Predictive Software for Sustainable Hydro Power Generation

Predictive Software for Sustainable Hydro Power Generation

Moving to sustainable sources of energy to generate electrical power, as Europe has, requires a balancing act. Solar and wind generation provide an imbalance of power since they only operate when proper atmospheric conditions exist—i.e. sunlight or wind. Hydro generation provides a necessary balance, explained Pier-Vittorio Rebba, technology manager power generation for ABB.

But many hydro plants are aging. Management realizes the need to digitalize operations to obtain the best use of Asset Performance Management applications as well as best optimization of plant assets. ABB and its customer Enel Green Power partnered to digitalize operations delivering predictive maintenance solutions that will lower maintenance costs and transform the performance, reliability, and energy efficiency of its hydropower plants throughout Italy.

The three-year contract will enable 33 of Enel Green Power’s hydroelectric plants, comprised of about 100 units, to move from hours-based maintenance to predictive and condition-based maintenance, leveraging the ABB Ability Asset Performance Management solution. With operations in five continents, the Enel Group’s renewable business line, Enel Green Power, is a global leader in the green energy sector, with a managed capacity of more than 43 GW.

“We are privileged to be partnering with Enel Green Power, a digital pioneer, in their move from hours-based to predictive maintenance utilizing ABB Ability technologies for big data, machine learning and advanced analytics,” said Kevin Kosisko, Managing Director, Energy Industries, ABB. “Predictive maintenance and asset performance management must become a key component of plant operators’ strategies to optimize maintenance operations, minimize risk, improve resilience and reduce costs. The results are more competitive electricity rates, in a more sustainable way.”

Collaborating closely since early 2018, the two companies have jointly developed and tested predictive maintenance and advanced solutions (PresAGHO) via a pilot on five Enel plants in Italy and Spain, including Presenzano, a 1,000-megawatt plant near Naples.

The new contract includes digital software solutions and services that will provide analysis of over 190,000 signals and the deployment of about 800 digital asset models, aimed at improving plant operational performance, reducing unplanned failures and enabling more efficient planned maintenance practices through predictive maintenance. The integration is expected to yield savings in fleet maintenance costs and increase plant productivity.

The ABB Ability Collaborative Operations Center for power generation and water will help bring wider benefits of digitalization and engagement, supporting informed decision-making, real-time solutions and cost savings. The center already provides similar digital solutions and advanced applications for more than 700 power plants, water facilities and electric vehicle charging stations globally.

“With personnel retirements resulting in knowledge gaps and more competitive electricity marketplaces, we believe that many power generation customers globally can benefit from this kind of digital transformation around maintenance and operations,” said Mr Kosisko.

Predictive Software for Sustainable Hydro Power Generation

Yet Another View of Industry 4.0

A blog on the HP site by Christian Verstraete offers yet another opinion on Industry 4.0. However, he never really talks about Industry 4.0. Instead, he discusses the Internet of Things. Even though this is not “mainstream media,” it is still an example of sloppy thinking.

Beware of Industry 4.0 Misinformation

Verstraete first off confuses two terms. He never really touches on what Industry 4.0 is–including digital manufacturing, cyber physical systems, or, indeed, manufacturing. While making a couple of aside comments about manufacturing, he really only talks about the consumer side of the equation.

He links it directly to the Internet of Things–catering specifically to the usage of the internet of things in industries.

“Let’s start with the fact that companies increasingly cooperate in product development, across their supply chain and in their maintenance operations. Then, let’s look at where the Internet of Things can actually help enterprises deliver better products, cheaper and faster while maintaining or improving quality levels and services.”

He continues, “So, collecting market research as well as user data and then making it available to the developers would really help them defining the next generation product. But given market concerns about privacy, your data collection approach should be thought through very carefully.”

From a manufacturing point of view, this is one of the two promises of machine-to-machine (M2M) theory. An OEM, for example, could monitor its machine in the customer’s plant for both providing maintenance service and for collecting data on machine performance and component performance for the purpose of improving its product.

“An Industry 4.0 example would then be that you, as part of the product development process, desire user data, but you are not interested in the individual. You will need to demonstrate to customers that the information gathered is anonymous and there is no way for anybody receiving the information, legally or illegally to trace it back to the end-user.”

He misses an opportunity to inform his readers about the “industry” in Industry 4.0. Here he once again uses consumer point of view:

He then progresses to “maintenance operations.” I’m not sure if he is confusing maintenance and operations or simply referring to maintenance. But he misses a great opportunity to discuss the value of predictive maintenance or condition-based maintenance.

“Whether we talk about maintenance operations within the production environment or services to maintain equipment at the customer site, the problem remains the same. When is an intervention required? Typically we have two approaches. Either regular preventive maintenance (for example yearly) or maintenance triggered by usage (typical in the car industry), it always happens before the fact and does not take into account the actual status of the equipment.”

Let’s all press people to define terms and resist just mixing up all the terms and then running with a half-baked idea. There is the Internet of Things. There is Industry 4.0 (of which you have probably heard much). There is Smart Manufacturing (of which you have probably only heard of here–and you most likely won’t any longer because I have been removed from the formation group).

As the technologies evolve and engineers begin to implement, manufacturing efficiency and profitability should be experiencing a step change improvement.