In our previous articles -one outlining how BESS installations work and the markets they operate in, and another covering grid services and energy trading – we explored the design of battery energy storage systems, their markets, and the platforms needed to manage these installations. This time, let’s look at a less visible part of the picture: data. At first glance, it seems straightforward. If a BESS has a specified power rating and energy capacity, and its control system displays the battery’s state of charge, we should know how much energy is still available. Well, not necessarily.

From the storage owner’s perspective, what matters most is not the energy capacity on the nameplate, but how much energy can actually be delivered to the grid over a given period, at what power level, and within warranty conditions. For the system operator, the question is whether that energy will be available exactly when needed. These two perspectives meet in the analysis of measurement, operational, historical, and market data. The quality of that data determines whether we use the BESS’s actual capabilities or merely manage a more or less accurate approximation of them.

Battery state of charge: A seemingly simple indicator

Let’s start with the best-known parameter: SoC (State of Charge). In simple terms, it expresses the battery’s charge level as a percentage of an assumed reference capacity. When the operator’s dashboard shows 60%, we intuitively read it like a car’s fuel gauge or a phone’s battery indicator: we still have 60% left. But the meaning is not quite as clear-cut. You cannot simply insert a probe into a battery and measure its remaining energy the way you measure the liquid level in a tank. In addition, for applications such as grid services, the actual amount of energy the system can absorb or deliver is much more useful (in MWh rather than as a percentage).

A typical BMS (Battery Management System) estimates SoC using voltage, current, and temperature measurements together with appropriate models. One method is coulomb counting, which integrates the current flowing into and out of the battery. It works reasonably well, but measurements have errors, and those errors can accumulate. Voltage-based correction also has limitations, particularly with today’s widely used lithium iron phosphate (LFP) cells. Their voltage curve is relatively flat across a broad charge range, making errors easy to introduce. A small voltage difference therefore does not always provide a clear answer about how much energy remains in a cell.

ACCURE, an independent battery analytics company, reports that its collected data shows state-of-charge estimation errors in LFP installations can reach approximately ±15%, and can be even greater in some cases. Physics-based models and advanced data analytics can reduce this error to below ±2%. However, this often involves a “BMS reset” procedure requiring a complete battery discharge and recharge cycle, which may not be feasible within the battery’s operating schedule.

SoC, SoH, and the energy actually available

Now for the next piece of the puzzle. The battery’s state of charge (SoC) does not tell us its available capacity. Cells age over time, and their ability to store energy changes. One indicator used to describe this is SoH (State of Health), which reflects the battery’s condition. The extent of this degradation is often addressed in the agreement with the supplier. Even if two modules display the same 60% SoC, they may not contain the same amount of energy. One may have a lower actual capacity, while another may be operating at an unfavorable temperature or have a power limit imposed by protective functions or an upcoming balancing cycle.

There are also system-wide constraints: the permitted SoC operating window, PCS conversion efficiency, auxiliary power for cooling and heating, transformer limits, and the availability of individual containers and modules. As a result, SoE (State of Energy), an estimate of the energy that can actually be delivered, increasingly appears alongside SoC. For energy trading, the key question is how many MWh the system can deliver to the point of interconnection, over what period, and at what power level – in other words, how much a trader can commit to the energy or balancing services market.

Of course, SoE is not a single, universal device reading. It must be calculated using the battery’s condition, efficiency, technical constraints, and current BESS operating schedule. The availability of a system prepared for a one-hour discharge will differ from that of an asset that must also maintain a reserve for balancing services, while staying within warranty limits on cycle counts and temperatures. That is why data on energy, power, and constraints should form a single, consistent asset model rather than reside in separate applications and spreadsheets. This availability is often defined in the warranty agreement using a formula such as:

Lost hours: (unplanned downtime + planned downtime + maintenance downtime + hours with external constraints)

A BESS management platform should monitor this value according to its contractual definition and provide reporting to support discussions with the supplier if availability measured using the formula differs substantially from the stated figure. These stated figures for actual availability – that is, annual operating time without technical constraints – often exceed 99%.

What are five percentage points worth in a BESS?

Suppose we have a BESS facility with a power rating of 100 MW and a reference energy capacity of 200 MWh. Assume the system displays 50% SoC, but an estimation error means the actual state of charge is five percentage points higher. For this example, we simplify the relationship between SoC and energy to a linear one, disregarding capacity variation and minimum SoC limits. The difference is then 200 MWh × 5% = 10 MWh of energy stored in the batteries.

That is not yet 10 MWh we can sell. If we assume 85% efficiency in transferring this additional energy from the batteries to the settlement metering point, about 8.5 MWh remains. At a hypothetical price of PLN 400/MWh, this represents gross sales of approximately PLN 3,400 in a single event. This is not profit, of course, but rather a missed opportunity: we have not included the cost of earlier charging, degradation costs, fees, market constraints, or whether an opportunity to sell at that price will arise at all. Still, it illustrates why reliable estimates of the asset’s capabilities are worth pursuing.

The situation also works in reverse. If the BMS overestimates SoC and we submit a market offer exceeding the system’s actual energy delivery capability, we risk missing the operating schedule, having to cover energy shortfalls, or incurring contractual penalties. A prudent operator will then build in a larger safety margin using another unit. The problem is that a wide margin protects against errors but may also leave part of a fully functional asset unused. Better data does not eliminate the battery’s physical constraints – it allows us to identify more precisely where those constraints actually lie.

Availability: is the BESS ready, or does it just report that it is?

SoC accuracy is one issue; the technical availability of the entire BESS facility is another. In an ACCURE study published in September 2026 covering more than 50 operating projects, the median availability reported by the installations – the middle value among all measured values – was 96.7%, while median availability measured by the components’ actual response to commands was 94.1%. The difference is 2.6 percentage points. These are results for the study sample and the methodology used, rather than a figure that can be assigned to any storage installation.

Why the discrepancy? A device may be visible on the communications network and have no active critical alarm, yet still fail to reach the requested power level or execute a command within the required time. We therefore need to distinguish “online” status from the ability to perform a specific task. Another question is whether an entire BESS facility is available when one container is offline but the others can still provide some services. There is no simple answer: we need to know how much power and energy are available, for how long, and under what conditions. In our GridConnect platform, we call this dispatch availability planning.

Likewise, at the operational level, collecting alarms and displaying them on a screen is not enough. We need to record command histories, equipment responses, deviations from schedules, power limits, downtime, and maintenance events. It helps if alarm management can be linked to an external service ticketing system. Better still, technicians should receive guidance on what to do based on previous faults of a similar type. Only this combined view allows us to determine whether lost availability stems from an equipment failure, a BMS protective function, a communications problem, or an inaccurate estimate of the installation’s capabilities.

From thousands of signals to one operator decision

As you can imagine, a large BESS facility has an enormous number of variables: cell temperatures and voltages, current measurements, module and container states, PCS parameters, energy meters, protection devices, HVAC systems, medium- and high-voltage equipment, and signals from the local SCADA system. Simply gathering this data in one place does not mean it can support better decisions. An architecture is needed to ensure appropriate data quality, timestamps, and links to specific devices.

The architecture of GridConnect, our modern BESS management platform, has three main areas. The first is the local layer – BMS, PCS, automation, SCADA, and an edge device – where measurements are acquired and critical control tasks are performed. The second is the operational EMS layer, which gives the operator a consistent view of one or more installations, event and availability records, and operating schedules. The third covers analytics and historical data, supporting estimates of capacity, efficiency, and technical condition, availability forecasts, and the delivery of reliable information to trading systems.

Table 1. From technical data to business decisions: An example allocation of BESS platform responsibilities.

Our GridConnect concept, explored at ConnectPoint during work on platforms for large storage installations, calls for precisely this separation of responsibilities. The equipment and integration layer includes local SCADA systems, edge devices, and protocols such as IEC 60870-5-104, MQTT, and OPC UA. At the center are the asset model, operational platform, and data exchange infrastructure. Above them sit a data lakehouse for historical records and integration with applications responsible for trading and optimization. This describes an architectural direction and use cases; it does not claim that every listed function has already been implemented in every such system.

In this architecture, we should not move safety functions or fast control from local controllers to database analytics simply because the database offers a more convenient computing environment. The supervisory platform can provide estimates and schedules, but local protection systems must retain their autonomy. Communications quality is just as important: missing signals, ambiguous timestamps, or a communications outage affecting one asset can quickly turn a good analytical model into one operating on an outdated view of the situation. These scenarios also require a plan.

Forecasting capabilities, not just recording events

It is time to move from current monitoring to the future. When providing services in the energy and balancing markets, knowing how much power a storage system has available at a given second is not enough. We also need to estimate how much will be available in an hour, tomorrow, and over the coming days, accounting for current SoC, planned cycles, temperatures, maintenance outages, and existing commitments. One use case considered in the GridConnect architecture materials is estimating dispatch availability over a longer horizon – a good example of how far today’s requirements extend beyond a simple screen of battery parameters. Given the structure of energy and balancing services markets, reliable estimates covering at least two days are essential.

This analysis involves at least two types of data. The first comes from the storage system itself and describes its technical constraints. The second comes from external sources: operator instructions, forecasts of operating conditions, and required reserves. Only by combining the two can we answer a practical question: can I offer 80 MW and 100 MWh for a specified period without conflicting with another commitment or a battery operating limit?

Comparing the schedule with actual performance is also important. If a trader planned a specific discharge profile but the facility delivered less energy, the difference alone explains little. We need a history of setpoints and actual values, the state of the assets at the time of the event, and the cause of the constraint. This information supports not only settlement of the storage system’s operation, but also improvements to subsequent estimates and verification of the parameters declared by equipment suppliers.

Interestingly, forecasting storage availability is more than an owner’s idea for more effective energy trading. In Poland, PSE also requires relevant data. For JGM scheduling units (storage scheduling units), the operator expects estimates of minimum and maximum power in both the generation and consumption directions (Pmax_gen_est, Pmin_gen_est, Pmax_pob_est, Pmin_pob_est), as well as the maximum energy the storage system can deliver to or draw from the grid (E_max_dysp_up and E_max_dysp_down). This distinction matters because a system may have sufficient power available at a given moment but be unable to sustain it for the entire scheduled period because of its current SoC, temperature, or technical constraints. BPKD-DB (Intraday) schedules have a 15-minute resolution, while BPKD-CR (Real-Time) schedules have a 5-minute resolution, so the forecast must refer to specific points in time rather than just the facility’s overall availability. In addition, key measurements and signals describing current JGM operation are transmitted to the LFC system every 1–2 seconds, allowing us to continuously verify estimates, detect deviations, and adjust subsequent forecasts.

Historical data, degradation, and operating costs

One more issue remains – an important one, although its consequences usually become visible only over time. Battery energy storage systems are assets that wear out with use. Every charge and discharge cycle has consequences that depend on factors such as depth of discharge, temperature, operating power, and cell chemistry. To assess the profitability of future transactions reliably, we cannot consider only the purchase and sale prices of energy. Under the warranty, the supplier specifies how much battery capacity may decline in subsequent years, assuming proper operation by the user.

Historical data lets us track capacity loss, differences between modules, actual round-trip efficiency, the number and characteristics of cycles, and operating time under specific conditions. We can then attempt to estimate the asset wear cost associated with a particular operating strategy and compare it with additional revenue. We must, of course, avoid presenting such an estimate as a falsely precise figure: degradation depends on many factors, and models require periodic calibration and validation against measured data.

For example, two trading strategies may generate similar gross revenue, while one requires more frequent and deeper battery cycles. If our economic model includes only energy settlements, we will treat them as equivalent. Once we add efficiency, warranty conditions, and estimated wear costs, the result may look different. This is precisely where historical analytics, the service system, and operational planning should draw on the same reliable information base. We can determine the “actual cost per cycle.”

How can we make the most of every percent of BESS battery capacity? First, we need to measure it reliably

There is no single method that guarantees maximum utilization of every BESS. A battery storage system used for price arbitrage and balancing market services will operate differently from an installation maintaining reserves for the operator, or from a BESS behind the meter at a large industrial plant. In every case, however, the starting principle should be the same: move from data collected at the installation to a model of its actual capabilities, and only then to operational and business decisions.

If we do not know where our storage system’s technical capabilities end, we will either take excessive risks or continually maintain an expensive safety margin. This is perhaps the strongest argument for investing in a robust BESS data platform and analytics: it will not replace the cells, converters, or operator, but it will help us make much better use of what the investor has already paid for.

The post Every percentage point in a BESS matters. How can data help unlock the potential of energy storage systems? appeared first on ConnectPoint.

In the previous article in our series, we explained how such a system works. Now let’s take it a step further and look at how BESS can operate in today’s energy market and what roles it can play.

Battery systems are divided into front-of-the-meter (FTM) and behind-the-meter (BTM) systems, depending on where they are installed and the role they are intended to perform. The latter also include residential battery systems (from the operator’s perspective, they are behind the meter, forming part of the electrical installation on the owner’s side, for example that of a homeowner). The figure below helps explain the difference.

Figure 1. a) Front-of-the-meter (FTM) and b) behind-the-meter (BTM) BESS systems.

In industrial settings, BTM BESS systems are mainly used to:

• Maximise self-consumption from renewable energy sources (RES, if the home, plant, company or farm has such sources): When combined with a local photovoltaic installation, a BTM BESS stores surplus energy generated during the day or, for example, at weekends, rather than feeding it back into the grid at unfavourable market prices or simply not generating that energy at all. The stored energy is used when needed, for example in the evening or the following day.
• Reduce peak demand charges (peak shaving): This is one of the key roles in industry. A BTM BESS discharges during periods of the highest (peak) electricity consumption by a company or plant. This reduces the maximum power drawn from the grid (the BESS and the grid jointly supply the plant’s needs, so the amount drawn from the grid is reduced by the amount supplied by the BESS). This can reduce fixed distribution charges or simply keep consumption within the contracted capacity agreed with the distribution system operator, avoiding penalties.
• Manage electricity prices (energy arbitrage/load shifting, for companies that choose electricity purchase contracts with dynamic tariffs): The system charges the batteries when electricity from the grid is cheapest (e.g. during off-peak night-time tariffs or periods of market oversupply) and supplies energy to the facility when electricity prices rise sharply.
• Provide emergency power and business continuity: A BESS operates like an advanced, large-scale UPS system. In the event of an external grid failure, it protects the company against costly production downtime and damage to machinery.
• Compensate for reactive power: Modern BESS systems allow power quality to be controlled and can therefore act as a source or load with specified characteristics. For companies with a significant inductive component (e.g. a large number of electric drives) or capacitive component (e.g. data centres or large facilities), this function is important for reducing electricity costs.

These are only some of the potential applications, but they include the most important functions offered by behind-the-meter BESS systems. One of the latest trends is the use of BTM BESS at electric vehicle fast-charging stations. In this case, the main objectives are also usually peak shaving and the ability to charge several cars simultaneously at high power. Such charging does not take long, but the power demand is substantial. BESS can eliminate the need to sign a contract with the operator for the station’s full capacity or enable a station to be built at a location where the required peak power is not available at the connection point. The second argument is price management.

These characteristics make BESS increasingly attractive to many investors. According to the Energy Market Agency (ARE), the total energy storage capacity in Poland reached 8.85 GWh (equivalent to our largest power station in Bełchatów operating at full capacity for almost two hours). According to the agency’s data from August 2026, there are 114,418 electricity storage installations operating in Poland, most of them in prosumer systems (112,465 units). There are 1,948 industrial storage installations (medium-sized, with capacities of 0.05–10 MW) in Poland, which is a considerable number. However, their combined power and energy capacity suggest that these are relatively small installations. The data are presented in the table below.

Summary of the data is presented in the table below.

Table 1. Electricity storage installations in Poland (source: Energy Market Agency S.A.).

The five large energy storage systems mentioned in the ARE report are pumped-storage power stations (including the largest, at Żarnowiec, with 716 MW/3.6 GWh). The small number of BESS systems in this segment may seem surprising, but we should remember that 1 GW/4 GWh of BESS capacity is awaiting grid connection conditions, acceptance procedures and so on in 2026 alone. According to the National Energy and Climate Plan adopted by the Council of Ministers (a document prepared by the Ministry of Energy), Poland is expected to have approximately 6 GW of installed battery storage power capacity by 2030 under the ambitious WAM (With Additional Measures) scenario, presumably involving support mechanisms.

Let us now look at front-of-the-meter (FTM) systems, i.e. large BESS installations that should provide services and enable interaction with both the distribution and transmission systems. Unlike domestic or behind-the-meter BTM systems, FTM installations are not assigned to a specific electricity consumer or factory. Their purpose is to stabilise the electricity system as a whole and generate revenue from energy trading on a large scale.

There are also many operational possibilities here, but let us focus on the key ones:

• Market arbitrage: The storage system charges from the grid when electricity is cheap (e.g. at sunny midday periods thanks to photovoltaics or on windy nights thanks to wind turbines), when prices are attractive and may even be negative. It then feeds energy back into the grid during periods of highest demand (usually in the evening), when prices reach their highest levels.
• Participation in the Capacity Market: The storage owner receives a fixed payment from the grid operator simply for being ready to supply energy at critical moments (so-called stress events), when reserve capacity is needed.
• Provision of ancillary and frequency regulation services (the balancing services market): This is the most technically advanced role and often the most important revenue stream. The storage system responds to grid frequency fluctuations within fractions of a second (FCR and aFRR functions), stabilising grid parameters and preventing blackout-type failures (it is highly likely that the malfunctioning of such mechanisms, combined with several other operator errors, was at the root of the blackout in Spain in April 2025).

How do these operational opportunities work in the market? Market arbitrage seems fairly easy to understand, although from the perspective of control and revenue generation, it is by no means a simple mechanism. The electricity exchange operates in 15-minute intervals, so prices change very dynamically. In addition, every battery charging and discharging cycle brings us closer to the cycle limit specified in the warranty conditions. The number of cycles must therefore be managed sensibly. Making money from energy trading alone is a considerable challenge.

As for securing reserve capacity, this system in Poland is managed by Polskie Sieci Elektroenergetyczne (PSE), under the supervision of the President of the Energy Regulatory Office (URE). The main capacity auctions are held well in advance. In December 2025, the main auction for reserves for 2030 was concluded (Notice No. 1/2026 from the President of the Energy Regulatory Office regarding the announcement of the final results of the main auction for the 2030 delivery year).  Almost 6.9 GW of reserve capacity was contracted across 198 units, including 33 foreign units. The price was PLN 465.02/kW/year.

Supplementary auctions also take place during a given year. For example, an auction for 2027 is scheduled for September 2026. The cost of providing reserves is ultimately passed on to consumers through the so-called capacity charge (visible on electricity bills).

So, if we contracted an entire 100 MW BESS system in the auction for 2030, we would receive PLN 46,502,000 per year. Impressive! But we can no longer win that auction, and there are still more than three years until 2030. The final and, at the time of writing, most important “product” that can be offered on the market is frequency stabilisation services, known as balancing services. As this is a fairly complex mechanism and service, I will devote more attention to it.

Balancing services market

In our first article, we drew attention to the complexity of electricity systems and the need to balance them. The transmission system operator (in Poland, this is straightforward, as there is only one such operator, PSE) continuously monitors the situation, paying particular attention to two parameters: frequency and voltage in the system.

In the simplest terms, when electricity demand begins to rise and no new sources of supply become available, the frequency starts to fall. This can happen for many reasons: large consumers or many smaller consumers may connect to the system, one of the major loads may significantly increase its power consumption, or an important electricity producer may disconnect from the system (e.g. due to a failure or cloud cover over a large photovoltaic farm).

This sensitive mechanism also works in the opposite direction: if there is an oversupply of electricity generation in the system and insufficient demand, the frequency begins to rise.

The operator monitors this frequency very carefully. In Europe, we use 50 Hz, so the operator will respond if the frequency falls to 49.99 Hz or exceeds 50.01 Hz. The operator will use the full contracted capacity when the frequency falls below 49.8 Hz or rises above 50.2 Hz. In the context of this article and BESS services, voltage is not quite as important (locally, it indicates the reactive power balance and the condition of the transmission network).

How can the transmission system operator protect against system destabilisation? The answer is simple: reserves must be secured. This means guaranteeing reserve capacity for the provision of balancing services, rather than simply for electricity generation. It involves maintaining a dynamic balance in the system by securing reserves both “upwards” (having units ready to supply additional energy when there is a shortage) and “downwards” (the ability to reduce generation or use surplus energy for charging). This is not a cheap process. Every year, PSE spends more than PLN 2 billion on it. The operator specifies whether an upward or downward service is required and which particular service is needed. There are several such services: FCR, aFRR, mFRR and RR.

These stand for:

• Frequency Containment Reserve (FCR): Also known as primary frequency control.
• Automatic Frequency Restoration Reserve (aFRR): Also known as secondary frequency control.
• Directly activated manual Frequency Restoration Reserve (mFRRd): Also known as tertiary frequency control.
• Replacement Reserve (RR): Each of these services is provided separately in the upward and downward directions.

Their most important characteristics are summarised below.

Table 2. Characteristics of different balancing mechanisms.

As we can see, different balancing services must support the operator not only by providing contracted capacity but also by responding within a specified time.

Of course, the operator also purchases these services separately, for specific periods and with an indication of the upward or downward direction (except for FCR, which is a symmetrical service). Four-hour time slots are standard, although there is already discussion about moving towards the electricity market’s 15-minute intervals. Due to the technological limitations of other solutions, BESS systems have an important role to play here. They are fast enough to provide FCR and aFRR services (the remaining balancing services can be provided by conventional resources and renewable energy sources). They also allow energy to flow in both directions, enabling both upward and downward regulation.

Current prices for providing aFRR services are approximately PLN 180/MW/h for upward regulation and approximately PLN 140/MW/h for downward regulation. Therefore, if I win an auction to provide upward aFRR services for four hours, using a 100 MW BESS system, I can expect to receive PLN 56,000. This applies regardless of whether the operator actually uses that capacity, because the operator has reserved it. This is known as a “capacity” service, securing balancing capacity. If the operator uses this capacity, as the service provider I will issue another invoice, this time for the energy itself. I must obtain the price for that energy on the balancing energy market, where I am required to submit an offer for the contracted capacity that I previously secured. I have become (or rather, my BESS system has become, and has been assigned the relevant identifier) a Balancing Service Provider (DUB).

Of course, entering this market is not easy. I must complete a complex qualification process, integrate with the operator’s systems and meet other requirements.

How does the balancing services market work?

How does this market work in practice? Let’s start by explaining who a DUB is. According to the definition on the PSE website: “A Balancing Service Provider (DUB) is an electricity market participant that supplies balancing energy and maintains balancing capacity for the Transmission System Operator.” If we are a DUB, we can therefore participate in auctions for providing balancing services to the transmission system operator (PSE), offering our available capacity as capacity reserved for balancing services. The market itself operates through auctions. PSE holds auctions on its balancing services platform, separately for “capacity”, meaning the reservation of capacity itself, and for the energy that may be needed if the operator decides to use it. Once I have qualified as a DUB, I can submit an offer on the capacity market for a specific time slot (at least one hour), a specific balancing unit (one of my BESS systems that has already received its identifier as a DUB) and a specified rate per reserved MW/h.

The operator forecasts its requirements for balancing services and selects the most advantageous offers.

Below is a graphical example of an auction result, followed by an explanation.

Figure 2. Example of the outcome of an auction for balancing services.

In our example, four bidders participated in an auction for balancing services, including me as a BESS operator qualified as a DUB. The operator needs to reserve the balancing capacity indicated by the dashed line for upward aFRR services (more power in the system). Each auction participant (DUB) proposed a price per megawatt for each hour of available balancing capacity reserved during that time slot. The unit is therefore PLN/MW/h. The operator closed the auction. The offer from provider DUB 1 was successful. My offer, as a DUB, was somewhere in the middle of the price range, and provider DUB 3 also qualified. We will all receive an offer to reserve our declared capacity for the declared period at the rate offered by provider DUB 3 (pay-as-cleared). DUB 3 will receive an offer, but not for the full capacity it offered, as this is not necessary. Bidder DUB 4 will earn nothing today for capacity reservation alone because its price was too high. However, if I have won the auction (as in our example), I must reserve that capacity for the required service during the specified time slot and be ready to provide the service. The operator has the right to request it if the situation in the system requires it.

This means that I will have to submit an offer on the balancing energy market, specifying a price for each MWh. If the operator requests this capacity and I fail to fulfil my obligation (because I do not submit an energy offer or ultimately fail to deliver the energy for another reason), penalties will be imposed. To summarise this rather complex mechanism: I participate in an auction to secure capacity (a “capacity” reservation priced in PLN/MW/h). If my offer is among the successful bids, I receive the capacity reservation rate at which the auction cleared. I must then submit an offer for the balancing energy itself (if it is ultimately needed, priced in PLN/MWh delivered), at a rate that I determine myself. The operator will again close the auction, selecting the final accepted offer in that auction and settling all bidders at that rate. I can therefore use my price per MWh to influence the likelihood of my offer actually being activated and, for example, limit the number of charging and discharging cycles of my system.

Once I have won a capacity auction and there is a need to use my energy at the proposed price per MWh, it is better to fulfil the obligation partially than not at all (for example, because of technical difficulties, which will also need to be explained). Even if I am forced to provide the service using another resource I own, rather than the one specified in my offer, I will have to explain this. In the case of mFRR and RR services, conventional generating units and renewable energy sources usually offer prices attractive enough that competing with BESS systems in these markets currently makes little sense.

As the number of distributed energy sources grows, so does the need to digitalise energy systems. The BESS battery system itself requires access to large amounts of real-time data and an intelligent operational platform that not only supports submitting different offers in different markets (energy and balancing markets) but also enables forecasting of the power and availability of my installation for different services in the future. A good BESS management platform (often referred to as an Energy Management System, or EMS) will also support the use of technological innovations such as advanced reporting, availability estimation, automatic execution of operating schedules, predictive maintenance management and artificial intelligence. It is also necessary to build an infrastructure capable of handling huge volumes of data, including historical information on energy consumption, the number of cycles and the condition of battery cells, in order to make more accurate forecasts of installation availability and monitor compliance with warranty conditions.

The post Grid services, peak shaving and energy trading: how BESS energy storage systems operate in the modern market appeared first on ConnectPoint.

For decades, the power system operated in a relatively straightforward way. On one side were utility-scale electricity generators – power plants and combined heat and power plants of various types and sizes – and on the other were consumers, also of various types, from large industrial plants through medium-sized industry and large commercial, office and hotel facilities to individual consumers and households. Most power plants and CHP plants were conventional facilities, powered by energy generated through the combustion of fossil fuels. As long as CO2 emissions were not strictly monitored, fuel supplies at these plants were full. There were also no other significant technical barriers, so their output was very stable and predictable. The energy equation was simple: electricity generation met the immediate need for consumption – generation = consumption. One side of the energy equation generated and sold electricity in a stable and predictable manner, while the other consumed and purchased it somewhat less steadily, but still quite predictably. Generators and transmission system operators carried the full responsibility for ensuring stable system operation by maintaining the balance between supply and demand. Most of the time, this worked, although there were exceptions, although sometimes it did not, hence the “power supply restriction levels” known from older movies and publications, when generators were unable to keep up with the needs of large consumers and had to persuade them to reduce their demand. According to the Institute of Environmental Protection, in 1990 electricity generation in Poland came from:

• coal: approximately 76.8%,
• oil: 14.8%,
• natural gas: 8.9%,
• biofuels and renewable energy sources: 3.9%.

Figure 1. Balance in the historical power system – generation balances consumption. Figure generated using artificial intelligence.

Power system: changes have arrived

Today the situation is completely different, as can be seen from the profiles and types of electricity generators reported for August 2026 by the PSE portal. (Polish Power Grid Company portal – system data, viewed on August 26, 2026, rounded to one decimal place.)

• Coal, oil and gas combined: 42.4%
• Hydropower plants: 0.3%
• Onshore wind farms: 4.3%
• Offshore wind farms: 0.2%
• Photovoltaics: 52.8%

It is not only the generation profile that has changed. Consumer behavior has also changed significantly, with many consumers becoming local generators themselves – producer + consumer = prosumer – and energy now flowing in different directions rather than only from generators to consumers. The system has grown, the number of sources has increased, and their nature has become less stable. The behavior of wind and photovoltaic power plants can be forecast when good weather forecasts are available, but it is also obvious that photovoltaic installations will not generate electricity after sunset, while on bright, windless days wind farms cannot be relied upon. In this situation, maintaining the balance between supply and demand, and consequently ensuring stable system operation, becomes much more difficult.

Figure 2. A fragile balance in a complex energy market. Figure generated using artificial intelligence.

When trying to balance supply and demand in a market, a good storage facility can be extremely useful. If a farmer produces too many apples and has no immediate buyer, they look for a good warehouse where the apples can be stored until demand increases. This way, the farmer does not lose either the product or the money. When a customer decides they want apples, the apples are still available. Of course, storage comes at a cost.

The energy market works in a similar way. There are storage systems designed for electrical energy, and energy can be stored in many different ways:

• in potential energy, for example by lifting a large weight when there is excess energy and lowering it to generate energy when there is a shortage; often that weight is water, as in pumped-storage power plants,
• in kinetic energy, by accelerating a mass when there is excess energy and then recovering that energy by slowing it down; this is how kinetic energy storage systems, also known as flywheels, operate,
• in a certain sense, energy can also be stored by heating a material, although converting it back into electricity later is difficult,
• in the energy of chemical bonds, either in elements such as hydrogen and fuel cells, or, much more commonly, in components known as batteries.

This last mechanism is the most widespread. For years, we have stored electricity this way to start vehicles using batteries, although some of us may still remember manual starters in motorcycles and cars, as well as to power portable devices, from flashlights, calculators and radios to today’s smartphones, tablets, watches, headphones and portable speakers. Since around 2009, with the first generation Nissan Leaf, batteries have also been used to power electric vehicles, today covering almost every type of vehicle, from passenger cars and vans to buses, trucks and specialty vehicles. Batteries and accumulators vary and are based on different electrochemical processes and material technologies. Lead-acid batteries remain the most widespread and, in various forms, still dominate in applications such as cars. However, it is now widely understood that other technologies dominate portable devices and electric vehicles because of their much better energy-storage capacity relative to size and weight. These include NMC and LFP, while Na-ion and solid-state electrolyte technologies are increasingly being discussed. Over the past decade, batteries have significantly improved their technological parameters, including the number of charging cycles, thermal characteristics and availability in different forms and shapes. At the same time, their prices have steadily fallen, making them an attractive alternative for building large systems capable of operating together with power systems.

Figure 3. Energy storage systems supporting stability in a complex energy market. Figure generated using artificial intelligence.

It is not difficult to see how such an energy storage system can greatly support grid stability. Put simply, it can quickly absorb excess energy by charging, and when the system is short of energy, it can discharge it. In our example with the scales shown in the figure above, it acts as a kind of shock absorber, both for generators and consumers. As a result, operators and participants in the electricity market gain a new tool: a Battery Energy Storage System, or BESS.

What is BESS really?

As the name suggests, a BESS is a system, not a single device or even simply a collection of devices. There is no single market standard for the construction of a BESS, but these installations, often referred to as battery parks, have many common components. Depending on the design, these may differ in power, appearance, location and role. Let’s begin with the simplified arrangement shown in the figure below.

Figure 4. Simplified BESS park. Figure generated using artificial intelligence.

The main components of most BESS parks are containers. These usually contain battery modules installed in battery racks. The modules often resemble slide-in cartridges with electrical and communication terminals on the front panel. Inside are battery cell packs and a BMS, or Battery Management System, responsible for managing and protecting the local pack and communicating with the outside world. It is worth becoming familiar with this terminology, because the terms rack, module and cell are often confused or used interchangeably, which can lead to misunderstandings. Packs inside modules, as well as the modules themselves, are connected in series and in parallel to achieve the required output voltage and total current.

Figure 5. Container, rack, module and cell – terminology used in battery systems. Figure generated using artificial intelligence.

Batteries are components that store direct-current energy. A typical cylindrical household battery, just like a battery module, has clearly marked positive and negative terminals – direct current, or DC. The power grid, on the other hand, uses alternating current – a sinusoidally varying current, or AC. To connect the two, a device is needed to convert the positive-negative DC supply into a 50 Hz sine wave. This is the role of PCS, or Power Conversion Systems. During charging, such a power electronics converter draws energy from the three-phase AC grid and, operating as a controlled rectifier, uses it to charge the cells in the modules. When the battery is discharging, the process is reversed. The system draws direct current from the battery and converts it into alternating current while operating as an inverter. From a technical perspective, this is a four-quadrant power electronics converter. In modern converters, power quality on both the DC and AC sides is very high, and converter efficiency often exceeds 98%. Typically, a single PCS serves an entire group of battery modules.

The next step is to combine the energy from individual PCUs into larger groups and match the output voltages of the inverters to the voltage levels typically used in the power system in a given region. A typical PCU is therefore followed by a transformer, often with two primary windings to which between one and several PCUs are connected. The secondary sides of these transformers are connected to switchgear, often at medium voltage. This is an old but still commonly used term; in Poland, typical voltage levels are 15 kV and 20 kV. Depending on the system capacity, this transformer will be connected through switchgear to the local power grid or, in the case of large BESS parks, the voltage level will be increased once again using a high-voltage transformer. Naturally, measuring equipment and systems are present at many points throughout this complex installation, on both the DC and AC sides. There are also electricity meters between the park and the power grid for final settlement purposes.

Additional systems at the BESS park

The park is supplemented by several additional systems. A significant role in the park’s internal energy balance is played by the heating, ventilation and air conditioning system, or HVAC.

Batteries heat up during intensive operation, as every smartphone owner knows. As a result, battery modules require cooling on hot days. On the other hand, batteries cannot operate, particularly at full power, at very low temperatures and therefore require heating. These requirements are handled by the park’s HVAC system, which can reach an impressive scale and require substantial amounts of power. Safety systems are also required, covering both electrical safety, with numerous protection systems of different types at various points within the BESS park, and fire protection. Different manufacturers use different technologies, but installations include numerous sensors for smoke, fire and temperature, as well as fire suppression systems and fire barriers. Technical spacing is also maintained, both for internal logistics, since these are neither lightweight nor easy-to-transport components, and for safety reasons, as well as to provide easy access to key components within the park.

As can easily be imagined, such a facility generates enormous amounts of data: measurement data, communications data, information about equipment status and condition, and a very large number of electrical measurements. Managing such a complex system is a highly responsible and demanding task, which makes having a trusted partner particularly important. At the park level, management is handled by park controllers, which often perform the role of an EMS, or Energy Management System, which we discuss in a separate article.

A well-designed and properly managed BESS requires not only the right technology, but also a partner capable of combining electrical engineering, automation, data and IT systems into a single functioning ecosystem. At ConnectPoint, we deliver projects of a similar nature and, based on our international experience, we see enormous potential in the management of BESS systems.

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