Conference Agenda

As utilities strive to perform efficiently while maintaining compliance with fewer resources, the importance of a reliable SCADA system in today’s cyber security environment has increased dramatically over the last ten years. Major upgrades to these critical systems is driven by component obsolescence, evolving industry standards, demand for new features, and requirements for increases in system resiliency and cybersecurity. System upgrades often include improvements to programmable logic controllers (PLCs), SCADA HMI graphic systems, communication infrastructure, network and computer systems, and even facility improvements to construct secure server and control rooms.

Implementation of SCADA improvements in existing operating process systems not only requires careful planning, design, and significant investments in material, construction, software programming labor, and field testing, but also educating managers and elected officials. In today’s environment, additional challenges with long material lead time and price inflation add complexity to management of project budgets and schedules.

Clark Regional Wastewater District (Vancouver, Washington) used a multi-phase, multiple-year, programmatic approach to perform SCADA system upgrades at the Salmon Creek Wastewater Treatment Plant. The initial project replaced the plant’s obsolete PLCs with a new state-of-the-art Allen-Bradley ControlLogix platform. The second phase constructed network improvements, including replacement and reconfiguration of the plant’s aging fiber optic cable, construction of dedicated and secure server and control rooms, and implementation of new network and computer systems. A final project phase is replacing the plant’s existing SCADA graphics with a new Inductive Automation Ignition platform, including configuration of all new graphics. Each phase provided updated system documentation to support long-term O&M. The work required significant planning for scope development, budgetary approvals, and implementation phasing, but the outcome has been overwhelmingly successful. The utility is currently working on projects to upgrade SCADA systems at their other wastewater facilities to apply the approaches from their Salmon Creek Treatment Plant as a uniform standard.

As data volumes and reporting requirements increase, municipal wastewater utilities are faced with a rapidly changing technology landscape. A comprehensive data management master plan (DMMP) can provide strategic guidance for utilities grappling with core data topics such as governance, architecture, quality, security, integration, and analytics.

Development of a data management master plan can be a time-consuming process that delays integration of systems and delivery of business intelligence products. This presentation identifies practical approaches to efficiently developing a DMMP for utilities covering a broad spectrum of technology readiness levels. The key to selecting the right approach is to calibrate the process to match the utility’s needs and capacities.

A traditional structured process will typically feature identification of data sources, ownership, responsibilities, data maintenance workflows, quality requirements, and governance policies. This is followed by the design of a data architecture that ensures data integrity, security, and accessibility while meeting the end user’s analytical, reporting, and dissemination needs. The design should consider both existing and planned data repositories and associated software tools, and often features a platform evaluation component. Finally, a DMMP includes a roadmap for recommended data system improvements that provides sufficient time for procurement, development and testing and considers options for phased or incremental development focusing on priority reporting needs first. On the human side, the roadmap should include training, change management, introduction of field computing tools, streamlining of workflows, and stewardship.

Utilities seeking to accelerate the delivery of improvements to daily planning, operations, and reporting may consider a streamlined approach in which data system integration and analytical tool development proceeds concurrently with data management master planning. This approach is more tangible for system stakeholders as it focuses on the delivery of functioning data tools rather than the codification of abstract principles.

This iterative and collaborative approach is particularly suitable for utilities that have multiple core enterprise data silos but lack a comprehensive data analytics platform. By leveraging commercial off-the-shelf software and platforms, data from these enterprise sources can be transformed and stored in managed, curated, and reliable datasets. These datasets can then serve a wide array of downstream needs.