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Tareg Ghaoud Written by Tareg Ghaoud, View the best blog on utilities and design lead manufacturing that written by Tareg Ghaoud.
on 24 Sep 2020

Utilities today are becoming increasingly data-driven, focusing on solutions that utilize existing data sources such as Supervisory Control and Data Acquisition (SCADA), Geographic Information System (GIS), Advanced Distribution Management System (ADMS), Automatic Metering Infrastructure (AMI), Outage Management System (OMS), and Customer Information System (CIS), as well as data acquired from the installation of new Remote Terminal Units (RTUs) and sensors at secondary substations. The low-voltage (LV) network has traditionally been designed as a passive network to accommodate the maximum load or demand required by customers, considering the continuous rise in demand. For this reason, the LV network has been designed with minimum or no observability and controllability in place. The growing proliferation of Distributed Energy Resources (DERs) has changed the dynamics of the LV network. Bi-directional power flows and increased installation of EVs may cause voltage violations and overloads on the network. If the grid is not managed smartly, it will result in increased network losses and shorter life expectancy of the most critical assets, such as transformers.

Moreover, the increase of DERs in the distribution network places tremendous stress on tap changers, which are mechanical components that must work harder to regulate the voltage, thereby significantly reducing their life expectancy. Smart grid solutions help distribution grid operators manage these challenges to improve:

  • LV network visibility by installing smart meters and RTUs at secondary substations
  • LV network controllability by introducing Battery Energy Storage System (BESS) and Demand Response (DR)
  • Network efficiencies by implementing Volt-Var controls and optimization
  • Network resiliency and reliability by implementing technologies such as microgrids and Fault Location Isolation and Supply Restoration (FLISR)
  • Controllability and optimization of voltage profile in the LV and hence, lesser reliance on tap changers in primary substations by using smart inverter technology

The introduction of DERs will require emerging planning processes to be deployed along with the traditional planning processes that already exist. This will add new resources to the existing planning, thereby improving reliability and power quality, and reducing losses, voltage violations, and overloads. Examples of the emerging planning processes include hosting capacity estimation using peaks, time series, and probabilistic approaches. These new processes could be used to enhance the hosting capacity in the grid by simulating and testing smart grid solutions such as DR, BESS, Smart EV charging, and inverter control before deciding the traditional reinforcement on assets such as transformers, cables, use of capacitor banks, and voltage regulators.

To pick the best-fit solution to address their challenges, utilities need to improve their network visibility by using their data and advanced analytics to obtain insights on their network, which traditional systems such as SCADA do not offer. The value chain for our integrated approach to data connection, readiness, and DER planning is shown in the figure below:

Towards smart planning - Slide - 2[2]

Not all utilities, however, are ready with their rollout of smart meters. Hence, utilizing smart meter data to improve distribution network visibility and planning is still a challenge for many utilities. In such cases, an integrated planning solution to connect to the available data sources such as PI historian ADMS, SAP, etc., cleanses the data and prepares it for DER planning applications on the network. The solution is scalable, in that, once the smart meter data is obtained and ingested into the platform, utilities will be able to leverage the smart meter data to implement more advanced grid analytics on the network.

The solution’s basic architecture, which can be on-premise or cloud-based, is presented in the figure below:


Towards smart planning - Slide - 1[4]

Further, the solution is built across three stages:

1. Connection and data integration: This stage involves the connection of the solution to the available data sources. The aim is to ensure that the data ingested is of good quality, availability, effectiveness, and will represent the data source of truth for consequent data planning and analytics.

2. Data cleansing, preparation, and analytics: We process the time-series of the measured data from the historian system. Data is cleansed ( e.g., improving missing values, zero values, spikes, etc.) and prepared (e.g., finding the minimum and maximum of the load profile values for the past two to five years for secondary substations and associated feeders, removing effects of DERs on the load profiles to represent net load profiles, etc.) The result will be fed into further planning activities to study the impact of DER on medium-voltage (MV) and LV networks.

3. DER analytics: This phase performs power flow calculations based on the network topology and connectivity model to study the impact of DERs. Estimation of hosting capacity, DER connection assessments, grid stress using probabilistic approaches, and time-series network simulation can all be performed in the same integrated solution.

Towards smart planning - Slide - 3[2]

Our integrated data readiness and DER analytics solution offer utilities several benefits:

  • One-stop solution for data connection, integration, data cleansing, preparation, and network simulation.
  • Easy and flexible platform in comparison to legacy and custom-made tools, which may lead to loss of valuable time, effort, and flexibility in analyzing the data and carrying out advanced DER analytics.
  • Appropriate for utilities that have not progressed with their smart meter rollout. The same solution could be used in the future to integrate the smart meter data once rolled out so more advanced analytics and smart planning can be performed.
  • Efficient, effective, and easy-to-use planning tool to study and investigate the DERs effect on the network when compared to prevalent and traditional planning tools.
  • Cloud-based solution; hence, it could be offered as a SaaS model against a yearly/monthly subscription.
  • Designed to drive high customer and investor engagement.

Utilities will need to become more data-driven for better reliability, resiliency, and efficiency. MV and LV network planning will benefit from an integrated approach to data connection, cleansing, preparation, and data analytics when combined with DER planning and network simulation. With increased penetration of DERs in MV and LV networks, utilities are required to improve their planning processes with DERs. This integrated approach will drive more successful project delivery in terms of time, cost, quality, and utility satisfaction by having one implementation company responsible for delivering the complete solution—from data connection and data readiness to planning and network simulation. Our approach will also enable planners and other internal stakeholders to perform analytics on the existing MV and LV networks’ data. The same platform could be used to perform more advanced analytics with smart DER planning when smart meter data becomes available.

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