Balancing act

inputs, including device status, weather, grid measurements, Machine learning algorithms monitor these changing market and market data. conditions set by local operators as another set of inputs. One valuable example of this is frequency regulation The hardware/software convergence on the grid. High power demand or down-ramp supply Hardware is an important element to support software from renewable energy can cause the shortage of electrical operations because the strength and integrity of the energy power supply on the grid, causing its frequency to decrease. storage battery can help the system last longer and handle Conversely, the opposite effects can cause the frequency to complicated and fast-changing priorities. Batteries working increase. Frequency volatilities can damage machinery, create alongside renewable energy plants or supporting the grid are challenges for getting energy to the load centres, and cause endlessly switching between collecting, storing, and delivering brownouts or blackouts. Grid operators rely on a tool called power as the needs of the grid and asset owner fluctuate. frequency regulation that enables energy storage to provide This process of fully charging and discharging a battery is the extra power and inertia needed to get the grid’s frequency referred to as battery cycling and is a delicate dance. Different back to a normal level. Energy storage systems are able to battery chemistries and devices have different operating monitor the electrical quality of the grid and detect frequency limits before they begin to degrade, including the number of anomalies in real-time, as well as respond to any deviations charge cycles a battery can handle in its lifetime, the number with fast powers in both directions to quickly bring the grid it can handle in a day, and the depth of discharge. Pushing the back into balance. battery beyond these limits can shorten the battery’s lifespan. A 22 MW energy storage project connected to wind While commissioning a project, system operators perform farms in Cremzow, Germany, helps balance the German grid endurance testing to ensure that the system can handle the network by providing frequency regulation services through changing priorities and workflows it is designed to undertake. applications including primary control reserve (PCR) and This complements the battery manufacturer’s own endurance reactive power. The Primärregelleistung (PRL) market in testing. Machine learning-enabled software factors these Germany offers the grid fast-acting energy reserves. Whenever nuanced battery limitations into its computations as a first Wärtsilä’s GEMS software platform detects a critical frequency input. anomaly or system imbalance at the Cremzow site, the

Once up and running, the software begins to optimise the software automatically triggers the battery system to dispatch system based on the device’s status and capacity. This also energy, delivering it within seconds. The main purpose of PCRs includes understanding the battery’s forecasted capacity. is to ensure the security of supply, and they are particularly For energy storage systems connected to renewable energy helpful in situations such as a power plant outage. Energy projects, the device’s capacity is largely a factor of weather, sources that participate in the PRL market must go through a since future sun and wind resources determine when the stringent qualification process and prove that they can provide battery will charge again. Once the algorithm understands the energy capacity in cases where other sources, such as variable amount of energy it is able to dispatch and when, the system renewable energy, need back-up. While PCRs act as back-up, can then consider other factors such as market signals. reactive power provides more local voltage support. Both applications require the battery to manage a state of charge An ear to the market in order to have capacity to offer. For example, software Grid operators are aware that they must implement measures can enable a contextual override to the batteries’ regular to keep the electrical grid sound if they are going to let more operations to ensure the system maintains the level of reserves renewable energy onto the network. Regions across the world it committed to in the PRL market. are developing many different types of incentives to activate A collaboration with Enel Green Power, ENERTRAG AG, energy storage and flexible energy generations for security Leclanché, and Wärtsilä, the Cremzow project and software and reliability in energy markets. These incentives and power platform also buys and sells energy on the 15 min. market, needs were once static and simple but are now becoming performing energy arbitrage. Energy arbitrage takes increasingly dynamic and subject to near-real-time changes. advantage of differing energy prices by storing energy until later when it is more valuable. It also helps avoid the issue of renewables curtailment, when wind or solar project operators are asked to scale back their output as renewables flood the system at the same time. Energy storage systems are undertaking Figure 2. Wärtsilä’s energy storage technology integrates with GEMS software to deliver powerful and reliable smarter things generation performance. under the umbrella

Figure 3. On the Caribbean island of Bonaire, Wärtsilä’s GEMS integrates and optimises a 6 MW energy storage solution with 13 wind turbines, providing island grid control.

of auto-bidding that are not only helping integrate more renewables but are also doing so in a way in which asset owners benefit from working together with grid operators.

Each region has varying types of market bidding incentives. In the US state of California, grid operators procure the majority of their power needs and services on the day-ahead market – which means energy storage batteries bid pricing a day ahead of when the energy is needed or available. In contrast, Australian grid dispatch operators procure the majority of their markets in the real-time markets that operate at 5 min. intervals, and these bids are placed for the whole week.

Improving the algorithm

The Caribbean island of Bonaire, part of the Netherlands Antilles, deployed a 6 MW energy storage project equipped with energy management software. The goal was to achieve extensive integration of renewable energy into the total electricity supply and a path to 100% renewable energy in the future. While microgrids on islands provide a simpler set of inputs in comparison to open markets in mainland areas such as Germany and California (US), this means they can also be constrained with less supply available given unexpected changes in customer energy demand. The Bonaire system was turned on in 2019 and has achieved significant wind energy usage improvement throughout the year.

The path to 100% renewables for Bonaire is an iterative process. The system leverages machine learning to better forecast load, based on historic data. It incorporates learnings from the system’s own experiences to better understand more nuanced and less predictable load changes. It then combines that knowledge with real-time data to come up with a forecast every 5 min. for the next 48 hr.

The Bonaire system has a very high accuracy for load forecasts over the next 12 hr and more than 90% accuracy for load forecasts the 12 hr after that. For the Bonaire system, machine learning and energy storage are hard at work, not necessarily focused on applications such as energy arbitrage for the best economics, but on how to best harness wind and solar energy output to avoid relying on thermal generation as back-up.

Customer-cited energy storage will play a key role as valuable grid assets to help manage the integration of renewables into the grid; however, energy storage projects must be able to manage the complexities of a more agile energy market through the use of smart, advanced computing technologies. The clean energy pioneers of yesterday were focused on steel, building wind turbines and solar panels and installing them across the globe. The energy pioneers of today are focused on software, integrating energy management and machine learning to make renewable energy security and reliability a present reality.

Sébastien Hita-Perona, General Manager ESS & Microgrids, Saft, France, explains how flexibility is an important factor for the energy storage system that the company is delivering for transmission grid operator RTE, as part of the RINGO project.

A30.8 MWh energy storage system (ESS) is under construction at the Bellac substation for the French transmission grid operator RTE. The site is one of three being established under the RINGO project, which will test large-scale batteries as a way to relieve congestion on the transmission grid.

Building greater flexibility

Managing peaks of generation capacity is becoming a major challenge for transmission grid operators during the energy transition. Society is moving away from centralised thermal power stations with a topdown flow of energy and towards renewable energy that is distributed around the grid.

Renewable generation plants are often located towards the edge of the power grid, where the wind and sun resources are rich but the grid is often ‘weak’ and has limited capacity to accommodate the full capacity of wind or solar farms. The traditional approach would be to invest in high voltage transmission lines and new or upgraded substations. However, this option is a costly way to manage peak periods that might last for just a few minutes.

Instead, RTE is exploring energy storage as a more flexible alternative.

A market-neutral approach

Normally, operators can manage peaks of production with peak shaving. In this mode, an ESS will store energy at times of peak production, when the market price is low. It will then release it later when demand has picked up and the price is high.

However, RTE is a regulated utility and has a mission for public service. Because of this, it may not interfere in competitive electricity markets by affecting the price or availability of energy.

Rather than simple peak shaving, RTE developed a new concept for RINGO, where energy storage systems at different sites around France will store and release energy simultaneously. This ensures variable renewables are used to their full potential – in other words, curtailment is avoided. It also overcomes possible bottlenecks in the transmission infrastructure, without affecting the net amount of power on the grid at any time.

At an early stage in the RINGO project, Saft provided RTE with advice on the possible functionalities of energy storage and their role on the grid. The goal was to help RTE evaluate an ESS solution that was advanced and forward-looking, while being technically and economically feasible.

Substations

Under the RINGO project, RTE has focused on three substations in areas of France that are rich in renewable energy. Due to its public service mission as the French transmission system operator, the company saw an opportunity to develop the country’s energy storage industry and appointed three French businesses or consortia to deliver the new storage facilities.