Distributed energy resource management - the way forward

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1 Distributed energy resource management - the way forward by Stuart Michie, ABB South Africa As the number of intermittent renewable and distributed energy resources (DERs) integrated onto the grid increases, digital solutions are required to manage the challenges posed by increased network complexity and load variability. Today s cloud and internet of things (IOT) technologies provide a new set of tools to achieve effective management of these resources. Widespread development of renewable energy technologies coupled with regulatory and policy directives has seen increasing levels of distributed generation and storage connected to distribution networks, directly connected to the networks and in customer networks that are behind the meter. Power distribution networks are being transformed by the connection of DERs such as rooftop solar, electric vehicles and energy storage. This increasing complexity of distribution networks creates operational challenges for network or system operators. Distribution network operators (DNO) need to operate the network reliably in the presence of high distributed energy resource (DER) penetration. DNOs need visibility into all DERs, including behind the meter assets, to monitor and potentially control them for safe and reliable network operation. DERs also brings new commercial opportunities, such as the creation of virtual power plants (VPPs) through the aggregation of these resources. Battery storage (BESS) and new forecasting tools using cloud functions such as artificial intelligence bring the ability to dispatch renewables, allowing VPP operators to participate more meaningfully in commercial power markets. Unlocking the potential in digital Since the early 2000s, innovation in technology has moved to the consumer space. This has led to dramatic improvements in computation, storage, and connectivity that are now spilling over to the industrial markets and are causing significant opportunity for new value creation. Cloud technologies and the internet make it easier than ever before to connect devices and sensors together and extract the data that they generate for the creation of additional functionality. Cloud services, such as machine learning and artificial intelligence, enable the creation of new applications. For distributed applications such as DERs and BESS, connection enables the operation and management of these resources that would not have been possible before. Aggregation in the cloud brings the ability to see how the assets are performing. End to end integration from the field to the boardroom starts at real time control in the field, continues to medium term optimisation and asset management functionality and ends at the boardroom to improve the quality of business decision making for future investment. Connection and analysis enables decision making using real data that is aggregated and analysed for the required purpose.

2 Fig 1 - End to end integration from the field to the boardroom Real time control A grouping of DERs at a local level together form a microgrid, which may or may not be connected to a grid supply. A typical microgrid consists of one or more renewable resources (solar, wind), base generation resources (diesel, hydro) and storage for either grid balancing or energy storage purposes. For a microgrid to function effectively, a real time controller system is needed to manage the elements of the microgrid, including a connection to the grid in the future. Significant loads should also be included to aid with the balancing of supply and demand in real time. Microgrid control systems can be centralised or decentralised. Decentralised control systems bring the advantage that a failure of a single element will not necessarily stop the grid from operating. Adding of new microgrid components can be achieved by adding additional controllers that will integrate into the system, allowing for flexibility of applications. The real time control system is an important source of data for upstream functionality and should collect and publish data that is needed for this functionality, such as condition monitoring data.

3 Fig 2- Elements of a Microgrid with distributed control Distributed energy resource management Looking at a wider view than a localised microgrid, distributed energy resource management systems (DERMS) enable the management of grids that are decentralised. This class of energy management is enabled by cloud, communications and IOT technologies. DERMSs are composed of hardware and software applications that enable utilities to reliably and safely operate the distribution system in the presence of high DER penetration. A DERMS analyses historical and real-time data that can help integrate, manage, and control flexible and intermittent DERs and electric demand. The analysis and actionable intelligence derived from such systems are then applied in efforts to keep the transmission and distribution system in sync with an efficient and reliable supply and demand balance. In turn, this demand balance should ideally optimize power flows, electric demand, DERs, and traditional centralized generation.[1] Looking at Fig 1, DERMS covers the seconds to minutes to hours part of the time horizon. It brings the following functionality to DER management: Resource management DERMS provides registration, visualization and aggregation per market and grid area to build an overall picture of the connected DERs. From this, functions such as active power management, volt/var optimization, DER optimization and DER visualization can be implemented. Resource optimization With the integration of other sources of information, such as weather, and AI assistance, it becomes possible to build a forecast for demand and generation capability. This allows optimisation and dispatch of a DER portfolio in near-real time. Market participation

4 DERMS creates the ability to aggregate DER allowing operators to offer and settle energy and ancillary services in wholesale markets. Commercial settlement DERMS provides the records needed for confirmation that the services were delivered and that financial settlement can be made. The outcomes of a DERMS system include: Increase of network hosting capacity DERMS provides a non-wire alternative (NWA) to significantly increase network hosting capacity for DERs. This avoids the cost of additional power network infrastructure by optimising the use of an existing network. Network DER monitoring & control DERMS allow a DNO to gain insights to DER events and to monitor and control assets at the substation and along the feeder backbone Grid reliability and performance DERs can significantly alter a traditional load curve. A typical case is the duck effect, where the drop-off of PV resources before the evening peak gives rise to a much steeper increase in demand as the sun goes down. DERMS helps to maintain grid reliability and performance through prediction and management of the energy resources. A good place to implement a DERMS is in the SCADA advanced distribution management system (ADMS) environment. This allows the DERMS to access the network model already present in the ADMS, preventing the duplication of data engineering and avoiding potential conflicts that could arise from managing multiple network models. Important characteristics required for a successful DERMS include Scalability A distributed architecture, such as provided by a cloud solution, enables the computation of large number of DER assets on a distribution network. This gives high performance and scalability. Asset Agnostic A mix of DER assets such as batteries, smart solar inverters, capacitors and other controllable loads must be supported. This connectivity will be achieved by using an edge device at a DER where the controller does not support internet connection or cannot do so securely. Speed The real-time control and optimization of DER assets is dependent on the speed of network response, with performance improving as the speed is higher. Connectivity is improving all the time with continuing fibre network roll-outs and emerging 5G technology in the mobile space. Asset lifecycle management Moving on to the weeks, months and years part of the time horizon, digitalisation adds the functionality that is needed to collate the information and perform effective asset management of DER assets. The real-time operational and condition monitoring data collected from DER equipment can be used to manage the plants by automating and interlinking asset management, asset performance and workforce management functions in a connected cloud environment.

5 The ability to align a whole-life approach to the management of physical assets with business objectives is vital to success. As such, asset and maintenance managers are increasingly required to report on performance against key performance indicators (KPIs) such as asset utilization, risk, and return on assets (ROA). These metrics are critical to understanding the overall health of an asset-intensive organization and rely on a current and correct view of all underlying asset information. Today, many utilities approach asset health with an ad hoc mix of information from multiple sources, like timeand usage-based inspection data, alarms from remote sensors, and industrial enterprise systems. Often, this data is trapped in functional silos across the business and utilities rely heavily on human experts to manually review this data to identify trends and address the highest risks of failure across the asset portfolio. As more and more DER devices and systems are added to a power network, the scale can become overwhelming. A cloud-based asset performance management system can collect, analyse and interpret data from many sources. As the number of devices grows, cloud-based systems can be scaled to include a potentially large number of assets. The use of expert equipment models provides detailed analytics for all types of equipment in the DERs. Maintenance strategies over the life of a DER can be modified based on real information to fit the condition of the plant. This alleviates the need for each utility to have its own on-site experts to analyse the data and decide on the actions needed. Some of the benefits of deploying an asset health strategy to critical infrastructure include: Fewer catastrophic equipment failures Optimised operational costs Extend asset life and optimisation of asset replacement Reduction in unplanned outages Lower planned outage costs Increased safety Enhanced regulatory compliance and reporting Integrated systems can dispatch maintenance teams automatically to deal with issues as they arise. An issue identified by the asset performance management system (APM) can be passed through to the enterprise asset management system (EAM) to record the problem and create a work order to resolve it. This triggers the workforce management module (WFM) to task a maintenance team to repair the issue. Once the problem is resolved, the status of the asset is automatically updated, triggered by the report from the maintenance team after the corrective action has taken place. This minimises downtime and makes efficient use of limited resources.

6 Fig 3- Asset Lifecyle Management Conclusion Digitalisation offers many solutions for the challenges of managing a DER infrastructure. Turning intermittent energy resources into a manageable system, where demand and supply are both optimised automatically in real time enables the energy revolution to be realised. The integrated management of DERs from real time to long team provides the best information at every point in the lifecycle of DER plants. Advances in computation, storage and connectivity make this possible, allowing management of these plants with the remote input of experts adding an additional layer of support. Acknowledgement Material used to write this paper was supplied by ABB and is used with permission. References [1] Villali, J: " Distributed Energy Resource Management in the Modern Grid ", IDC, November Contact Stuart Michie, ABB South Africa, Tel (010) , stuart.michie@za.abb.com