Techno-Economic Assessment of CO₂-Based Power to Heat to Power Systems for Industrial Applications

Nowadays the industrial sector is one of the main greenhouse gases emitters [1], representing a major challenge toward achieving worldwide net zero energy targets [2]. About 50% of the worldwide energy consumption is spent on heating purposes, and about 44% of this is devoted to the industrial sector [3]. Similarly, about 30% of the industrial sector's energy demand is in the form of electricity [4]. Efficient and cost-effective solutions targeting the industrial energy demand on terms of both heat and electricity are largely needed. By exploiting thermal energy storage (TES) based power-to-heat and power-to-heat-to-power systems the industrial sector could largely cut its dependency on fossil fuels, minimize its operational costs, whilst providing a source of flexibility to the overall grid and facilitating the integration of fluctuating renewable energy sources.

Electrification has been recognized as major pathway to attain a decarbonized society, by cost-effectively contributing to fossil fuel substitution and renewable integration [5]. The technological potential for industry electrification has been estimated in Ref. [6] showing that 78% of the heating demand could be fulfilled by commercial technology. Electrification could also reduce the industry's greenhouse gases emissions by more than 75% [7]. Flexible coupling of power and heat could cost-effectively contribute to renewable energy integration and fossil fuel substitution in the residential sector [8]. However, comprehensive techno-economic assessments of power-to-heat-to-heat and power systems including TES are rare, particularly when focusing on the industrial sector [9].

This work, also starting from the results of previous authors' research [10] and valorizing their expertise in modeling both TES integrated power plants [11,12], sCO₂ cycles [13,14], and power plant electric market opportunities [15], aims at filling this research gap and presents the techno-economic assessment of a molten salts (MS) TES based power-to-heat-to-heat and power system. The proposed system stores thermal energy at about 450 °C and provides electricity and saturated steam between 150 °C and 180 °C. Typical major industrial users of steam and electricity, such as paper and cardboard industries, are considered together with their typical consumption patterns. Four different configurations of power-to-heat-to-heat and power systems are introduced, sketched in Fig. 1, and described in detail in System Definition. Their performance is assessed comparatively based on technical and economic indicators. Key components such as electric heaters, high temperature heat pumps, supercritical, and transcritical CO₂ power cycles are also presented and investigated.

The set of investigated system layouts is sketched in Fig. 1, and Table 1 summarizes the main sizing parameters. All systems are based on a modular TES exploiting a ternary molten salt (Yara MOST^®, mass ratio of 43% potassium-nitrate (KNO₃), 15% sodium-nitrate (NaNO₃), and 42% calcium nitrate (Ca(NO₃)₂) [16]. Each TES module has a volume of about 28 m³ and an energy capacity of 5 MWh_th, several TES units can be stacked to accommodate the required total thermal capacity [10]. The thermal load is represented by a typical cardboard facility demand, equivalent to 3 MW_th of saturated steam at 180 °C constant in the time interval between 06.00 and 22.00 all days. The assumed thermal load is based on the clustering activity carried on by the IEA SHC Task 64 [17]. The thermal demand is fulfilled by means of a steam generator unit (SGS).

Two different charging units have been investigated: (i) a modular electrical heater (EH) with a nominal power of 10 MW_e (with multiple units that could be stacked in case of higher power), (ii) a high temperature heat pump (HTHP) evolving CO₂ and recovering industrial waste heat. The charging units provide the required power to charge the TES during charge operation and raise the MS temperature from 220 °C to 450 °C, as limited by the Yara Most^® maximum operating temperature [16]. The EH is a commercial and proven solution. Notwithstanding, the typically elevated efficiencies of immersed electric heaters, the attained values cannot compete with the coefficient of performance (COP) theoretically attainable by heat pumps. HTHP are innovative solutions, upon which wide research effort are ongoing [18]. In industrial contexts waste heat at temperature higher than 100 °C has been recognized as a critical energy stream, currently largely not recovered [19,20]. Within Europe, a total waste heat of about 300TWh/year has been estimated in Ref. [20], with about 33% below 200 °C, 25% in the range 200–500 °C, and the remaining at temperature higher than 500 °C. HTHP could contribute to leverage the low-temperature waste heat stream, increasing its temperature and permitting later use for power or heat generation [6]. This equipment would increase the system complexity and capital expenditure (CAPEX) with respect to a solution based on EH. However, higher round trip efficiencies and COP higher than two are attainable. Thus, it is expected that possible savings in electricity consumptions would pay off and counteract the higher CAPEX and complexity of HTHP-based systems, leading to more cost-effective solutions.

Similarly, two different power units have been considered: a supercritical and a transcritical CO₂ power loop. The power cycles are integrated in the system, extracting heat from the MS at their hottest point thus ensuring high turbine inlet temperatures (440 °C) and limiting the temperature difference between incoming MS and steam demand at the SGS. With respect to a supercritical cycle, in which the fluid conditions are always maintained above the critical point (30.978 °C, 7.3773 MPa for CO₂ [21]), in transcritical cycles the low pressure side operates at pressures lower than the critical pressure and fluid condensation is obtained. Thus in transcritical cycles the cooler is substituted by a condenser unit, while the compressor is substituted by a pump. Assuming the same turbine inlet conditions a transcritical cycle, ensures higher network and the avoidance of a the compressor which is typically a critical component due to its working conditions close to the critical point where changes in the thermodynamic properties of the fluid are large and sudden. Thus, higher efficiency could be attained by CO₂ transcritical cycle with respect to supercritical ones. However, to ensure good conditions in the CO₂ condenser low inlet temperatures of the coolant (typically air or water) are needed [22]. This specific requirement has often been highlighted as a major obstacle for the adoption of this cycle in hot and warm climates, where low condensation temperature can be hardly guaranteed without additional components [23]. Simple recuperated power cycles have been considered due to their simplicity and limited capital cost, still guaranteeing acceptable thermodynamic performance [14]. Easiness in operation and reduced upfront investment would be key factors for a widespread future introduction of the technology in the industrial context. More details on the main assumptions and modeling approach followed to assess the performance of the different charging units and power loops are described in Materials and Methods.

Figure 2 shows a summary of the methodology followed during the modeling of the proposed systems and layouts, including the main inputs and outcomes of each step as well as the considered key performance indicators (KPIs). The full model is built via Excel VBA macros, detailed thermodynamic models of the HTHP unit and of the different power cycles are built in matlab, the dispatch optimization is built via Python scripts, and coolprop has been exploited for the thermodynamic properties.

First, the main technical inputs describing the key components (i.e., power cycle efficiency and COP), the system's requirement (i.e., thermal load), and boundary conditions (i.e., electricity prices) are specified. A dispatch optimizer, based on a mixed integer linear programming (MILP) algorithm, has been developed to identify the optimal system operation. A more detailed description of the dispatch optimizer is provided in Dispatch Optimizer. Additional technical inputs fully describing the thermodynamic behavior of the integrated system, together with the identified dispatch strategy fed the full thermodynamic model. This step provides hourly based thermodynamic outputs, based on which technical and energy-related KPIs are calculated. The detained approach followed in the implementation of the thermodynamic model, its main assumptions, and considered KPIs is presented in Thermodynamic System Modeling and Economic System Modeling. A parallel bottom-up economic model, based on cost functions gathered from literature and direct data from industrial partners, is exploited to evaluate the economic performance of the proposed solution. The key features of the economic model are introduced in Economic System Modeling. Techno-economic KPIs such as the nominal levelized cost of heat (LCoH) and electricity (LCoE), the CAPEX, and the operational expenditure (OPEX) are evaluated and exploited to compare the different solutions and benchmarked against reference business as usual (BAU). Additionally, LCoH, LCoE, and OPEX have been exploited as main objectives aiming at optimizing the system sizing, considering the nominal power of the charging unit and the TES capacity as decision variables.

To investigate the thermodynamic performance of the proposed systems quasi-steady-state models have been built. The TES, including thermal losses, and SGS models have been widely described by the authors in Ref. [10]. The models of the supercritical and transcritical CO₂ cycles are based on typical thermodynamic approaches considering the iso-entropic efficiency of the main turbomachinery and neglecting pressure losses in the main heat exchangers. The recuperated arrangement for both supercritical and transcritical CO₂ cycles has been considered representative of a relevant tradeoff between system complexity and CAPEX, and attainable thermal efficiency [22]. The main working conditions and data assumed to describe the power cycles are summarized in Table 2. Figure 3 shows the temperature-entropy diagram of the two cycles under the considered design conditions. Both cycles considers a turbine inlet temperature of 440 °C (10 °C lower than the maximum MS temperature). The working pressure for the supercritical cycle has been chosen in agreement with most of the literature assessing the potential for sCO₂ integration in concentrating solar power plants [12]. The maximum pressure in the transcritical CO₂ loop, considered equal to 22 MPa, has been selected in order to ensure a safety margin from the critical point at the outlet of the pump. In the supercritical cycle, the compressor inlet point has been fixed to 32 °C and 7.38 MPa, typical boundary conditions ensuring elevated cycle performance while guaranteeing a sufficient safety margin from the critical point [25]. For the transcritical CO₂ cycle a condensation temperature of 10 °C and consequent pressure of 4.5 MPa have been assumed. These values are within the typical temperature range, 5–15 °C [26,27], considered in different previous works. Additionally, since this work investigates locations with a relatively cold climate (with average ambient temperature below 10 °C), the specific assumption has been considered attainable. The HTHP cycle considers similar working conditions as the sCO₂ power cycle, with the same working pressure. Waste heat recovery with a waste heat temperature of 280 °C has been considered. A compressor outlet temperature of 460 °C is attained in order to ensure an MS outlet temperature of 450 °C. The HTHP cycle is then able to deliver heat to the MS and TES by cooling the CO₂ from 460 °C to about 225 °C (point C), leaving the heat exchanger at about 5 °C above the incoming cold MS stream.

During operation of the integrated system the state of charge of the TES unit has been calculated as the ratio between the stored energy over the maximum TES energy capacity.

A bottom-up model, based on specific costs and data gathered from literature, has been develop to describe and analyze the economic performance of the proposed systems. The economic KPIs considered are CAPEX, OPEX and OPEX savings with respect to alternative BAU scenarios, and nominal levelized cost of heat (LCoH) and electricity (LCoE). The economic model includes the capital costs of all the main equipment and balance of plant units: molten salts vessel and insulation [28,29], salts (MS) [16], EH [14], SGS [30], CO₂ power cycles [26,31,32], HTHP [12,32], transformer [33,34], circulation system and battery management system (BMS). The specific cost functions are summarized in the  Appendix. Indirect CAPEX accounts for taxes, EPC, and contingencies, considered equal to 2%, 3%, and 2% of the direct CAPEX, respectively [35]. Decommission costs of 2% of the direct CAPEX have been included. The OPEX includes expenses for electricity, operation, and maintenance (among which replacement of some components for the circulation system and TES, characterized by a lifetime of 5 years, have been included), and site. Seasonal and yearly tariffs for electricity consumption have been also accounted for.

In Eq. (5)$max(pel|124)$ and $min(pel|124)$ represent the daily maximum and minimum electricity price. Figure 4 summarizes the characterization of the different electric grid regions in the EU. Norway and the Northern Swedish regions, largely relying on hydropower, are characterized by low average electricity prices and limited fluctuations. In these locations, electrification of heat and other services is expected to be beneficial thanks to the low prices. However, the reduced price fluctuations limit the potential for energy storage solutions. Southern Sweden, Finland, and other Eastern EU countries could instead provide a suitable environment for the proposed system. These markets are indeed characterized by limited average prices and high fluctuations, leading to high potential for electrification and high need for flexibility ensured by TES. Therefore, Finland has been considered in this study. Additionally, Germany has been also assessed in this study since it is the largest potential market in EU and it closely represents average EU conditions.

This section presents and discusses the main results. First, the main techno-economic results for a base case are shown. Second, the optimized system sizing is presented including discussions on the influence of key parameters. Finally, the performance of the proposed systems is compared and benchmarked also against BAU alternatives.

A relevant base case has been considered to generally describe the behavior and some key features of the proposed system. The considered layout comprises an EH as charging unit and a supercritical CO₂ cycle as power loop. The main design parameters and KPIs for this selected base case are summarized in Table 3. The considered system is located in Finland.

The considered base case has a TES capacity of 150 MWh, which is about three times the considered industrial daily thermal energy demand and equivalent to cover the full thermal demand to power both the sCO₂ cycle and the SGS for a full day. The TES utilization is not maximized and on many days the TES is not fully cycled. However, such high TES capacity ensures the potential to store large amounts of energy before high peak in electricity prices, thus maximizing the attainable OPEX savings. A nominal power of 50 MW is considered for the EH, the high power capacity ensures a maximization of the exploitation of the hours at cheap electricity prices limiting the costs during the charging phase.

Figure 5 shows the main behavior and operation of the system as identified by the dispatch optimization algorithm for six characteristic consecutive days (from Mar. 15–20, 2022). It can be noted that most of the TES charge phase occurs during the night period when no thermal load is demanded. Additionally, in the majority of the days, the electricity price decreases during the central hours of the day leading to an additional TES charging phase around noon. This additional energy can be then exploited to fuel the power cycle and produce, not only heat but also electricity, during the peak periods with high electricity prices (as during the Mar. 17, 20, and 22). Considering a full year of operation of the base layout, the system operates under only heat production for the majority of the time (42.9%). The high charging capacity installed permits to limit the charging operation to only 9.6%, while the system provides heat and power for about 27.9% of the time, thus limiting the capacity factor (CF) of the power cycle.

Figure 6 presents the CAPEX and OPEX share of the considered base case layout and sizing (as from Table 3). Due to the required large TES capacity and EH nominal power to limit the OPEX, large shares of the CAPEX are associated with these components. Specifically, the TES tanks together with the MS accounts for almost 50% while the EH accounts for about 19% of the total CAPEX. However, it should be highlighted that from an LCoH and LCoE perspective, these systems are mainly driven by the OPEX. Thus, higher initial investments can be justified when ensuring large energy cost reductions throughout the whole lifetime of the project. The OPEX is largely driven by the cost of electricity which accounts for more than 85% of the total.

Optimal system sizing ensuring minimal LCoE and LCoH has been identified for all proposed system layouts and electricity markets. The relevance of TES capacity (E_TES) and the nominal power of the charging unit (P_EH) for the considered base layout with EH and sCO₂ is summarized in Fig. 7. Additionally, Fig. 7 shows the range of attainable LCoH for a similar system only focusing on heat delivery (light vertical band), as well as the range of average electricity prices during operation of the power cycle (light horizontal band). As expected a clear tradeoff between heat and power production is highlighted, an LCoE reduction leads to an increase in the achievable LCoH and the relative Pareto front can be identified. The size of the charging unit has a dominant influence over the system performance, and larger investment in the EH are compensated by the attainable OPEX savings. TES capacity in the range from 120 to 170 MWh ensures minimal LCoE with the smallest capacity associated with the smallest EH. Additionally, it should be highlighted that even if a tradeoff between power and heat exists, the introduction of power cycle and the relative increase in TES capacity and EH nominal power can largely reduce the attainable LCoE at the expense of a limited increase of the LCoH. Specifically, for an LCoE reduction of more than 40% with respect to the average price during discharge an increase of about 20% of the LCoH is recorded.

Figure 8 shows the achievable OPEX savings thanks to the electricity produced by the power cycle when compared against the spot market prices, as well as the CF of the CO₂ power cycle for the same EH + sCO₂ base case layout. Higher sCO₂ CF ensures lower LCoE and thus higher electricity OPEX saving. Within the considered ranges, maximum electricity OPEX saving of about 272 k€/y are achievable for a sCO₂ CF of around 28%. However, to achieve further increase of the sCO₂ CF, an oversizing of the TES is required together with more charging hours, which causes reductions in the system profitability.

Figure 9 shows a comparative assessment of the main KPIs for the four considered system layouts and the two different electricity markets. Specifically, the Pareto fronts showing the optimal tradeoffs between LCoE and LCoH are shown together with the attainable electricity OPEX savings. The Finnish market, characterized by lower average electricity prices, ensures more cost competitive outcomes. Particularly, all proposed layouts ensure electricity OPEX savings. Increasing the system round trip efficiency by means of the introduction of a transcritical CO₂ cycle (solid lines in Fig. 9) leads to reduction in the LCoE, with limited changes in the LCoH. The introduction of the HTHP comes with lower OPEX due to a reduction of the needed power consumption (thanks to a higher COP). This permits a higher exploitation of the power cycles with CF higher than 50%. However, a higher CAPEX has to be faced. Specifically, to ensure minimum LCoE in the EH-based system 50 MW_e charging units are needed, while 10 MW_e HTHP are required in the relative configurations. Such installed power difference coupled with the different CAPEX leads to the EH and HTHP accounting for about 19% and 52%, respectively, of the full system (sCO₂ based) CAPEX. To attain electricity OPEX savings and thus ensure a profitable addition of heat-to-power technologies in the German context, the use of HTHP and the associated high COP is needed. The HTHP provides large reductions (about 50%) in the LCoH due to an increase in system efficiency and a limited associated increase in CAPEX. Similarly, even if the attainable LCoE is not largely reduced the achievable electricity OPEX savings are increased by the introduction of the HTHP thanks to lower OPEX.

Figure 10 summarizes the total OPEX attainable by the proposed systems (black bars) as well as by BAU alternatives (green and gray bars) and the OPEX savings for both heat and power production for the two considered markets (red and blue bars). The data refer to the system sizing attaining the minimum LCoE in all cases. The systems including a tCO₂ cycle, characterized by a higher efficiency, provide higher power production. This permits the tCO₂-based systems to attain higher OPEX savings for the electricity. It should be highlighted that the only proposed system including EH and sCO₂ power cycle in Germany provides negative OPEX savings (higher costs for the user). This is caused by the low overall efficiency of the system and the lower electricity price fluctuation in the German market. The HTHP-driven systems can attain improved performance. The proposed systems including HTHP require lower OPEX and the OPEX savings, particularly for heat production, are increased with a higher relevance in more expensive spot markets (i.e., Germany). The flexibility provided by the proposed systems ensures OPEX savings in all configurations. The total OPEX savings range between about 1.5 M€/y and more than 3 M€/y, and the largest share of these savings is thanks to heat generation.

In this work, the techno-economic assessment of a MS TES based power-to-heat-to-heat and power system for the industrial sector has been presented. Four different configurations of power-to-heat-to-heat and power systems have been introduced and their performance is assessed comparatively on the basis of technical and economic performance. The relevance of the components such as electric heaters, high temperature heat pumps, and supercritical and transcritical CO₂ power cycles have been investigated. Optimized dispatch strategies and system sizing are also identified. From the discussed results, the following main conclusions can be drawn:

The investigated power-to-heat-to-power and heat systems could offer cost-competitive solutions for the industrial sector requiring both heat and power.

The proposed systems, thanks to the flexibility ensured by the thermal energy storage units, can provide large OPEX savings, particularly in market characterized by high electricity price volatility and fluctuations.

The charging unit is the most relevant part of the proposed systems and to ensure cost-effective systems high nominal power units are needed. This also highlight the need for further development of high temperature heat pumps which today could get up to 160–200 °C with good COP [37], particularly focusing on the industrial heat demand.

It should be mentioned that the studied HTHP are not yet commercial products. However, quick market entry could be foreseen thanks to the rapid growth of R&D effort in the topic and the potential for components reuse for sCO₂ power cycles. This study sets the ground for future power-to-heat-to-heat and power techno-economic investigations, considering different layouts and requirements, and aimed at addressing different industrial sectors.

The authors acknowledge the contribution with technical feedback and data from Kyoto Group AS.

• Kyoto Group AS through the research project “Renewable Industrial Heat On-Demand” (RIHOND).

BAU =

business as usual

C =

cost

CAPEX =

capital expenditure

CF =

capacity factor

COP =

coefficient of performance

CU =

charging unit

d =

degradation rate

E =

energy

EH =

electric heater

el =

electric

EOH =

equivalent operating hours

h =

enthalpy

H =

thermal

HTHP =

high temperature heat pump

LCoE =

levelized cost of electricity

LCoH =

levelized cost of heat

KPI =

key performance indicators

MILP =

mixed integer linear programming

MS =

molten salt

OM =

operational mode

OPEX =

operational expenditure

P =

power

p_el =

electricity price

r =

economic discount rate

RTE =

round trip efficiency

sCO₂ =

supercritical CO₂

SoC =

state of charge

SGS =

steam generator

tCO₂ =

transcritical CO₂

TES =

thermal energy storage

u =

Boolean control variable

α =

operation reduction factor due to EOH

γ =

share of external investment

η =

efficiency

ν =

electricity price fluctuation

The cost for CO₂ piping has been assumed equal to 15% of the power cycle CAPEX.