric providers.
Nicholas Abi-Samra is a senior vice-president and John McDaniel is a senior principal consultant at DNV GL
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