For many industrial enterprises, reducing energy costs is a crucial goal in energy management. Where can I reduce energy costs? What options for optimisation exist? We spoke with Dr Stefan Kirschbaum, optimisation expert at the Society for the Promotion of Applied Computer Science (GFaI) about the opportunities and limitations of operational optimisation.
We wanted to get answers to the following questions:
- What is operational optimisation?
- How can companies optimise their energy systems?
- Optimisation for ensuring supply security – is it possible?
- Where does energy optimisation make the most sense?
- The more complex an energy system is, the more potential there is for optimisation. Why is that?
- What benefits are associated with energy optimisation in the real world?
Let’s take the opportunity to explain it in very simple terms.What is operational optimisation?
From my point of view, operational optimisation is about optimising the way in which an energy system operates. We are usually talking about power plants in this context, but an energy system can also involve cooling, heat generation, steam or compressed air. The objective of operational optimisation is keeping the costs of providing energy and operating the energy system as low as possible.
There are other goals that go beyond cost optimisation, of course. Companies can optimise other parameters, such as when they seek the lowest possible CO2 emissions or try to minimise the consumption of primary energy. However, the most common use case in our projects is when an enterprise seeks to optimise costs. Companies want to make the best use of their plants without further investment, and they also want to do this on a solid decision-making basis, not just on gut instinct.
With a bit of expertise, simple energy systems can also be controlled manually in a cost-efficient manner. Simple energy systems are systems in which energy can only be generated in a very specific way, for example. The company covers its load and can optimise very little due to the lack of any additional degrees of freedom. The situation is different when more complex energy systems are involved. Complex energy systems have degrees of freedom that allow key parameters to be adjusted. A simple example would be if I were to have two plants that can produce one form of energy. In this case, the capacity, operating costs and technical limits of operation would determine which one would be operated. It is necessary to take advantage of these degrees of freedom in order to minimise operating costs or, to put it another way, to maximise additional revenue from feeding into the grid.
How can companies optimise their energy systems?
As previously mentioned, most businesses try to optimise their energy costs. Energy systems are typically designed with redundancy. This makes it possible to perform maintenance work on one plant while the other is in use. It is redundancy that provides degrees of freedom. With the deregulation of the electricity market as well as new access to electricity trading options and a situation of fluctuating prices, it makes perfect sense to put plants into operation that would otherwise only serve a back-up role. An example of this would be capping load peaks through the use of emergency generators that are usually only kept in reserve for a power outage.
In our experience, most companies have degrees of freedom in their energy systems. It’s almost impossible to imagine a company designing its energy system so that demand could be met in only one way. As mentioned above, every enterprise needs to be prepared for an outage or for necessary service and maintenance. And another option that companies frequently put at their disposal is energy storage units. If a company already has energy storage units in use, this creates an additional degree of freedom. Energy storage units are usually controlled through charging and discharging strategies, such as filling the units up at night and using their energy during the day or another strategy that makes sense in the given circumstances.
What else can companies optimise?
Another application area is optimisation of the electricity purchasing of an industrial enterprise. Optimisation is a sound answer to questions about purchasing strategy. Do I buy my electricity using long-term forward contracts, on the day-ahead market or on the intraday market? There is a great deal of potential here to buy electricity cheaply or to sell it if my company generates a lot of electricity itself. If companies take their own energy system and its degrees of freedom into consideration, they can end up with even more, including in situations in which they trade electricity on the market.
And what about CO2 emissions?
In practice, CO2 emissions are rarely specified as an objective in operational optimisation. The company’s targets, such as emissions that are 20% less in a certain period, are achieved through investments.
ISO 50001 certification is a key topic in the context of optimisation for industrial enterprises. In each audit, companies need to demonstrate how they have improved their energy efficiency. Many companies have exhausted their potential in this area, or the possible measures to take are becoming increasingly expensive. By optimising operations and taking advantage of degrees of freedom, companies can further increase their energy efficiency and transparently demonstrate this in an audit.
In discussions with companies, I am hearing more and more that auditors are becoming stricter and insisting that any savings be backed up with verifiable proof. An example of an approach to operational optimisation in this context would be: We are now operating the storage unit in a completely different way. We have modified it as necessary, and more skilful operational planning allows us to now achieve greater energy efficiency compared to the baseline situation.
In addition to lower energy costs and CO2 emissions, the goal of improving supply security is becoming increasingly crucial for many companies as the renewable energy sector undergoes expansion. Can I as a company also optimise for security of supply?
Security of supply and operating costs are frequently issues that are in opposition to each other. Ensuring security of supply is an expensive proposition, while optimisation is about reducing costs. For many companies, security of supply is an issue that involves long-term investment planning. They have to ensure that the existing plants are sufficient. If there is ever an energy supply shortage, then covering the required load has the highest priority and the associated costs are of secondary importance. In contrast with this, optimising energy costs is an issue with both long-term and short-term implications.
When optimising operations, certain redundancy criteria always need to be met. For example, it is necessary to keep an additional boiler warm in case another one suddenly breaks down. This is necessary because after a boiler fails, a business simply cannot afford to wait several hours until another boiler is at operating temperature. Such requirements naturally influence the operating optimum. However, these requirements are not available as a degree of freedom and therefore cannot be used for the purpose of operational optimisation.
The company’s strategy for ensuring security of supply provides the framework for optimisation. In my opinion, the decision to do this is made for the long term, putting it on a different level than the decisions relating to operational optimisation of the energy system.
Where does energy optimisation make the most sense? In other words, how can a company figure out where its own potential for optimisation lies?
Optimisation requires that there is a degree of freedom in the energy system. In concrete terms, this means that several plants generating one form of energy and/or storage units are needed, along with the possibility to make purchases from different sources (variable tariffs, markets). This creates a choice (degree of freedom) between in-house production and external procurement.
It can also be described as the companies using degrees of freedom to create latitude for searching for the best solution for them. And they expect that some sort of improvement results from this process, of course, meaning that the difference between the results from one plant and that of another must be significant. If a company has two nearly identical boilers, it doesn’t really matter which one is operated. Things get interesting when one plant can generate both steam and electricity, while the other can only generate steam. You then see a significant difference in the costs associated with generation at one plant or the other. In a situation like this, it also makes sense to store energy so it can be shifted from one point in time to another in which the energy is worth either more or less. This becomes particularly interesting in the context of capacity pricing or in cases of atypical grid usage outside of high-load time windows. It is possible to leverage these differences in order to take advantage of great savings potential.
It is important to note that any potential for savings must exceed the organisational effort involved in operational optimisation. To name a simple case, there is either no or very little leverage involved in an energy supply with fixed electricity prices, for example. An energy system with more flexibility has significantly greater potential.
The more complex an energy system is, the more potential there is for optimisation. Why is that?
While this statement is true, the reason behind it might be different than you expect. I believe that the more complex an energy system is, the greater the probability that it is not already being operated optimally. With simple energy systems, how they need to be operated is often pretty obvious. If we compare a boiler and a combined heat and power unit (CHP) unit, we can say that both have certain marginal costs for the generation of heat. The marginal costs of the CHP are usually lower than those of the boiler, making operation of the CHP the less expensive alternative. Arriving at this answer is a trivial matter.
On the other hand, if a company has several storage units and additional plants, the related calculations can no longer be carried out using an Excel spreadsheet. There is a greater probability that they are not being operated optimally even if the plants are not necessarily being operated incorrectly.
Once a system reaches a certain level of complexity, it would be a wild coincidence if the storage units were being operated with precisely the right charging strategy. That’s because the more complex the energy system is, the harder it is to keep track of what an optimal operating state is. This is especially the case if the plants are distributed across a variety of different business areas, such as production, facility management and so on. In this situation, exchange of data and holistic optimisation often do not take place.
Is there potential that companies could still leverage by linking their data?
This is precisely what is possible. The organisational effort required is a bit higher, of course, especially when several business units are involved. However, the potential is certainly higher there under such circumstances.
What benefits are associated with energy optimisation in the real world?
We installed a solution for optimising operations of a medium-complexity energy system for a district heating supplier in Austria. The company had three large combined heat and power units, three boilers and a very large energy storage unit. The energy storage unit was what made it possible to bring about a great deal of leverage in this optimisation. There is also the option to purchase waste heat from a nearby cement plant. The company supplies some 1,300 customers with district heating. Under these conditions, we implemented a daily operational optimisation of the producer portfolio. (More information about the project)
The savings were able to be leveraged to such an extent that the project, including the software licenses, had paid for itself within just a few months.
Stefan Kirschbaum is product manager for the energy optimisation software TOP-Energy at the Society for the Promotion of Applied Computer Science (GFaI for short). After earning an initial degree in physics, Stefan Kirschbaum worked intensively on simulating and optimising industrial energy systems as well as implementing software in this environment as part of his doctorate programme in mechanical engineering at RWTH Aachen University.
At GFaI, Stefan Kirschbaum is responsible for further development of the TOP-Energy software package. He has worked on a wide range of industrial projects in the area of energy optimisation and is also the project director for several research projects.