The current LIPA infrastructure includes the ESB and supporting components to support extensive process automation. Future upgrades will include ongoing implementation of service-oriented architecture and complex event processing to enable further process automation and solutions based on the need to support specific and prioritized applications of DARM.
Some of the planned use cases will require automation and extensive computing power to perform many runs of studies. These runs will use a wide range and combinations of parameters to identify, for example, an optimum schedule for planned maintenance of transmission lines that will optimize the cost of labor for regular and overtime work, account for fluctuating energy pricing and eventual loss of revenue, and take into account risk and impact on system reliability and customer satisfaction performance goals.
In an approach similar to the current risk assessments of capital projects, LIPA is planning to develop risk models of individual circuits and system components. These risk models will take into account asset condition and predictive probabilistic performance of individual components of circuits and their components. The models will include, for example, status and maintenance history, performance of protection and communications systems, anticipated operating condition, asset design and performance data. This probabilistic risk assessment will be dynamically updated as changes in operating and asset performance are forecasted.
Other use cases will require real-time monitoring of operating parameters and will need to anticipate operating conditions and day-ahead (or even hours and minutes ahead) load-delivery requirements. One example of use cases would combine forecasted weather, load and expected reliability, and risk of failure of any number of critical assets to forecast and optimize load pocket must-run generation. This use case illustrates a risk optimization scenario with a potentially significant impact on system reliability, cost of system operation and impact on customer satisfaction, and will require adding solutions for complex event triggering and orchestration of multiple applications to LIPA’s infrastructure.
Probabilistic approaches use combinations of statistically possible values and provide better understanding of ranges of possible outcomes with related probabilities and confidence levels. Current deterministic processes and criteria are clumsy and obsolete. It is clear better probability-based risk models are needed. Such models will provide better understanding of risk associated with various and possible combinations of critical parameters, as well as overall risk of complex systems that have many independent and interrelated risks parameters.
To maximize benefits, risk optimization needs to be done simultaneously for key performance areas. For example, in the earlier described use case of optimizing day-ahead needs for must-run generation, probabilistic reliability of specific circuits and their specific individual components needs to be combined with probabilistic energy pricing for specific/probabilistic operating conditions and should include probabilistic assessment of impact on specific customers.
Conceptually, a multi-parameter optimization approach is applicable for both short-term operational decisions and longer-term capital investment decisions. Analysis of various possible combinations of individual parameters used in probabilistic studies is more likely to uncover high-risk operating scenarios that may not be identified with a deterministic
Predrag Vujovic (firstname.lastname@example.org) is the director of T&D planning at the Long Island Power Authority. Since joining LIPA in 2007, his responsibilities have included development and implementation of tools and methodologies for asset and risk management, risk-based capital projects selection and development of LIPA’s smart grid road map. In a prior position at EPRI, he managed research and development projects focused on integrated equipment monitoring and diagnostics, asset management and reliability-centered maintenance.
Mike Hervey (email@example.com) leads Navigant Consulting’s service offerings related to T&D business strategy and performance improvement. Throughout his career, he has been involved with multiple process improvement and organizational development initiatives. Most recently, he was COO and acting CEO of LIPA. He was integrally involved in the transition of LIPA’s T&D business to a new service provider under a public-private partnership model. Previously, he spent 18 years at Commonwealth Edison, working in T&D operations.