Thomas Kiessling, the CTO of Siemens Smart Infrastructure, provided in a keynote at the Enlit Europe event, held in Milan between 30th November to 2nd December 2021 his thoughts on how to prepare as an Energy Company for significant disruption  He outlined in twenty-odd minutes keynote his transformation list to enable this with “All of us will go through disruption and opportunity.”

When anyone argues from the start of their keynote: “that no one would dispute that the energy sector is ripe for disruption, we have to go through profound change.” Then further adding, “there is a need to transform the systems radically“, you indeed start paying attention.

Kiessling said the industry “has entered a much greater degree of uncertainty. And uncertainty needs entrepreneurs; it needs trial and error, and it needs system-scale innovation.”

Emerging from the recent CoP26 held in Glasgow between 31st October to 12th November 2021, the push towards a net-zero future is the reality ahead. “After COP26, no one would dispute that the energy sector is ripe for disruption. We have to go through profound change.”

The CoP26 outcome calls for a fundamental, profound system change within the energy system and the global need for the whole energy community to cope with this net-zero need.

Kiessling cited a recent report from Boston Consulting and the German Federation of Industry, recognizes that no sector today is set up correctly for the change that needs to happen and argues this German perspective reflects across the Globe. He cited a doubling of electricity demand in the next 20 to 25 years, with a requirement of a tripling of the supply of PV and Wind firstly. “Each makes up part of a massive “collective” challenge.”

Kiessling suggests we are entering “a period of uncertainty.” and his view is uncertainty calls for Entrepreneurs as much ahead within the energy system changes ahead will have high levels of “trial and error.”

He calls for a regulatory framework to encourage flexibility and innovation and, at the same time, to ensure that production (of Electricity) needs to be secure, resilient and the supply significantly increased.

Various “asides” are provided throughout this review.

* I have provided some “asides” to clarify or explain as well to help put a further context for a broader reading community, as the keynote was given to an audience of energy experts. Some additional examples were sought from Thomas Kiessling following this keynote to illustrate his points, it makes this review longer, but it brings added value.

There are parallels with other significant industrial disruptions

Kiessling drew parallels with other industrial areas that have gone through similar and significant disruptions, such as telecommunications, factory automation and even data centres, stating there is a lot to learn from these examples.

• My aside here is that those industries did go through massive disruption. Perhaps the power grid can be considered the most complex system humanity ever built, as all our energy consumption is directly linked to power consumption. Equally, the electrical power grid has only added increased complexity over time.
• Second aside here: A major part of the energy transition is it is moving from a traditional vertically integrated hierarchy into a new form of operating within a more open “smart, intelligent grid” to enable an instantaneous, on all-the-time, safe, two-way passage, of information and energy needs will become a real game-changer. We can learn from other significant disruptions, but the energy transition is, for many, the most complex, operationally and technically demanding.

As Thomas Kiessling rightly points out in this keynote, combining operational technology, managing (differently) the physical assets and underlying technology is the set of things we need to manage together.

Preparing the Energy Company- a transformation approach

The primary point of his keynote was “how to prepare as an Energy Company” for the challenges ahead where a seven-fold increase in renewables with still the number one objective of having the security of supply and resilience within the system being paramount.

The keynote provided seven needs for transitional change.

Today as we transform our power generation into renewables, we face ageing powerlines, struggling to add capacity, a lack of (real-time) awareness, difficulties in controlling the voltage, especially at the grid edge.

Kiessling used specific examples of the needs in Electricity and the Grid Edge to underline the changes needed to be undertaken.

Firstly today, the need is to apply cutting edge technology.

Transition need one: The security of supply, resilience, and automation

Point One: Kiessling points out we will see less inertia and less short circuit power in the networks. There will need to be more sophisticated fault detection algorithms. Kiessling points out the likely need is to change the network protection architecture of the network itself. For example, the overcurrent and distance protection might need to be substituted by differential protections. AI technology will help to do this.

The good news here suggested by Thomas Kiessling is that AI and Analytics are well on their way to help in this transformation to control and operate the network in a “real-time” fashion. This shift in managing the system’s demands becomes a major transiting challenge.

• As an aside here: Historically, for example, in the U.S. power grid, inertia from conventional fossil, nuclear, and hydropower generators was abundant—and thus taken for granted in the planning and operations of the system. But as the grid evolves with increasing penetrations of inverter-based resources—e.g., wind, solar photovoltaics, and battery storage—that do not inherently provide inertia, questions have emerged about the need for inertia and its role in the future grid. Understanding the role of inertia requires understanding the interplay of inertia and these other services, particularly primary frequency response, which is derived mainly from relatively slow-responding mechanical systems.

Point two made here was shifting from static monitoring to a more dynamic setup. The present static load flow calculation to operate the network needs different thinking. As rotating masses are progressively removed, it will require different approaches with renewables towards a more dynamic data-driven environment.

• Aside here– examples provided later by Thomas Kiessling on issues that support this point two:
  • Static load flow calculation will not detect wide-area power swings, which might cause tripping of circuit breakers.
  • Such power swings might increase when rotating masses are decommissioned from the network.
  • Dynamic Stability Supervision is needed, typically using Phasor measure units.
  • There are promising technologies to detect upcoming dangerous situations early in a world of volatility.

Kiessling liked this, in an interesting comparison, to “resembling a patient-monitoring system during heart surgery” – one that was dynamic, self-healing and would evolve into a “system of systems”. This monitoring system needs to understand the system’s metrics in a real-time fashion to understand if dangerous situations are coming over the network to respond to these.

Point three– the need for self-healing networks. Closed-loop switching to help isolate and restore network segments in fast fashions and apply a very different total fault metric to this.

The need comes to the point of a system of systems for semi-autonomous parts of the network, driven by renewables can then manage themselves and contribute to the overhaul resilience of the network, so it becomes a “resilient, decentralized and autonomous system”.

• Aside here: This is taking the smart grid as a System of Systems (SOS) which moves towards operation independence of the elements, the ability to manage within a network the autonomy of these elements, as well as have an evolutionary development to retire at any time without causing an impact to other parts of the system, provide for emergent behaviour to meet the demands for a clean, economical and efficient way by all in the system design and finally allow for geographic distribution to be highly dispersed and linked through information exchange channels.

These transitions will need industry cooperation to mature these technologies and set all the energy systems up for the planned and expected growth.

As pointed out in the keynote- we all need to learn how to deal with data, and this is a cultural change where the need for data scientists, data lakes and IT/OT need to come together in new, radically different ways.

Transition need 2: Digitalization and Data

The challenge is validating and enriching the data to make it useable.

One example provided here is how Smart Meters are now going beyond just billing, but a deeper verification for providing data that increases the awareness of the network of power consumption, specifically on the grid edge. This shift enables improved metrics, planning and operational management for capacity planning, better aggregation insights, forecasting potential, ultimately improving the industry’s capital efficiencies and allowing the prosumer to participate.

Aside: Siemens re-launched their meter data management software EnergyIP at the Enlit Europe event, where its focus has a higher level of user-centricity and supporting customers to get ready for future changes to the energy system.  Links to the PRESS RELEASE and MORE information, taken from the Siemens website

Transition need 3: Innovation and proactivity

The use of power electronics, inverter-based resources will inform and stabilize the grid and protect the infrastructure.

• Aside here: Invertor-based resources including wind, solar and storage can quickly detect frequency deviations and respond to system imbalances. These “fast-frequency responses” can provide response rates faster than traditional mechanical responses from conventional generators, thereby reducing the need for inertia.

One example offered within the keynote was operating, simulating and monitoring islands (actual physical islands) as rotation free, here Siemens has several larger-scale projects around the world.

The massive opportunities here is to system scale innovation and reinvention, yet there are three fundamental issues to tackle

1. Inverters from different manufacturers require generic inverter models enabling standardization across the industry to achieve a rotator free network.
2. Challenge two: In larger transmission scenarios the inverters are located at a larger distance and this increases the risk of more weakly damped oscillations. Therefore, we need accurate simulation models and algorithms and present challenge
3. The issue of time-varying eigen modes is a challenge to be addressed. As the generation changes between conventional and inverter-based (or renewable) generation from hour to hour, the oscillatory behaviour of your power system will change, this requires an operator support system that continuously analyses the dynamics and if needed, the power system needs to adjust on the fly to secure N-1 failure security

In conclusion, to get to a rotation, free network in most countries calls for a system scale innovation for the energy community to work together to resolve and scale these specific challenges.

Transition need 4: Dealing with Cooperation at all levels

For example, TSOs and DSOs must cooperate more to cope with volatile inputs from renewables

Offered following the keynote to explain this cooperation point Kiessling gave a concrete example of how such cooperation can help speed progress to carbon-free networks:

With less and less TSO control of conventional power plants and rotating masses, the TSO’s mission to secure grid balance will be harder to achieve. This is because the TSO has no direct control over RES at the distribution grid. That’s where DSO comes into play. The DSO can react to TSO control signals, effectively providing ancillary services by aggregating DER and DSR This allows operators to reduce TSO side issues like redispatch, which has increased dramatically in some countries in recent years

In one of Siemens research projects cooperating with multiple TSOs / DSOs, this work has verified this works using real network data of TSOs, and are now working on deploying this with a number of TSOs

• Aside: Having clear definitions of data to be exchanged, recognizing network development in demand and generation forecasts, establishing the ancillary services, load shedding, and capacity markets will all need greater collaboration. Exchanging planning information, coordinating technical studies to assess constraints on the system, dealing with congestion management, having common grid user understanding and free exchanges on available network capacity, all needs listening and collaborating more in the new system needs.

Transition need 5: Standardization and scalability

The keynote comes back to evolving into this vision of a system of systems. The system will resemble more of a system of systems, where energy nodes will take autonomous decisions that contribute to overall grid stability, only possible with standardization among nano, Micro, distribution and transport grids.

• Aside Standardization matters because larger power systems will have many grid-forming inverters from different vendors. There is a need to harmonize cyber security standards so as to ensure a common level of cyber security for the entire, interconnected energy system and Cooperation between TSO and DSO for ancillary services and transport grid balance requires interconnection standards.

Transition need 6: Regulations for flexible investment plans

As pointed out by Thomas Kiessling we need a regulatory environment that builds digitalization into incentive frameworks. To build on this

We need to simplify data collection across the industry already at the point of asset registration and there need to be energy data best practices that are embraced by operators

To speed innovation, regulators should give grid infrastructure stakeholders (including equipment manufacturers) access to past operational data so they can model solutions. At present, the network operators often have a hard time getting innovation investments approved by regulators, even as research projects with part of the issues coming from digitalization investment, by nature, will lead to a certain amount of innovative trial and error, as is the case of every innovation

Such an investment is in competition with simply adding hardware assets most of the time with a fixed rate of asset capital return. The regulator and the DSO understand this process much better. One way to evolve this logic is to start looking at business outcomes

What is the asset base needed to deliver a given amount of energy? Capital efficiency incentives need to be introduced into the discussion. The flexibility to deploy Opex or Capex needs to be increased.

Here lies a cultural and transformational problem, as regulators have been “engrained” to approve and measure in a certain way, to apply known metrics or handed down-regulation requirements to safeguard energy.

You have to start with “what do we dare in the industry?”, “what do we focus upon?” and how can all involved in the energy transition collaborate, learn and work together.

Aside: that would be unique but will be necessary for all stakeholders within the Energy system

Transition need 7: Consumer/prosumer focus

It is forecasted that Distributed Energy Resources will grow sevenfold by 2030. At a changing grid edge, data is (simply) not there, to prove that investment or change.

In a further follow-up, due to limits of time within the keynote, the points were offered by Kiessling in a set of challenges to be addressed.

Today’s reality: DSOs often don’t know if authorizing the next EV charging stations leads to voltage band violations. The DSO might also curtail solar production expecting overvoltage events

This is not based on data at the point of potential under or over voltage, since that data is rarely available today. There is then risk and leading to a perception in the industry that parts of the network could actually carry twice the load without a problem, but due to lack of data the generation & load balance is kept well below the actual capacity

How can this be changed and what help within the evolving grid edge provide a change that allows for the transformation to take shape?

So, what if you could estimate the status of LV lines based on a combination of real-time data available typically at the substation level, plus meter data, even if you get that meter only once a day or periodically

Siemens is working with DSOs on pilots to use neural networks to estimate if and where voltage issues arise both on load and on the DER supply side.  These methods achieve better transparency, enabling the DSO to curtail less, and authorize more new loads like EV chargers

This information, combined with peak shaving, load shifting, storage systems to smooth out supply and demand, will go a long way to accommodate new loads and prosumer systems.

Thomas Kiessling’s suggestion is in the application of Neural Networks- “Achieving more informed decisions”

The possible solution to make changes in the Grid Edge is to use substation data alongside offline smart meters. That data can be extrapolated to identify hotspots and load needs and becomes a Network Grid Edge.

This approach avoids having more sensors on every meter or connecting point to save time and expense. It can be pushed out over time and experience to connect into the final energy-consuming point.

• Aside here: A neural network is likely to be a series of algorithms that endeavours to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates or, in this case, the energy system. In this sense, neural networks refer to systems of neurons, either organic or artificial in nature. An artificial neuron receives a signal, then processes it and can signal neurons connected to it. The “signal” at a connection is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs. The connections are called edges. Neurons and edges typically have a weight that adjusts as learning proceeds. Source (partly Wikipedia)

Achieving more informed decisions

This proposal made by Thomas Kiessling can provide a more apparent determination of the grid edge’s state and provide the state of the LV network for more informed decisions and (more targeted) capital investment.

So here, innovation and creative thinking are being applied to solve a current problem holding back the needed Grid Edge shift to the intelligent use of consumption and demand data. Insights gained will improve the knowledge on the network without deployment at scale, of sensors to provide an assessment of data close to demand.

• Aside: For me, the idea of the concept suggested, Neural Networks offers the potential to bring about change, bring data, AI, technology into the equation to accelerate the Grid Edge was the most intriguing point.

So, in the conclusion of Thomas Kiessling’s Keynote.

We are in a disruptive phase; Kiessling provided in his keynote a transformation list of needs to follow, specifically working through issues and challenges both in the transmission, distribution and Grid Edge networks. He gave many rich examples that are already shifting Energy and Grid Edge design. These offered radically different ways to manage the demand and supply, reflecting the changing nature of power generation, distribution and grid edge supply.

Thomas Kiessling’s final comment was we do need to “wrap our minds around it” to undergo such a disruptive time of profound system change. It is how the energy community comes together and finds ways to imagine, collaborate to learn and share.

I found the keynote stimulating, thoughtful and informative.