Next Article in Journal
Optimal Sensor Placement for Contactless Medium- or High-Voltage Measurement
Previous Article in Journal
Performance Modulation of AB2-Type Ti-Mn-Based Alloys for Compact Solid-State Hydrogen Storage Tank
Previous Article in Special Issue
Optimal Allocation of Phasor Measurement Units Using Particle Swarm Optimization: An Electric Grid Planning Perspective
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Identification of Energy Storage in Distribution Channels

by
Joanna Alicja Dyczkowska
1,
Aleksandra Panek
2,* and
Norbert Chamier-Gliszczynski
1,*
1
Faculty of Economics Sciences, Koszalin University of Technology, 75-453 Koszalin, Poland
2
Faculty of Transport, Warsaw University of Technology, 00-661 Warsaw, Poland
*
Authors to whom correspondence should be addressed.
Energies 2025, 18(18), 4981; https://doi.org/10.3390/en18184981
Submission received: 5 August 2025 / Revised: 12 September 2025 / Accepted: 16 September 2025 / Published: 19 September 2025

Abstract

Energy storage facilities serve as flexible resources that comprehensively support grid operations; they are also essential, especially when the thermal power plants that previously served as regulators run out. Electricity is becoming the dominant carrier through which the bulk of consumers’ energy needs are met. The efficiency of long-distance transmission and the ease of conversion to other forms of energy in Poland are attributed to the national grid. Thanks to the development of new technologies and distribution channels, energy is changing its supply network system. The purpose of this article is to discuss the economic viability of energy storage systems and their strategic role in the energy transition. The research methods used are data analysis, and the dependence on capital expenditures ( C A P E X ) and operating costs ( O P E X ) of energy storage in distribution channels. Energy storage facilities operated by grid companies account for 90% of the installed capacity, but there is a noticeable increase in the number of prosumer installations, with an energy storage of up to 50 KWh at microinstallations.

1. Introduction

The global trend in electricity production in the world is related to the growing demand for energy. The main factors influencing the increase in electricity demand are demographic and economic. The European Union economy is showing a trend toward reduced energy consumption. The diversity of energy sources is related to their unique characteristics. Each source of electricity exhibits specific characteristics determined by technological and geographical conditions. The transformation of the energy system in Poland, in accordance with the Paris Agreement and the EU FiT-for-55 climate package, along with the sector coupling strategy, requires a rapid increase in the use of RESs in all sectors of final energy consumption. In Poland, 24 million tons of coal and 4.5 billion m3 of gas are burned annually for heating; individual households consume 12 million tons of coal with a demand of 850–950 PJ/year, with 150–200 PJ/year coming from industry. Meanwhile, both individual heating and district heating face changes related to the implementation of the goals of the Green Deal adopted in Europe, and the required reduction in CO2 emissions by 55% by 2050, as well as specific requirements for 2030, i.e., an increase in the share of renewable energy under the Buildings Directive and the RES Directive [1]. Recently, due to the operational limitations of wind and solar sources in the power system, thermal energy storage has gained increasing attention; electricity is increasingly considered in plans to stabilize power grids during periods of the oversupply of electricity generated by RESs (renewable energy sources). This type of approach has been recognized in the Polish Energy Networks (PEN) plan for grid development until 2034, where new tools for increasing the flexibility of the power system and limiting the scale of weather-dependent RES reductions through the integration of the electricity and heat sectors are being considered. Technologies for the coupling of the electricity and heat sectors, supported by thermal energy storage (TES) technologies, can therefore help in terms of further increasing the share of renewable energy, and increasing its use in district heating and industry. The purpose of this article is to discuss the economic viability of energy storage systems and their strategic role in the energy transition. The analysis considers available technologies and the implementation opportunities of energy storage in the various segments of the market until 2030. The main research question is to determine the extent to which energy storage systems are economically viable and what role they play in distribution channels during the energy transition. It is worth noting that there is a research gap, as no studies have been conducted in Poland to date that comprehensively address the aspects of energy and heat storage in distribution channels. So far, no one has conducted research on storage in distribution channels. Most of the work focuses on storage technology and does not comprehensively address the issue of storage in distribution channels. RES specialists deal with renewable energy storage (level three). There are also many publications on heat storage technology, i.e., level two.

2. Literature Review

2.1. Electricity Production

Obtaining energy from renewable sources has long been widely known and used, but the changes in this segment of the energy sector in Poland date back to the 1990s. Considering only installations using renewable energy sources of a small capacity (up to 5 MW), it should be mentioned that, in the period 1990–1996, their number in Poland increased by more than four times, and the amount of electricity sold to distribution companies increased by more than eight times [2]. The European Commission has unveiled a legislative package called “Fit for 55,” which is intended to amend or update EU legislation within the framework of climate and energy laws being issued. The “Fit for 55” package includes 13 legislative proposals, among which, in addition to CO2 allowances, an important area is increasing the share of renewable energy as part of an amendment to the Renewable Energy Directive. With the rising price of emission allowances, the dynamics of this process will be even greater. The managers of power companies face the dilemma of how to avoid losing out on unprofitable coal generation and, at the same time, insuring themselves from the system obligations of the inherently unstable energy generation of RESs [3,4,5]. Poland’s main challenge in developing a renewable-based electricity system lies in managing the variability in wind and solar energy. The volatility of energy generation from these sources is an inherent feature due to variable weather phenomena, the primary source of which is the sun. The European Commission has proposed raising the share of renewable energy to 40% by 2030 [6,7,8]. Uneven heating of the Earth’s surface by the sun’s rays results in winds that blow unevenly due to the variation in the heated surface [9,10,11]. EU directives on energy storage include a number of regulations aimed at developing and integrating energy storage facilities into the electricity system. An additional element of system change is to ensure the security and competitiveness of the energy market [12,13]. The observed trends in electricity generation globally and within the European Union (EU-27) show significant divergence. In the EU, one can see a clear shift towards clean electricity generation, which is associated with a noticeable decline in the role of nuclear power. The EU area is characterized by a dynamic development of renewable energy sources, which is associated with the growing priority of sustainable and green development [14,15,16,17,18]. The adopted target for change and the associated increase in the price of CO2 emission allowances, as well as the requirement to increase the share of RESs, is fundamental to the modernization of the heating sector and the technologies used in the transformation of the energy and heating industry. The first in this regard was Directive 2019/944, which establishes rules for the generation, transmission, distribution, storage, and supply of electricity. In addition, consumer protection provisions were included to create an integrated, competitive, flexible, and transparent energy market. All of this is reflected in several recent EU ETS directives, including RED III [19,20], EED, IED, and MCP [21,22,23,24]. Current patterns of energy production and use pose a serious threat to the global environment, especially with regard to greenhouse gas emissions, mainly CO2, and resulting climate change. As a result, industrialized countries are exploring a range of new policies and technological issues to make their future energy sustainable based on renewable sources [25,26,27]. In this transition, the responsible use of various renewable energy sources, including bioenergy, geothermal, hydropower, ocean energy, solar, and wind energy, and the adoption of energy storage technologies are crucial. These measures are necessary to ensure a clean, reliable, and competitively priced energy supply, as well as the sustainable management of the energy market. In addition, according to social and industrial development projections, the Energy Information Agency (EIA) forecasts a 25% increase in energy demand for Organization for Economic Cooperation and Development (OECD) countries and an 88% increase for non-OECD countries by 2040 [28].

2.2. Energy Storage

The challenges of energy storage have been discussed for decades. The first batteries were used as early as the early 1900s, and the first pumped storage energy storage was put into operation in 1920. However, it was not until the late 20th century, with the emergence of significant demand for the aforementioned applications, that energy storage technologies developed significantly [29,30]. Thermal energy storage (TES) is currently being presented as one of the most viable solutions for energy conservation and environmentally friendly behavior. Its potential applications have led to research and development activities and the development of various technologies [31]. Energy storage technologies provide several key benefits to the modern energy system, including increasing the share of renewable energy, improving energy efficiency, and improving economic viability. The NIS2 Directive imposes obligations on the energy sector—in this case, in Poland—on energy network operators as entities managing energy storage facilities, and in the area of cybersecurity and protection against incidents that may affect the continuity of the energy supply. Directive 2019/944 of 5 June 2019 on the common rules for the internal market in electricity and amending Directive 2012/27/EU6 (hereinafter Directive 944) introduced a new, non-intuitive definition of energy storage in Article 2(59), which reads as follows: Energy storage means deferring, in the energy system, the final consumption of electricity from the time of its generation or converting it into another form of energy that allows it to be stored, storing such energy and then converting such energy back into electricity or using it in the form of another energy carrier [32,33,34]. EU Regulation 2023/1542, also known as the new battery directive, is a legal act aimed at increasing the competitiveness and sustainability of the European battery and energy storage market. The document covers portable batteries, batteries for electric vehicles [35,36,37], industrial batteries, and stationary energy storage systems. It introduces requirements for labeling, battery passports, battery management systems (BMSs), and producer responsibility for batteries, including energy storage devices. Currently, grid operators are using strategies such as backcasting (using historical data to predict economically beneficial deployment schedules) to apply energy storage [38].
Article 3(10k) of the Energy Law (hereinafter the EEU), as amended on 20 May 2021, effective as of 31 December 2022, defines energy storage as the conversion of electricity drawn from the electricity grid or generated by a generating unit connected to the electricity grid and cooperating with the grid into another form of energy, the storage of this energy, and its subsequent conversion back into electricity [39].
Section 59(a) defines energy storage as the deferral, in the electricity system, of the final consumption of electricity or the conversion of electricity drawn from the electricity grid or generated by a generating unit connected to the electricity grid and cooperating with the grid into another form of energy, the storage of this energy, and its subsequent conversion back into electricity [40].
It is therefore necessary to develop efficient energy storage (EES) solutions to meet the problem of matching locally available RESs and loads [41,42,43]. An important large-scale market for energy storage technology in the long term is balancing service markets, where investments would be financed through reserve substitution. However, energy storage could also offer services in other ancillary markets for fast reserve services and grid stability [44]. Grid energy storage systems that can alleviate the high loads and voltages resulting from the increase in decentralized renewable energy generation are not an economically viable alternative for grid reinforcement or innovative utilities, and have not reached market maturity [45]. The intermittent nature of most RESs leads to fluctuations in energy production, which must be dealt with appropriately through storage [46]. Repeated changes in the operation of fuel cells and electrolyzer components should be avoided in order to reduce the degradation of their performance, extend their service life, reduce the negative impact on the power grid [47], and reduce the distortion of the grid voltage [48]. Maintaining grid voltage in power systems at the stage of integration with RESs is an important measure [49]. The battery bank thus becomes useful as an immediate and daily energy buffer to smooth out the high-frequency variability of RESs [50]. EU directives on energy storage aim to create a stable and competitive energy market, increase the share of renewable energy sources, and ensure security and protection for consumers in EU countries, including Poland.

2.3. District Heating and Heat Storage

One alternative is heat storage. The benefits of thermal energy storage, however, may not be so obvious on the surface, as its effects are not immediate or are only noticeable under certain circumstances [51]. This fact increases the demand for energy storage in various forms, including heat, and creates opportunities to increase the share and assimilation of electricity from RESs as a result of electrification and the deep integration of the electricity sectors, as well as the share of the total distributed energy capacity [52], heat, and transport. Energy consumed by heating, ventilation, and air conditioning (HVAC) [53,54] systems in buildings accounts for a significant portion of global energy consumption in Europe. Thermal energy storage is considered a promising technology for improving the energy efficiency of these systems, and its integration into the building envelope can reduce energy demand. Many studies have looked at thermal energy storage applications in buildings, but few have considered their integration into the building. Functional and structural integration of thermal energy storage could promote these systems in the commercial and residential building sectors [55]. The thermal energy storage system (TES) [56] should be designed based on the heating and cooling needs of each specific case. Underground thermal energy storage (UTES) [57] is the most common choice for seasonal storage. In addition, stratified chilled water storage (SCW) [58] or warehouses with phase change materials (PCMs) [59] can be used as short-term storage systems to meet daily demand and peak loads. This article presents a qualitative economic evaluation of this concept [60].
The heating sector has enormous potential as a consumer of electricity and is an untapped buffer for surplus energy from RESs. Heat in the structure of gross final energy consumption in 2020 accounted for 53% (with 20% of electricity according to the Eurostat methodology), and this illustrates how much potential there is for combining sectors in Poland (Table 1).
The ongoing energy transition in Poland has begun to recognize the opportunities offered by thermal energy storage [61,62]. The above challenges mean that both district heating and individual heating are faced with increasing the share of RESs in final energy production [63]. In residential construction, solar thermal systems are used to heat domestic hot water, which provides a store of heat in the form of water. Research on these systems is directed at, among other things, increasing the efficiency of these systems [64,65], the control and management of individual solar systems in residential complexes [66], the selection of system control systems [67], the location of solar panels [68], the identification of the operating states of solar systems [69], and the operation of systems [70]. Another solution is the construction of photovoltaic panels, where efforts are being made to select operating parameters [71], the maintenance of panels [72], the increase in the energy efficiency of photovoltaic panels [73], and research in the area of pro-consumer applications [74].
The recorded increase in the number of installed prosumer installations, and the construction of new wind farms and large photovoltaic installations (farms) will continue the upward trend in the coming years, which, in view of underinvested distribution networks and for balance reasons (the output of weather-dependent RESs at certain times exceeds demand), will cause periodic production constraints. This can already be clearly observed from the second quarter of 2023. Taking full advantage of the benefits of storage technologies and smart grids [75] requires the establishment of energy storage as a new asset class with an appropriate set of regulatory and financial policies to support its development [76]. At this stage, an important activity is the design and implementation of integrated energy storage systems [77].
TES technologies are classified into three main types: latent heat storage, sensible heat storage, and thermochemical heat storage. The THS method, which can be integrated with three TES technologies, stores both cold and hot heat transfer fluids (HTFs) and TES media in the same tank [78].

3. Materials and Methods

According to a report by the analytical company InfoLink, Taipei City, Taiwan [79], the global energy storage market increased its capacity by 175.4 GWh in 2024, with over 90% of installations taking place in China, the Americas, and Europe. Forecasts for 2025 predict a further growth of 26.5%, which means an additional 221.9 GWh of storage capacity. In Europe, 19.1 GWh of new energy storage capacity was installed in 2024, representing a 12.4% increase compared to the previous year. Italy was the European leader, ahead of the United Kingdom and Germany, mainly thanks to front-of-the-meter energy storage systems. In Poland, the energy storage market is currently developing. According to a report by the ERO from May 2024, there are 12 energy storage facilities with a capacity of at least 50 kW operating in the country. Planned regulatory changes from 2025 aim to facilitate investment in energy storage facilities, which may contribute to the dynamic development of this sector in Poland. An example of intensively developed electricity storage facilities is Denmark, in the context of increasing the share of RESs in the energy mix. Companies such as Eurowind Energy and BOS Power are building large-capacity energy storage facilities and integrating them with wind and solar power plants, e.g., in GreenLab Skive. Energy storage projects are being developed in cities such as Copenhagen, where a system capable of powering 60 households for 24 h has been installed. These investments are aimed at stabilizing the grid, making more efficient use of wind and solar energy, and improving Denmark’s energy independence. Sweden has launched the largest energy storage park in the Nordic countries. In addition to the Isbillen Power Reserve (93.9 MW/93.9 MWh), Neoen’s Swedish assets also include the 57 MW Storbrännkullen wind farm, the aforementioned Storen Power Reserve energy storage facility (52 MW/52 MWh), and the Hultsfred solar park (100 MWp). All are currently under construction. Norway is pursuing a policy of energy storage in pumped storage hydroelectric power plants and is also exploring new technologies, including underwater storage facilities (USFs).
According to data from Polish Power Grid, Poland’s electricity production in 2024 was 166,990 GWh, which was 2.05% higher than the previous year. Domestic consumption was 0.86% higher y-o-y, and amounted to 168,956 GWh (Figure 1).
The energy demand process can be analyzed as a process in which each selected time interval, such as an hour or a day, is assigned the amount of energy consumed by consumers during that interval. The analysis assumes monthly and annual demand. The specific nature of the power system, caused by the inability to store energy on an industrial scale, requires that the energy consumed by consumers and the energy sold by the supplier, or obtained by the supplier from internal and external sources, be balanced at all times. Therefore, we can more generally define the process of energy demand as the process of loading the power grid. Electricity is produced primarily at utility power plants. In 2024, the volume of production at these facilities amounted to 124,781 GWh, which accounted for almost 75% of the total output. The rest was accounted for by wind power plants and other renewable energy sources (42,208 GWh). The EU has called for the installation of smart meters in 80% of households by 2020, and most member states have introduced smart electricity metering [80,81,82]. In many European countries, smart meter initiatives form a key component of national energy policies. These policies are not designed solely to facilitate balancing supply and demand on the electricity grid; rather, these policies serve to support other sustainable energy or climate change policies [83]. First, the potential for heat storage of surplus RES energy in the prosumer sector was observed as a result of the “My Current” program starting in 2022, and then in district heating in the “RES-Renewable Energy Source for District Heating” program (2024). Heat storage installations in district heating and multi-family housing have already appeared in 2021 in the KPO and in the “District Heating of the Future” program (2021).
The energy demand of consumers in a regional system—in this case, Poland—is obviously a stochastic process. The basic tools used in this field are data analysis models, deductive models such as linear regression and ARIMA models, and inductive models such as neural networks or fuzzy neural models. The problem of annual variability is usually solved by adding a seasonal input variable (or variables) encoding the month for which the forecast is made. In addition, information on loads from the same day, with a one-week delay, is provided at the input. In summary, information on historical (delayed) energy demand values from selected periods constitutes the basic data for preparing short-term forecasts of daily network loads. The relationships between the input variables and the model output are strongly linear in this case. Therefore, if the forecast is based solely on historical network load values, it is recommended to use deductive methods based on linear regression analysis models. In the analyses, one can observe the identification of the potential for the development of 200–400 L of storage in the face of the development of prosumerism (limitations of prosumer sources) and the electrification of heating (dynamic tariffs for households). The problem of more frequent shutdowns of prosumer PV sources and the benefits of daily and weekend heat storage have been taken into account. Storage facilities of 1–10,000 L in the tertiary sector (commercial) and housing cooperatives, as well as phase-change storage facilities (compactness and stabilization of heat-take temperature), were also considered. A key aspect of this study is the role of heat storage in district heating systems. According to the authors, this segment has the greatest potential for using heat storage with synergies in terms of the largest weather-dependent RES generation and heating demand. In particular, they analyzed the potential of seasonal natural heat storage (with a capacity of 30–200 thousand cubic meters) and steel storage (10–30 thousand cubic meters) to provide system services.
In Figure 2, the reversible energy storage device is not a source of energy, but rather a shift in time between the moment of energy use and the moment of energy generation, as well as a shift in space between the place where the electricity returns to the grid and the place where it was originally generated. Energy storage is playing an increasingly important role in the energy market, driven by factors such as ensuring energy security, the development of renewable energy sources, increasing the level of self-consumption of energy from microinstallations, and the need to optimize energy consumption.
The construction of energy storage facilities is an important element of the energy transition. It reduces the duration of power outages, improves the quality of the energy supplied, and has a positive impact on the cooperation between the distribution network and local renewable energy sources. Storage facilities are also intended to be an alternative to more expensive and time-consuming investments in the expansion of traditional power lines and substations.
Electricity distribution channels are systems and infrastructure that enable electricity to be delivered from power plants to end users. They include transmission networks, transformer stations, distribution networks, and substations, as well as energy meters. Energy storage facilities in these distribution channels are not included in previous analyses. Traditionally, there are three segments of the electricity market: generation, transmission, and distribution. In addition, there is the function of the national power system operator, which, in Poland, is performed by the PSE Operator Sp. z o.o., and, at the local level, separate divisions within distribution companies. The most profitable segment of the market, i.e., the transmission (distribution) of energy through power grids, constitutes a technical monopoly. This is due to the fact that it is practically unreasonable for different companies to build several parallel grids to supply end users. As a result, electricity distribution channels are inherently monopolized, which is not the case with liquid fuels, for example.
Two consistent models for the distribution network can be constructed to address monopolistic behavior: one state-owned and the other private. In the first model, the power grids of both distribution companies and PSEs remain state-owned. The state gains the ability to influence these entities both through tariffs and as the owner. In this way, by pursuing the strategic goal of moderate energy prices, it prevents market drainage by natural monopolists. The condition for success is the strong will of state structures and not succumbing to pressure from distribution companies that will want to force the state to allow their monopolistic behavior. Currently, this model is practically impossible to implement in Poland due to the privatization of selected distribution companies. The privatization of another distributor, the ENEA group, is also planned. If this situation were to remain unchanged, i.e., if the sector were to remain partly private and partly state-owned, there would be a risk of unequal treatment of these entities by the market regulator and inconsistent competition rules. In the private model, the electricity networks of local distributors are privatized. The network company PSE will also be privatized, with the State Treasury retaining the right to block strategic decisions by means of a “golden share” and to appoint the chairman of the supervisory board, whose “yes” vote is required to appoint members of the management board. If this solution is not compatible with EU law (due to the existence of the golden share), the PSE will not be privatized, and the state will secure its interests directly by exercising ownership supervision. In this model, market competitiveness is maintained primarily by a strong regulator who treats private distributors equally. In both models, the principle of third-party access (TPA) is consistently implemented, i.e., the end user chooses the energy producer and the transmission company is obliged to deliver the purchased energy to the consumer. The introduction of this principle is a prerequisite for price competition between energy producers.
At the beginning of 2024, the Energy Regulatory Office (ERO) monitored the websites of 191 entities with a Distribution System Operator (DSO) and Transmission System Operator (TSO) status. It can be seen that these are key entities in the power grid, performing different functions and complementing each other’s roles. The TSO manages the high-voltage transmission network, which transmits electricity over long distances from power plants to regional or local distribution networks. DSOs, on the other hand, manage low-voltage distribution networks that supply electricity to individual consumers. In Poland, these are often the same companies, whose departments perform different functions in energy systems. The review shows that the obligation to keep an electronic register of energy storage facilities was fulfilled by 54 operators (28% of all operators surveyed). Notably, 47 out of the 54 operators reported having no electricity storage facilities connected to their networks. In relation to operators for whom it was not possible to obtain information about the electronic register, requests were sent to provide information on the fulfillment of the obligation referred to in Article 43g(1) and (7) of the Energy Law by sending a link to the company’s website regarding the energy storage register. Table 2 presents the installed capacity of storage facilities connected to the TSO and DSO networks.
Monitoring carried out by the President of the ERO shows that energy storage facilities have been identified in the registers of the five largest DSOs and TSOs. These include 12 energy storage facilities with a total installed capacity of 1464.5 MW (Table 3).
The largest storage facilities in terms of installed capacity are pumped storage power plants, whose total installed capacity accounted for 85% of the total capacity of registered storage facilities. Half of the storage facilities use lithium-ion battery technology.
Building on these technological advancements, we now turn to the economic aspects of energy storage. The research methods used include data analysis, and the relationship between capital expenditure ( C A P E X ) and operating costs ( O P E X ) of energy storage facilities in distribution channels. An important feature of a given heat source is its dependence on capital expenditure ( C A P E X ) and operating costs ( O P E X ). Levelized cost of heat ( L C o H ) is a measure that enables reliable economic comparison of different energy sources, including renewable ones. It is based on an estimate of the average total cost of construction and operation of a facility over its entire lifetime. The L C o H indicator can be used to estimate the future cost of heat generated by a heating system supported by renewable energy sources over its life cycle, taking into account initial investment costs, operating and maintenance costs, and other financial factors. The greater the impact of operating costs on L C o H , the more difficult it is to predict its final value, which requires taking into account forecasts of variable energy prices. When we talk about establishing a hierarchy of sources, we mean selecting individual system components in such a way as to maximize the objective defined at the outset—reducing L C o H , meeting legal obligations, and reducing investment risk. The changing environment means that the economic model should be flexible and closely linked to a technological model of the heating plant that is open to changes and modifications (thanks to TRNSYS). The following assumptions regarding capital expenditure were made for the designed size of the installation. It was assumed that, after 2025, the ETS-2 system would be introduced, which will cover smaller heating plants, but L C o H is the minimum fixed price of heat sold during the investment life cycle at which the investment will achieve a return equal to the weighted average cost of capital, i.e., it will have a net present value (NPV) of 0. For the investment in question, the expected L C o H is PLN 448/MWh (PLN 124/GJ). This value is determined by approximately 1/3 by the initial capital expenditure ( C A P E X ). L C o H shows low sensitivity to changes in expected parameters, with the exception of financing costs, for which L C o H shows high flexibility (almost +2). If the elasticity of L C o H with respect to a given variable is X, this means that an increase/decrease in the value of the variable by 1% will not cause the predicted price of CO2 emission allowances in the analyzed period to exceed EUR 45/t. It was also assumed that the installation will start operating in 2025 and its expected lifetime is 25 years.
L C o H = t 1 25 C A P E X t + O P E X t ( 1 + r ) t t 1 25 P r o d u c t i o n t ( 1 + r ) t
where
  • r —weighted average cost of capital;
  • C A P E X t —capital expenditure incurred in year t .
The formula and calculation of C A P E X is as follows:
C A P E X = P P & E + C u r r e n t   D e p r e c i a t i o n
where
  • C A P E X —capital expenditures;
  • P P & E —change in property, plant, and equipment.
Capital expenditures are also used in calculating the free cash flow to equity (FCFE).
FCFE is the amount of cash available to equity shareholders.
The formula for FCFE is
F C F E = E P C E D · 1 D R C · ( 1 D R )
where
  • F C F E —free cash flow to equity;
  • E P —earnings per share;
  • C E —CapEx;
  • D —depreciation;
  • D R —debt ratio;
  • C —∆Net capital, which is a change in net working capital.
Or
F C F E = N I N C E C + N D D R
where
  • N I —net income;
  • N C E —net CapEx;
  • N D —new debt;
  • D R —debt repayment;
  • O P E X t —operating costs of the heating plant in year t .
Lines supplemented at the request of the EFO concerning current expenditures related to operation and maintenance, broken down into more detailed categories, are as follows:
-
Fuel and energy: The consumption of electricity purchased from the National Power System in individual time zones is entered by summing up the values for all devices operating in the energy generation range in individual time zones of the day. These values should be confirmed by calculations prepared by the electricity distributor and made available to the NCBR. It is filled in by entering the total for all devices operating in the energy generation range in individual time zones of the day for energy purchased from RESs. The price forecast is automatically retrieved from the energy operators’ database. Production should therefore be reduced by losses during transmission, storage, or efficiency in relation to fuel and energy consumption. This gives us the actual structure of heat demand coverage by all production installations.
-
Repairs: Quantities and purchase prices of various specific additives, materials, and substrates that are not included in repairs and maintenance. This gives us a category of direct costs that is not included in other calculations. They include price forecasts for the 20 most popular substrates used in RESs. Annual repair costs were proposed as a percentage of the initial expenditure on the fixed asset.
-
Maintenance and inspections: Annual maintenance and inspection costs were proposed as a percentage of the initial expenditure on the fixed asset.
-
Service and salary costs: Allows these costs to be entered in two ways (combined or separately). First, they should be supplemented with service costs expressed in their actual, real values. This approach is particularly applicable in the case of outsourced services, but not only. Second, service costs are calculated based on the number of hours allocated to servicing all devices per year (applied primarily to the settlement of full-time employees).
-
Overhead costs: The level of overhead costs is calculated automatically and amounts to 10% of fuel, energy, repair, and maintenance costs. The energy operator should also specify any specific costs for the proposed technologies that are not included elsewhere, as well as public expenditure on concessions, taxes, environmental charges, etc. The volume of production covered by CO2 emission allowances should be added. The operator enters specific expenses for the technology used, e.g., public obligations such as taxes, concessions, other environmental charges, etc.
-
Economic effect of energy sales to the energy system: This item refers to additional revenue from the sale of electricity generated (e.g., in a photovoltaic installation) that was not used in heat generation installations during the summer. Enter a positive value. Due to the fact that the main purpose of the analysis is heat generation and supply, a distribution key for the cost of heat generation has been defined to avoid subsidization (the share of heat in the total volume of electricity and heat generated). It is used to proportionally reduce the share of heat inputs that are exclusively involved in the generation of surplus electricity. The revenues obtained in this way will reduce the value of energy production costs.
P r o d u c t i o n t —heat energy production in year t (expressed in GJ or MWh).

4. Results

Based on the presented assumptions, the first energy distribution channel is defined (Figure 3).
The limitations of the traditional energy grid are becoming increasingly evident as we move away from stored fuels (coal, natural gas, oil, and nuclear energy) toward more robust, renewable, and efficient processes for connecting end users to energy services [84]. The distributed value chain [85] has created limitations in the systematic efficiency of the traditional network system. In contrast, intelligent network design enables greater efficiency by providing greater control over deliveries and immediate feedback on consumption, thereby reducing waste.
In 2024, pumping water in pumped storage power plants required 1.4 TWh of electricity, which is 1.1% of gross domestic consumption. These units produced 1 TWh, so the efficiency of these energy storage facilities was 71.3%. Figure 4 shows the share of capacity contracted by energy storage facilities as a result of main auctions for 2021–2028, and additional auctions for 2021–2025, broken down by pumped storage power plants and electrochemical accumulators, as well as the total percentage share of energy storage capacity in the contracted capacity for individual years, taking into account long-term contracts and average quarterly auction results.
The key factor determining the effective implementation of reversible warehouses is the possibility of discounting investments in these assets. It consists of the following interrelated factors (Figure 4).
The pricing principles applicable on the market and the legislative framework for the energy market in Poland are determined by the government. The number of cycles that can be carried out without a significant loss of parameters, and the availability to energy market participants of measurement infrastructure enabling the digital (secondary) aggregation of distributed generation resources, storage facilities, and demand management resources, depends on the market situation (the number of suppliers and consumers).
The dynamic development of storage facilities is linked to the functioning of the capacity market. The use of support, which in the case of winning an auction constitutes remuneration for readiness to provide services on the capacity market, currently appears to be a key incentive for the creation of storage facilities.
Under this program, 2676 applications for heat storage facilities were submitted, amounting to PLN 11,343,474. It is worth noting here that the number of applications in this edition concerning electricity was similar, and the number of subsidies granted was three times higher. Under the My Electricity 4.0 program alone, prosumer heat storage facilities with a total capacity of 323,040 dm3 were added in Poland. Figure 5 shows the energy and heat distribution channels in Poland.
In 2022, battery energy storage systems (BESSs) and heat storage systems accounted for 14% of grant applications under the “My Electricity” program for PV microinstallations. Between 2022 (third quarter) and 2024 (end of the first quarter), a total of 9156 energy storage systems were built, accounting for 12% of all prosumer installations built during that period. The prosumer market in the net-billing system (from the second quarter of 2022) and with the support of the “My Electricity” program, and from 1 July 2024, in the dynamic tariff system, represents an increasing potential for the development of domestic heat storage facilities.
The number of operating prosumer microinstallations exceeded 1.4 million; 99.4 percent of all microinstallations are photovoltaic panels. Mainly thanks to prosumers, with 0.82 kW of PV power per capita, Poland ranks fourth in the world, behind Australia, the Netherlands, and Germany, and third in terms of the number of prosumers (after Australia and Germany). Globally, photovoltaics account for 85.7% of prosumer installations. Other microinstallations include micro-wind turbines (11.1%) and supporting installations: battery storage (11%) and heat storage (6.3%). Figure 6 shows the increase in the capacity of prosumer microinstallations in Poland between 2019 and 2024.
The short period of operation of the new balancing market rules (the new Balancing Terms and Conditions entered into force on 14 June 2024) and the small number of operating storage facilities do not allow for an assessment of their overall significance for the functioning of the balancing market in Poland. However, it can be assumed that storage facilities will be crucial for the functioning of flexibility services [86,87]. The potential for storing electricity in the form of heat is growing due to the rapid increase in the share of electricity from weather-dependent RESs (negative energy prices and, unfortunately, the curtailment of zero-emission sources at peak generation times are becoming an unexpected standard). This potential is growing as a result of the liberalization of the electricity market in the EU. The introduction of multi-zone tariffs and dynamic (“time of use”) tariffs for electricity encourages “load shifting” and creates business models for short- and long-term (seasonal) energy storage.
The significant surplus of renewable energy generation over heating in the period from April to September, i.e., outside the heating season, represents enormous and growing potential for heat storage. The size of the domestic market is growing in line with the expected rapid development of RESs until 2030 (with limited flexibility of the energy system) and with sufficiently long-term investments in cogeneration (earlier investments in fossil fuels have resulted in excess heat that can be used in the summer).
The variability in renewable energy sources necessitates the stabilization of the power system with “traditional” energy sources, such as coal- or gas-fired power plants and nuclear power plants. Pumped storage power plants are also an important component in stabilizing the power system.
Based on the assumptions and simulation results, the average cost of heat production generated during the life cycle of the L C o H installation was estimated using the following equation: causes an increase/decrease in L C o H by x%. Low values of elasticity with respect to individual variables, in particular energy carrier prices, indicate that the designed system is highly resistant to changing market conditions. The average heat production cost L C o H and, for comparison, the average variable cost (AVC) and average fixed cost (AFC) of heat production in individual years are presented in Figure 7.
The modeling process utilized network load and temperature observations from all distribution companies. The training data included a three-year set of observations. The forecasting system was tested on a long, more than five-year data set. The data used covered all months of a given year. This was simplified from weekly to monthly periods, which may cause errors. Variable costs primarily include the purchase of fuel and electricity, as well as CO2 emission allowances, while fixed costs include all network operating costs. Depending on the relationship between changes in fuel and energy prices, CO2 emission allowance costs, and capital costs resulting from inflation, risks in the heating industry related to the choice of technology and access to subsidies may lead to adjustments in the technical assumptions of the planned heating plant. Opportunities to obtain subsidies may, for example, lead to a decision to increase the role of zero-emission capex sources. This, in turn, may inspire the purchase or lease of additional land located further away (2–3 km from the heating plant) to increase the share of solar collectors or toward the decision to build a photovoltaic or wind power plant. The results of economic analyses are difficult to separate from technical assumptions and vice versa.
The results are shown in Figure 8. Exponential extrapolation was used. A high R2 coefficient of model fit to the data was obtained. As a result, the following forecast for heat storage sales until 2030 was obtained. Based on the formula:
y = 1 E 80 e 0.0974 x ;                R 2 = 0.9343
In 2024, the share of electricity in heating (individual) was 17%, and in 2030 it may reach 41% (an increase of 24 percentage points), while in 2015–2023, this share increased by only 2 percentage points. The forecast for the demand for heat storage in residential buildings requires assumptions about the overall market growth rate and the rate of change in fuel types and heating methods in buildings (some segments generate greater demand for heat storage). As regards the growth rate of the market for small water heat storage systems, SPIUG data on sales of various storage tanks and buffers in years considered representative (2017–2022) were extrapolated.
The analysis was based on a household consuming approximately 5 MWh of electricity per year, of which 1363 kWh was energy needed to prepare hot water [88,89]. It was assumed that, in order to purchase and install the PV system and heat storage, the household took advantage of the current My Electricity 5.0 subsidy scheme, which allows for financing up to 50% of the cost of a given installation component with a non-repayable grant. Based on the above assumptions, the installation of a PV system in the 2–5 kWp range and a storage tank with a capacity of 100–1000 L (approx. 5–50 kWh) was considered.
At the end of 2024, 33.6 GW of renewable energy sources were installed, which represents an increase of 5.2 GW (+18.3%) compared to 2023. The capacity of photovoltaic installations increased by 4.4 GW (+26.3%) over the year, reaching 20.9 GW. The first photovoltaic installations began to appear in 2014, and their capacity at the end of 2015 was 0.1 GW. The most dynamic growth is in the capacity of prosumer photovoltaic installations [90,91]. Such installations were first reported in 2017 with a capacity of 0.1 GW, and by 2024, they already amounted to 12.1 GW. The capacity of wind power plants increased by 0.8 GW (+7.7%) over the year. Over the past 10 years, an increase of 5.6 GW (+112.6%) has been recorded. The development of renewable energy sources is mainly driven by investments in wind and photovoltaic energy [92].
The unit cost of PV installation was assumed to be PLN 5000/kW, and the unit cost of heat storage, including installation (Figure 9), was determined based on current offers for small heat storage facilities.
It was assumed that the current call for applications for the “My Electricity 5.0” program would be used, in particular the possible subsidies of up to 50% of eligible costs and up to a maximum of PLN 5000 in the case of heat storage. In addition, it was assumed that certain replacement costs would have to be incurred (in particular, for the replacement of the inverter in the 15th year of operation of the installation).
Based on these assumptions, the potential electricity cost savings from PV and heat storage investment were estimated, depending on the size of individual devices. On this basis, the rate of return on such investments was calculated. The minimum expected rate of return (cost of capital) was set at 9%.
The maximum daily absorption capacity of cheap energy from RESs at peak generation was estimated at 115 GWh for the whole country. This estimate is based on a forecast that, by 2030, Polish homes will have significantly larger hot water buffers (an increase in capacity from the current 200 L to 400 L), which will enable greater storage capacity for surplus energy over a longer period (the entire day from 2:00 p.m. to 10:00 a.m.).
The year 2023 turned out to be the best so far for the European prosumer home energy storage sector. Home batteries with a total capacity of 12.2 GWh were installed in Europe, which was almost twice as much as in 2022. The year 2024 was weaker in this respect: the capacity of home energy storage systems in the EU increased by 8.8 GWh during this period. New research must focus much more on the use of surplus energy from renewable sources. Changes in distribution channels are influencing the development of energy storage facilities at a time of paradigm shifts and a lack of new, established trends. Forecasting the demand for energy and heat storage in residential buildings requires assumptions about the overall market growth rate and the rate of change in fuel types and heating methods in buildings. The progressive trend presented in the studies is also justified by the proposals of the Polish government, which is introducing regulatory changes aimed at reducing barriers to the use of RESs, preferential conditions for the development of systems, and pressure to build both daily and seasonal energy storage facilities using various technologies, with the aim of fully integrating weather-dependent renewable energy sources.

5. Conclusions

The Polish power system is characterized by a large territorial extent, and is therefore highly dispersed. It is also divided in organizational and economic terms between numerous separate entities that use its components for production and commercial activities. Despite its organizational dispersion, the power system is closely integrated in terms of technology. The generation, transmission, and delivery of electricity to end users constitute a single, closely integrated production and distribution process. An analysis of three distribution channels with energy storage systems showed that the latter is the most promising due to subsidies and the development of home energy networks with renewable energy sources. The final choice of energy storage system depends on user demand, operating parameters, and expected functionality. Factors to be considered when selecting a solution include load characteristics or profiles, power sources and energy costs (grid connection conditions and local energy sources), expected availability of power and energy, available space and environmental conditions, legal requirements, safety of use, and financing. To support system balancing, energy storage technologies are being developed alongside renewable energy sources. Their growing importance is confirmed by the results of the Power Market auction held at the end of 2024. In Poland, energy storage facilities with a capacity of approx. 8 GWh and a total power of almost 2 GW were in operation in 2024. Of this, over 90% are pumped storage power plants. However, approx. 0.7 GWh are prosumer installations with a capacity of less than 50 kW. Due to the way they are financed from EU programs, the development of energy storage facilities in microinstallations will be the most popular option in distribution channels and will integrate energy storage facilities through the transformation of RESs with energy operators’ networks.
A key barrier to the widespread implementation of energy storage is its traditional role in conventional grid systems. Implemented as a one-dimensional measure to balance load and reduce peak demand, grid-connected and distributed storage systems limit their value to energy arbitrage: transferring energy produced during off-peak hours to times of high demand and high prices. This severely limits the full value of the services offered by different types of energy storage technologies. With the development of deregulated markets, there are significant opportunities to expand markets for a fuller and more efficient use of energy storage services in the grid. In Poland, legislation on energy storage is not yet fully developed and does not offer attractive business models for investors.
Energy and heat storage facilities in distribution channels in Poland are located on three levels, with the largest storage area on the first level, but most storage facilities are being built by prosumers. The analysis presents the importance of energy storage at various levels in distribution channels. The comprehensive analysis fills a gap in existing research and offers a new perspective on this issue. The dynamic development of renewable energy sources in Poland, especially photovoltaics and wind energy, has led to a significant increase in generation capacity, which the power system is unable to consume efficiently. Only 17% of microinstallations are equipped with energy storage facilities. RES limitations occur mainly in the summer half of the year and show the scale of energy waste produced from RESs, as well as indicate the urgent need to develop seasonal heat storage facilities capable of taking over summer PV generation surpluses for use during the heating season. Poland still lacks a strategy for energy and heat storage, despite the fact that work on this policy document has been ongoing for several years. Despite the absence of a single strategy document enabling energy operators to make decisions, the direction of change is clear and EU support programs are being launched. It is estimated that the long-term cost of modernizing the energy storage sector in Poland will require investments of PLN 13–14 billion by 2030.

Author Contributions

Conceptualization, J.A.D. and N.C.-G.; methodology, J.A.D. and N.C.-G.; software, J.A.D. and N.C.-G.; validation, N.C.-G., J.A.D., and A.P.; formal analysis, J.A.D., N.C.-G., and A.P.; investigation, J.A.D. and N.C.-G.; resources, J.A.D., A.P., and N.C.-G.; data curation, J.A.D.; writing—original draft preparation, J.A.D. and N.C.-G.; writing—review and editing, J.A.D., A.P., and N.C.-G.; visualization, J.A.D., N.C.-G., and A.P.; supervision, N.C.-G.; project administration, J.A.D., A.P., and N.C.-G.; funding acquisition, A.P. and J.A.D. All authors have read and agreed to the published version of the manuscript.

Funding

This paper was co-financed under the research grant of the Warsaw University of Technology supporting the scientific activity in the discipline of Civil Engineering, Geodesy and Transport.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analysis, or interpretation of the data; in writing the manuscript; or in the decision to publish the results.

References

  1. Energy from Renewable Sources in 2023. Statistical Analyses. Eds. Statistical Poland, Warsaw. 2024. Available online: https://stat.gov.pl/en/topics/environment-energy/energy/energy-from-renewable-sources-in-2023,9,3.html (accessed on 17 July 2025).
  2. Chodkowska-Miszczuk, J.; Szymańska, D. Odnawialne źródła energii w produkcji energii elektrycznej w Polsce. Naucz. Przedmiotów Przyr. 2012, 41, 4. [Google Scholar]
  3. Gabryś, H. Elektroenergetyka w Polsce 2020. Energetyka 2020, 8, 365–373. [Google Scholar]
  4. Nallolla, C.A.; Chittathuru, P.V.D.; Padmanaban, S. Multi-objective optimization algorithms for a hybrid AC/DC microgrid using RES: A comprehensive review. Electronics 2023, 12, 1062. [Google Scholar] [CrossRef]
  5. Tumeran, N.L.; Yusoff, S.H.; Gunawan, T.S.; Hanifah, M.S.A.; Zabidi, S.A.; Pranggono, B.; Halbouni, A.H. Model predictive control based energy management system literature assessment for RES integration. Energies 2023, 16, 3362. [Google Scholar] [CrossRef]
  6. Erbach, G.; Jensen, L. Fit for 55 Package. EPRS, European Parliament. 2022. Available online: https://policycommons.net/artifacts/11463736/fit-for-55-package/12354871/ (accessed on 17 July 2025).
  7. Pérez de las Heras, B. The ‘Fit for 55’package: Towards a more integrated climate framework in the EU. Rom. J. Eur. Aff. 2022, 22, 63–78. [Google Scholar]
  8. Brożyna, J.; Lu, J.; Strielkowski, W. Is European current climate regulation strategy feasible? A comparative analysis of “Fit for 55” green transition package for V4 and LEU4. Energy Strategy Rev. 2025, 61, 101843. [Google Scholar] [CrossRef]
  9. Kaznowski, R.; Sztafrowski, D. System elektroenergetyczny oparty o odnawialne źródła energii-możliwości i bariery rozwoju. Przegląd Elektrotechniczny 2023, 99, 186–189. [Google Scholar] [CrossRef]
  10. Bielecki, A.; Ernst, S.; Skrodzka, W.; Wojnicki, I. The externalities of energy production in the context of development of clean energy generation. Environ. Sci. Pollut. Res. 2020, 27, 11506–11530. [Google Scholar] [CrossRef]
  11. Tiruye, G.A.; Besha, A.T.; Mekonnen, Y.S.; Benti, N.E.; Gebreslase, G.A.; Tufa, R.A. Opportunities and challenges of renewable energy production in Ethiopia. Sustainability 2021, 13, 10381. [Google Scholar] [CrossRef]
  12. Sułek, A.; Borowski, P.F. Business Models on the Energy Market in the Era of a Low-Emission Economy. Energies 2024, 17, 3235. [Google Scholar] [CrossRef]
  13. Madler, J.; Harding, S.; Weibelzahl, M. A multi-agent model of urban microgrids: Assessing the effects of energy-market shocks using real-world data. Appl. Energy 2023, 343, 121180. Available online: https://www.sciencedirect.com/science/article/pii/S0306261923005445 (accessed on 17 July 2025). [CrossRef]
  14. Rybarz, M. Transformacja energetyczna jako katalizator zmian strukturalnych w gospodarce. Zesz. Nauk. Inst. Gospod. Surowcami Miner. I Energią PAN 2024, 112, 73–82. Available online: https://bibliotekanauki.pl/articles/59112300 (accessed on 12 July 2025).
  15. Sequeira, T.N.; Santos, M.S. Does country-risk influence electricity production worldwide? J. Policy Model. 2018, 40, 730–746. [Google Scholar] [CrossRef]
  16. Yu, B.; Fang, D.; Yu, H.; Zhao, C. Temporal-spatial determinants of renewable energy penetration in electricity production: Evidence from EU countries. Renew. Energy 2021, 180, 438–451. [Google Scholar] [CrossRef]
  17. Arbabzadeh, M.; Sioshansi, R.; Johnson, J.X.; Keoleian, G.A. The role of energy storage in deep decarbonization of electricity production. Nat. Commun. 2019, 10, 3413. Available online: https://www.nature.com/articles/s41467-019-11161-5 (accessed on 17 July 2025). [CrossRef]
  18. Safarzadeh, H.; Di Maria, F. How to Fit Energy Demand Under the Constraint of EU 2030 and FIT for 55 Goals: An Italian Case Study. Sustainability 2025, 17, 3743. [Google Scholar] [CrossRef]
  19. Lehnert, W.; Traum, Y. The ‘new’Renewable Energy Directive (RED III): An overview. Eur. Energy Clim. J. 2024, 12, 40–47. [Google Scholar] [CrossRef]
  20. Gajdzik, B.; Wolniak, R.; Nagaj, R.; Žuromskaitė-Nagaj, B.; Grebski, W.W. The influence of the global energy crisis on energy efficiency: A comprehensive analysis. Energies 2024, 17, 947. [Google Scholar] [CrossRef]
  21. Niestępska, M. Priorytety likwidacji barier prawnych w energetycznej transformacji ciepłownictwa w ocenie branży ciepłowników i przedstawicieli regulatora. Dist. Heat. Instal. 2025, 4, 12–20. [Google Scholar] [CrossRef]
  22. Mir, M.Y. Sustainable Fuels Production; Springer Nature: Berlin/Heidelberg, Germany, 2025. [Google Scholar] [CrossRef]
  23. Ilves, R.; Küüt, A.; Allmägi, R.; Olt, J. The Impact of RED III Directive on the Use of Renewable Fuels in Transport on the Example of Estonia. Rigas Teh. Univ. Zinat. Raksti 2024, 28, 165–180. [Google Scholar] [CrossRef]
  24. Halkos, G.; Zisiadou, A. Energy crisis risk mitigation through nuclear power and RES as alternative solutions towards self-sufficiency. J. Risk Financ. Manag. 2023, 16, 45. [Google Scholar] [CrossRef]
  25. Dell, R.M.; Rand, D.A.J. Energy storage—A key technology for global energy sustainability. J. Power Sources 2001, 100, 2–17. [Google Scholar] [CrossRef]
  26. Yao, Z.; Lum, Y.; Johnston, A.; Mejia-Mendoza, L.M.; Zhou, X.; Wen, Y.; Seh, Z.W. Machine learning for a sustainable energy future. Nat. Rev. Mater. 2023, 8, 202–215. [Google Scholar] [CrossRef] [PubMed]
  27. Bellani, J.; Verma, H.K.; Khatri, D.; Makwana, D.; Shah, M. Shale gas: A step toward sustainable energy future. J. Pet. Explor. Prod. Technol. 2021, 11, 2127–2141. [Google Scholar] [CrossRef]
  28. Garitaonandia, E.; Arribalzaga, P.; Ibon, M.; Bielsa, D. Characterization of the Ratcheting Effect on the Filler Material of a Steel Slag-Based Thermal Energy Storage. Energies 2024, 17, 1515. [Google Scholar] [CrossRef]
  29. Sayed, E.T.; Olabi, A.G.; Alami, A.H.; Radwan, A.; Mdallal, A.; Rezk, A.; Abdelkareem, M.A. Renewable energy and energy storage systems. Energies 2023, 16, 1415. [Google Scholar] [CrossRef]
  30. Wang, W.; Yuan, B.; Sun, Q.; Wennersten, R. Application of energy storage in integrated energy systems—A solution to fluctuation and uncertainty of renewable energy. J. Energy Storage 2022, 52, 104812. [Google Scholar] [CrossRef]
  31. Arce, P.; Medrano, M.; Gil, A.; Oró, E.; Cabeza, L.F. Overview of thermal energy storage (TES) potential energy savings and climate change mitigation in Spain and Europe. Appl. Energy 2011, 88, 2764–2774. [Google Scholar] [CrossRef]
  32. Prawo Energetyczne i Ustawy o Odnawialnych Źródłach Energii. Available online: https://eli.gov.pl/eli/DU/2022/2370/ogl (accessed on 12 July 2025).
  33. Mitali, J.; Dhinakaran, S.; Mohamad, A.A. Energy storage systems: A review. Energy Storage Sav. 2022, 1, 166–216. [Google Scholar] [CrossRef]
  34. Liu, J.; Hu, H.; Yu, S.S.; Trinh, H. Virtual power plant with renewable energy sources and energy storage systems for sustainable power grid-formation, control techniques and demand response. Energies 2023, 16, 3705. [Google Scholar] [CrossRef]
  35. Duda, J.; Fierek, S.; Karkula, M.; Kisielewski, P.; Puka, R.; Redmer, A.; Skalna, I. Determining lower bound on number of vehicle blocks in multi-depot vehicle scheduling problem with mixed fleet covering electric buses. Arch. Transp. 2023, 65, 27–38. [Google Scholar] [CrossRef]
  36. Poorani, S.; Jebarani Evangeline, S.; Bagyalakshmi, K.; Maris Murugan, T. Management Systems through Deep Learning-Based Cell Balancing Mechanisms. Eksploat. I Niezawodn. 2025, 27, 200714. [Google Scholar] [CrossRef]
  37. Zhu, L. Energy management in microgrid integrated with ultracapacitor-equipped electric vehicles and renewable resources using Hybrid Algorithm Perspective. Eksploat. I Niezawodn. 2025, 27, 200713. [Google Scholar] [CrossRef]
  38. Wade, N.; Taylor, P.; Lang, P.; Jones, P. Evaluating the benefits of an electrical energy storage system in a future smart grid. Energy Policy 2010, 38, 7180–7188. [Google Scholar] [CrossRef]
  39. Lindholm, O.; Rehman, H.U.; Reda, F. Positioning positive energy districts in European cities. Buildings 2021, 11, 19. [Google Scholar] [CrossRef]
  40. Schubert, C.; Hassen, W.F.; Poisl, B.; Seitz, S.; Schubert, J.; Oyarbide Usabiaga, E.; Gaudo, P.M.; Pettinger, K.H. Hybrid energy storage systems based on redox-flow batteries: Recent developments, challenges, and future perspectives. Batteries 2023, 9, 211. [Google Scholar] [CrossRef]
  41. Marocco, P.; Ferrero, D.; Gandiglio, M.; Ortiz, M.M.; Sundseth, K.; Lanzini, A.; Santarelli, M. A study of the techno-economic feasibility of H2-based energy storage systems in remote areas. Energy Convers. Manag. 2020, 211, 112768. [Google Scholar] [CrossRef]
  42. Wu, H.; Shan, C.; Fu, S.; Li, K.; Wang, J.; Xu, S.; Hu, C. Efficient energy conversion mechanism and energy storage strategy for triboelectric nanogenerators. Nat. Commun. 2024, 15, 6558. [Google Scholar] [CrossRef]
  43. Ullah, Z.; Qazi, H.S.; Rehman, A.U.; Hasanien, H.M.; Wang, S.; Elkadeem, M.R.; Badshah, F. Efficient energy management of domestic loads with electric vehicles by optimal scheduling of solar-powered battery energy storage system. Electr. Power Syst. Res. 2024, 234, 110570. [Google Scholar] [CrossRef]
  44. Gissey, G.C.; Dodds, P.E.; Radcliffe, J. Market and regulatory barriers to electrical energy storage innovation. Renew. Sustain. Energy Rev. 2018, 82, 781–790. [Google Scholar] [CrossRef]
  45. Zeh, A.; Müller, M.; Naumann, M.; Hesse, H.C.; Jossen, A.; Witzmann, R. Fundamentals of using battery energy storage systems to provide primary control reserves in Germany. Batteries 2016, 2, 29. [Google Scholar] [CrossRef]
  46. Mrozowska, S.; Wendt, J.A.; Tomaszewski, K. The challenges of Poland’s energy transition. Energies 2021, 14, 8165. [Google Scholar] [CrossRef]
  47. Mieński, R.; Wasiak, I.; Kelm, P. Integration of PV Sources in Prosumer Installations Eliminating Their Negative Impact on the Supplying Grid and Optimizing the Microgrid Operation. Energies 2023, 16, 3479. [Google Scholar] [CrossRef]
  48. Lei, Z.; Zheng, Z.; Zhang, L. Current Harmonics Suppression Scheme for GaN-Based DCM Grid-Tied Micro-Inverters. In Proceedings of the PEAS 2023–2023 IEEE 2nd International Power Electronics and Application Symposium, Conference Proceedings, Guangzhou, China, 10–13 November 2023. [Google Scholar] [CrossRef]
  49. Nguyen-Tuan, A.; Ta-Duy, B.; Nguyen-Duc, T.; Fujita, G. A novel approach to optimize and allocate battery energy storage system in distributed grid considering impact of demand response program. Sustain. Energy Grids Netw. 2025, 43, 101738. [Google Scholar] [CrossRef]
  50. Ipsakis, D.; Voutetakis, S.; Seferlis, P.; Stergiopoulos, F.; Elmasides, C. Power management strategies for a stand-alone power system using renewable energy sources and hydrogen storage. Int. J. Hydrogen Energy 2009, 34, 7081–7095. [Google Scholar] [CrossRef]
  51. Suresh, C.; Saini, R.P. Thermal performance of sensible and latent heat thermal energy storage systems. Int. J. Energy Res. 2020, 44, 4743–4758. [Google Scholar] [CrossRef]
  52. Wang, X.; Zhang, N.; Li, D.; Du, Z.; Feng, Y.; Liu, D. Development Status and Prospect of Distributed New Energy Participating in Power Market. In Proceedings of the 2023 4th International Conference on Advanced Electrical and Energy Systems (AEES), Shanghai, China, 1–3 December 2023. [Google Scholar] [CrossRef]
  53. Simpeh, E.K.; Pillay, J.P.G.; Ndihokubwayo, R.; Nalumu, D.J. Improving energy efficiency of HVAC systems in buildings: A review of best practices. Int. J. Build. Pathol. Adapt. 2022, 40, 165–182. [Google Scholar] [CrossRef]
  54. Kim, D.; Lee, J.; Do, S.; Mago, P.J.; Lee, K.H.; Cho, H. Energy modeling and model predictive control for HVAC in buildings: A review of current research trends. Energies 2022, 15, 7231. [Google Scholar] [CrossRef]
  55. Navarro, L.; De Gracia, A.; Colclough, S.; Browne, M.; McCormack, S.J.; Griffiths, P.; Cabeza, L.F. Thermal energy storage in building integrated thermal systems: A review. Part 1. active storage systems. Renew. Energy 2016, 88, 526–547. [Google Scholar] [CrossRef]
  56. Elkhatat, A.; Al-Muhtaseb, S.A. Combined “renewable energy–thermal energy storage (RE–TES)” systems: A review. Energies 2023, 16, 4471. [Google Scholar] [CrossRef]
  57. Chicco, J.M.; Mandrone, G. Modelling the energy production of a borehole thermal energy storage (BTES) system. Energies 2022, 15, 9587. [Google Scholar] [CrossRef]
  58. Mousavi Ajarostaghi, S.S.; Amiri, L.; Poncet, S. Application of Thermal Batteries in Greenhouses. Appl. Sci. 2024, 14, 8640. [Google Scholar] [CrossRef]
  59. Song, L.; Guo, W.; He, Z.; Zhang, P. Thermal, economic and food preservation performances of a refrigerated warehouse equipped with on-shelf phase change material. Int. J. Refrig. 2024, 165, 16–30. [Google Scholar] [CrossRef]
  60. Vadiee, A.; Martin, V. Thermal energy storage strategies for effective closed greenhouse design. Appl. Energy 2013, 109, 337–343. [Google Scholar] [CrossRef]
  61. Jałowiec, T.; Wojtaszek, H.; Miciuła, I. Analysis of the potential management of the low-carbon energy transformation by 2050. Energies 2022, 15, 2351. [Google Scholar] [CrossRef]
  62. Chudy-Laskowska, K.; Pisula, T. An analysis of the use of energy from conventional fossil fuels and Green renewable energy in the context of the European Union’s planned energy transformation. Energies 2022, 15, 7369. [Google Scholar] [CrossRef]
  63. Tao, M.; Yu, Y.; Zhang, H.; Ye, T.; You, S.; Zhang, M. Research on the optimization design of solar energy-gas-fired boiler systems for decentralized heating. Energies 2021, 14, 3195. [Google Scholar] [CrossRef]
  64. Halam, R.; Raman, R. Enhancing Energy Efficiency in Solar Water Heating Systems for Sustainable Homes with IoT Technology. In Proceedings of the 2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2023, Chennai, India, 14–15 December 2023. Date Added to IEEE Xplore 19 March 2024. [Google Scholar] [CrossRef]
  65. Alawi, O.A.; Kamar, H.M.; Mallah, A.R.; Mohammed, H.; Sabrudin, M.A.S.; Newaz, K.M.S.; Najafi, G.; Yaseen, Z.M. Experimental and theoretical analysis of energy efficiency in a flat plate solar collector using monolayer graphene nanofluids. Sustainability 2021, 13, 5416. [Google Scholar] [CrossRef]
  66. Krinitsky, M.; Averbukh, M. Control and Managing of Individual Solar Water Heating Systems in an Apartment Complex. Electronics 2024, 13, 2305. [Google Scholar] [CrossRef]
  67. Xin, X.; Liu, Y.; Zhang, Z.; Zheng, H.; Zhou, Y. A day-ahead operational regulation method for solar district heating systems based on model predictive control. Appl. Energy 2025, 337, 124619. [Google Scholar] [CrossRef]
  68. Jafari, S.; Sohani, A.; Hoseinzadeh, S.; Pourfayaz, F. The 3E Optimal Location Assessment of Flat-Plate Solar Collectors for Domestic Applications Iran. Energies 2022, 15, 3589. [Google Scholar] [CrossRef]
  69. Liyew, K.W.; Louvet, Y.; Habtu, N.G.; Jordan, U. Experimental investigations of the operating behaviour of a low-flow drainback solar heating system. Energy Rep. 2025, 13, 594–608. [Google Scholar] [CrossRef]
  70. Bellos, E.; Tzivanidis, C. Investigation of a novel CO2 transcritical organic rankine cycle driven by parabolic trough solar collectors. Appl. Syst. Innov. 2021, 4, 53. [Google Scholar] [CrossRef]
  71. Bugała, A.; Bugała, D.; Jajczyk, J.; Dąbrowski, T. Statistical Analysis of Electrical and Non-Electrical Parameters of Photovoltaic Modules in Controlled Tracking Systems Artur Bugała. Rocz. Ochr. Srodowiska 2021, 23, 694–714. [Google Scholar] [CrossRef]
  72. Orosz, T.; Rassolkin, A.; Arsenio, P.; Poor, P.; Valme, D.; Sleisz, A. Current Challenges in Operation, Performance, and Maintenance of Photovoltaic Panels. Energies 2024, 17, 1306. [Google Scholar] [CrossRef]
  73. Olchowik, W.; Bednarek, M.; Dąbrowski, T.; Rosiński, A. Application of the Energy Efficiency Mathematical Model to Diagnose Photovoltaic Micro-Systems. Energies 2023, 16, 6746. [Google Scholar] [CrossRef]
  74. Kelm, P.; Mieński, R.; Wasiak, I. Modular PV System for Applications in Prosumer Installations with Uncontrolled, Unbalanced and Non-Linear Loads. Energies 2024, 17, 1594. [Google Scholar] [CrossRef]
  75. Tuballa, M.L.; Abundo, M.L. A review of the development of smart grid technologies. Renew. Sustain. Energy Rev. 2016, 59, 710–725. [Google Scholar] [CrossRef]
  76. Zame, K.K.; Brehm, C.A.; Nitica, A.T.; Richard, C.L.; Schweitzer, G.D., III. Smart grid and energy storage: Policy recommendations. Renew. Sustain. Energy Rev. 2018, 82, 1646–1654. [Google Scholar] [CrossRef]
  77. Nalina, B.S.; Chilambarasan, M.; Tamilselvi, S.; Al Alahmadi, A.A.; Alwetaishi, M.; Mujtaba, M.A.; Kalam, M.A. Design and Implementation of Embedded Controller-Based Energy Storage and Management System for Remote Telecom. Electronics 2023, 12, 341. [Google Scholar] [CrossRef]
  78. Zhang, Y.; Guo, Y.; Zhu, J.; Yuan, W.; Zhao, F. New Advances in Materials, Applications, and Design Optimization of Thermocline Heat Storage: Comprehensive Review. Energies 2024, 17, 2403. [Google Scholar] [CrossRef]
  79. Global Energy Storage Market, InfoLink, 24 January 2025. Available online: https://www.infolink-group.com/energy-article/energy-storage-topic-global-energy-storage-market-review-outlook (accessed on 20 August 2025).
  80. Electricity Production. Annual Report 2024. Available online: https://www.rynekelektryczny.pl/produkcja-energii-elektrycznej-raport-roczny/ (accessed on 16 April 2025).
  81. Uribe-Pérez, N.; Hernández, L.; de la Vega, D.; Angulo, I. State of the art and trends review of smart metering in electricity grids. Appl. Sci. 2016, 6, 68. [Google Scholar] [CrossRef]
  82. Brown, M.A.; Zhou, S. Smart-grid policies: An international overview. WIREs Energy Environ. 2013, 2, 121–139. [Google Scholar] [CrossRef]
  83. Clastres, C. Smart grids: Another step towards competition, energy security and climate change objectives. Energy Policy 2011, 39, 5399–5408. [Google Scholar] [CrossRef]
  84. Smalley, R.E. Future Global Energy Prosperity: The Terawatt Challenge; Cambridge University Press: Cambridge, UK, 31 January 2011. [Google Scholar]
  85. Makansi, J. Lights Out: The Electricity Crisis, the Global Economy, and What It Means to You; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2007. [Google Scholar] [CrossRef]
  86. Kania, M.; Jaskowski, P.; Madlenak, R.; Zaranka, J. Analysis of real-time Energy transfer possibilities at intersections with consideration of Energy storage and reduction of transport impact on the environment. Arch. Transp. 2025, 73, 195–206. [Google Scholar] [CrossRef]
  87. Sablin, O.; Bosyi, D.; Kuznetsov, V.; Lewczuk, K.; Kebal, I.; Myamlin, S.S. Efficiency of energy storage control in the electric transport systems. Arch. Transp. 2022, 62, 105–122. [Google Scholar] [CrossRef]
  88. Znaczko, P.; Kaminski, K.; Chamier-Gliszczynski, N.; Szczepanski, E. Experimental analysis of control methods in solar water heating systems. Energies 2021, 14, 8258. [Google Scholar] [CrossRef]
  89. Kaminski, K.; Znaczko, P.; Lyczko, M.; Krolikowski, T.; Knitter, R. Operational properties investigation of the flat-plate solar collector with poliuretane foam insulation. Procedia Comput. Sci. Conf. Pap. 2019, 159, 1730–1739. [Google Scholar] [CrossRef]
  90. Kurz, D.; Dobrzycki, A.; Krawczak, E.; Jajczyk, J.; Mielczarek, J.; Woźniak, W.; Sąsiadek, M.; Orynycz, O.; Tucki, K.; Badzińska, E. An Analysis of the Increase in Energy Efficiency of Photovoltaic Installations by Using Bifacial Modules. Energies 2025, 18, 1296. [Google Scholar] [CrossRef]
  91. Trzmiel, G.; Jajczyk, J.; Kardas-Cinal, E.; Chamier-Gliszczynski, N.; Wozniak, W.; Lewczuk, K. The condition of photovoltaic modules under random operation parameters. Energies 2021, 14, 8358. [Google Scholar] [CrossRef]
  92. Olkiewicz, M.; Dyczkowska, J.A.; Olkiewicz, A.M. Financial Aspects of Energy Investments in the Era of Shaping Stable Energy Development in Poland: A Case Study. Energies 2023, 16, 7814. [Google Scholar] [CrossRef]
Figure 1. Electricity production. Annual Report 2024 [79].
Figure 1. Electricity production. Annual Report 2024 [79].
Energies 18 04981 g001
Figure 2. Energy storage in all forms of system services.
Figure 2. Energy storage in all forms of system services.
Energies 18 04981 g002
Figure 3. Energy distribution channel with energy storage for the power grid operator.
Figure 3. Energy distribution channel with energy storage for the power grid operator.
Energies 18 04981 g003
Figure 4. Factors determining the implementation of reversible warehouses.
Figure 4. Factors determining the implementation of reversible warehouses.
Energies 18 04981 g004
Figure 5. Distribution and heat channels with storage facilities in the network.
Figure 5. Distribution and heat channels with storage facilities in the network.
Energies 18 04981 g005
Figure 6. Growth in the capacity of prosumer microinstallations in the period 2019–2024.
Figure 6. Growth in the capacity of prosumer microinstallations in the period 2019–2024.
Energies 18 04981 g006
Figure 7. Capacity contracted by energy storage facilities in main auctions for 2021–2028.
Figure 7. Capacity contracted by energy storage facilities in main auctions for 2021–2028.
Energies 18 04981 g007
Figure 8. Sales and use of energy storage in a prosumer microinstallation with a forecast until 2030.
Figure 8. Sales and use of energy storage in a prosumer microinstallation with a forecast until 2030.
Energies 18 04981 g008
Figure 9. Energy distribution channels in microinstallations with storage facilities.
Figure 9. Energy distribution channels in microinstallations with storage facilities.
Energies 18 04981 g009
Table 1. Gross final energy consumption in 2020 according to Eurostat methodology. Source, Eurostat; compiled by IEO.
Table 1. Gross final energy consumption in 2020 according to Eurostat methodology. Source, Eurostat; compiled by IEO.
Final Energy Consumption 2020TWhShare [%]
Heat consumption44753
Electricity consumption17020
Transport fuel consumption22827
Gross final energy consumption846100
Table 2. Summary of installed capacity of storage facilities connected to the TSO and DSO networks.
Table 2. Summary of installed capacity of storage facilities connected to the TSO and DSO networks.
Power Grid OperatorNumber of WarehousesNumber of kW
Polskie Sieci Elektroenergetyczne S.A.21,250,600
PGE Dystrybucja S.A.2200,748
TAURON Dystrybucja S.A.41400
ENERGA-OPERATOR S.A.26180
ENEA Operator Sp. z o.o.NDND
Stoen Operator Sp. z o.o.170
PGE Energetyka Kolejowa S.A.15500
ND–no data.
Table 3. Information on warehouses connected to the operators’ network as of the end of 2023.
Table 3. Information on warehouses connected to the operators’ network as of the end of 2023.
Warehouse NameWarehouse TechnologyTotal Installed Power [kW]Capacity [kWh]Efficiency [%]
PGE Energia Odnawialna S.A.Pumped storage power plant710,0003,800,00078
PGE Energia Odnawialna S.A.Pumped storage power plant540,0002,000,00075
Stoen Operator Sp. z o.o.Lithium-ion batteries706282
PGE Dystrybucja S.A.Lithium-ion batteries2088423784
PGE Energia Odnawialna S.A.Pumped storage power plant198,660640,00079
Tauron Ekoenergia Sp. z o.oLithium-ion batteries50050080
Tauron Inwestycje Sp. z o.oElectrochemical energy20025093
Tauron Polska Energia S.A.Electrochemical energy15015088
PGE Energia Odnawialna S.ALithium-ion batteries with NMC cells55075090
Energa Wytwarzanie S.A.Hybrid rechargeable battery600015,00070
Orlen S.A. Branch PGNiG in OdolanowLithium-ion batteries18040398
PKP EnergetykaLithium-ion batteries50001200ND
Total 1,464,4986,462,552
ND–no data.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Dyczkowska, J.A.; Panek, A.; Chamier-Gliszczynski, N. Identification of Energy Storage in Distribution Channels. Energies 2025, 18, 4981. https://doi.org/10.3390/en18184981

AMA Style

Dyczkowska JA, Panek A, Chamier-Gliszczynski N. Identification of Energy Storage in Distribution Channels. Energies. 2025; 18(18):4981. https://doi.org/10.3390/en18184981

Chicago/Turabian Style

Dyczkowska, Joanna Alicja, Aleksandra Panek, and Norbert Chamier-Gliszczynski. 2025. "Identification of Energy Storage in Distribution Channels" Energies 18, no. 18: 4981. https://doi.org/10.3390/en18184981

APA Style

Dyczkowska, J. A., Panek, A., & Chamier-Gliszczynski, N. (2025). Identification of Energy Storage in Distribution Channels. Energies, 18(18), 4981. https://doi.org/10.3390/en18184981

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop