Biomass to H2: Evaluation of the Impact of PV and TES Power Supply on the Performance of an Integrated Bio-Thermo-Chemical Upgrading Process for Wet Residual Biomass

Abstract

The last Intergovernmental Panel on Climate Change (IPPC) assessment report highlighted how actions to reduce CO₂ emissions have not been effective so far to achieve the 1.5 C limit and that radical measures are required. Solutions such as the upgrading of waste biomass, the power-to-X paradigm, and an innovative energy carrier such as hydrogen can make an effective contribution to the transition toward a low-carbon energy system. In this context, the aim of this study is to improve the hydrogen production process from wet residual biomass by examining the advantages of an innovative integration of anaerobic digestion with thermochemical transformation processes. Furthermore, this solution is integrated into a hybrid power supply composed of an electric grid and a photovoltaic plant (PV), supported by a thermal energy storage (TES) system. Both the performance of the plant and its input energy demand—splitting the power request between the photovoltaic system and the national grid—are carefully assessed by a Simulink/Simscape model. The preliminary evaluation shows that the plant has good performance in terms of hydrogen yields, reaching 5.37% kg_H2/kg_biomass, which is significantly higher than the typical value of a single process (approximately 3%). This finding demonstrates a good synergy between the biological and thermochemical biomass valorization routes. Moreover, thermal energy storage significantly improves the conversion plant’s independence, almost halving the energy demand from the grid.

1. Introduction

The sixth assessment report of the Intergovernmental Panel on Climate Change (IPPC) highlights the need to take action to mitigate climate change. In the report, global greenhouse gas emissions have not reached their peak yet, and reaching the temperature increase limit of +1.5 °C is expected to occur with a high degree of confidence. This confirms how the actions adopted so far to reduce CO₂ emissions have not been effective, and radical measures are required to keep the temperature as low as possible [1,2].

In this perspective, novel concepts are emerging in the energy field. First, bioenergy is increasingly relevant for the sustainable production of bio-based fuels and energy carriers [3,4,5,6]. Several paths can be followed to convert raw biomass into valuable products, and the choice of the best option strongly depends on its physical and chemical characteristics. However, the integration of more stages of valorization can improve the energy conversion of feedstock [4,5,6]. Furthermore, since biomass carbon dioxide emissions can be considered neutral along their life cycle [7,8,9], bioenergy, combined with carbon capture and storage (BECCS), is a potential way to significantly reduce the emissions, potentially achieving an overall carbon negative process [7,8,9].

Another main issue for the energy transition is the production of power from non-programmable renewable energy sources. The installed capacity of these conversion plants is required to increase considerably, according to the energy transition pathway [10], and this growing penetration requires the definition of strategies to manage the demand-production mismatch [11,12,13]. Electrochemical batteries are a potential solution for local and daily energy storage, but other solutions are required for a longer storage period [14,15]. From this perspective, the power-to-X paradigm has been recognized as an effective strategy. Indeed, it allows storing energy for long periods by means of the production of stable energy carriers, and it also allows the linking of different energy sectors.

Among the energy carriers, hydrogen is one of the most interesting due to its potential for decarbonization. Its main advantages are as follows: (i) The absence of carbon dioxide emissions during its use. (ii) The flexibility to be used in different applications such as light- and heavy-duty transport [16], rail mobility, heat and electricity production, and possible use in other sectors such as the chemical industry for the production of fertilizers or polymers [17] and other hard to abate processes.

In the last few years, the topic of bio-based energy carrier production has been investigated in several studies. In particular, the integration of different processes to maximize the exploration of energy potential from input biomasses emerges as a trend from the literature analysis. Trieb et al. [18] explored the production of liquid fuel by an integrated conversion process for the upgrading of waste biomass, powered both by non-programmable renewable energy and electricity provided by an internal combustion engine fueled with biogas, reaching a conversion efficiency of 53%. Poluzzi et al. [19] analyzed the recent studies on biomass upgrading via gasification-based pathways, evaluating the results through power-to-X and power-to-H₂ concepts, highlighting the need for more detailed analysis. The Technical University of Denmark, in collaboration with Aalborg University, proposed different studies [3,20,21,22] where the flexible operation of a biomass energy was upgraded into a methanol plant. They developed both a 75 kW two-stage reactor and an integrated numerical model for the simulation of the overall plant, which can produce both methanol (in case of local renewable energy surplus) and electricity (in case of peak demand from the grid), according to a flexible transition from one operation to the other. They found a maximum overall efficiency of 70.5% achieved by including a complete methanol production process, while the efficiency in the case of electricity production is limited to 37%. Moreover, the main challenge highlighted in the study consists of the capability to operate the solid oxide fuel cell (SOFC) using cleaned pyrolysis gas. In fact, several issues arise due to tars and hydrocarbons affecting the SOFC’s durability. The integration of pyrolysis and sorption-enhanced gasification has been analyzed in [23], where the goal of the plant is the production of both hydrogen and drop-in biofuels from softwood. In this work, an Aspen Plus model is used to investigate the impact of some process parameters, such as pyrolysis temperature, Steam/Biochar, and Sorbent/Biochar. These results showed how the pyrolysis temperature affects the product distribution while the other parameters affect the energy conversion efficiency. Moreover, the article highlights that process integration leads to improved mass conversion yield and increases overall energy efficiency by up to 10%.

Regarding wet biomasses, anaerobic digestion (AD) is a widely diffused process for their energy conversion. However, it has some limitations in converting waste biomass since microorganisms have poor degradation efficiency with specific biomass components [24]. For this reason, some studies have analyzed the integration of the incomplete exploitation of biomass energy potential. In [25], the integration of AD and gasification has been evaluated with the goal of maximizing the overall efficiency of the process to produce gaseous fuel (biogas from AD and syngas from gasification). In [26], a life cycle analysis of the co-gasification of sewage sludge, coming from an anaerobic digestion system, and woody biomass has been performed, showing how the synergy of the system can increase the energy recovery up to 24% compared to the separate process. In [27], a comparison between double-stage AD and single-stage AD coupled with the pyrolysis of digestate has been performed. Their results show how the coupling of AD with pyrolysis increases the energy yield to 6.1 MJ/kg_VS (kg of volatile substance), while the double-step digestion only yields 2.6 MJ/kg_VS.

The literature review has shown a lack in the study of the enhancement of hydrogen production from the AD by its coupling with other processes and still requires further insights. From this perspective, the aim of this paper is then to explore an innovative integrated bio-thermochemical route to produce a high purity hydrogen stream from wet residual biomass and, in particular, to analyze the mass and energy yields and the theoretical energy outputs and efficiencies. Moreover, in order to evaluate the plant’s performance in an energy transition scenario, a hybrid power supply is considered. The plant is powered by a photovoltaic system (PV), a thermal energy storage (TES) system, and the electric grid. Particular emphasis is given to the evaluation of the power demand of the plant and the power source split to understand the advantages and impacts of their integration in the plant supply mix, with the aim of limiting the energy withdrawn by the grid.

In order to obtain high purity hydrogen, innovative biomass by-product upgrading processes, such as electrified steam reforming and a membrane reactor, are included in the plant. A Simulink/Simscape model is developed for the preliminary evaluation of the overall process performance characteristics in terms of hydrogen production, global energy and conversion efficiency, and CO₂ emission comparison between the different scenarios.

The paper is structured as follows: Firstly, information about the methodology considered is provided, along with a description of the plant, feedstock characteristics, and assumptions. In the results section, three different case studies about the plant operation are described, and the main findings are reported. Finally, in the discussion section, a comparison between the three cases is carried out, highlighting the major contributions of the study.

2. Materials and Methods

2.1. Plant Description

The plant aims at producing hydrogen while maximizing the exploitation of available residual biomasses by integrating several thermochemical processes, such as anaerobic digestion (AD), pyrolysis (Py), oil reforming (P-Ref), and syngas reforming (Ref). The performance parameters of the proposed plant were evaluated through a numerical model developed in the MatLab/Simulink/Simscape environments.

As shown in Figure 1, the biomass enters first in the AD, where it produces a biogas composed mainly of carbon dioxide and methane. After a hydraulic retention time of 41 days, the remaining solid part is transferred to a dryer and then to a pyrolizer, where a fast pyrolysis at 500 °C occurs. The three products of pyrolysis follow different routes. The solid part (char) goes into a burner, where its chemical energy is converted into heat to supply the energy needed for drying the digestate and maintaining the pyrolysis process. The liquid part (bio-oil) is composed of two main parts: an organic fraction, which can be suitable for the production of bio-based fuels, and an aqueous fraction. The gaseous part (pyro-syngas) goes into a reformer, together with the other gaseous streams coming from AD and P-Ref, where a hydrogen-enriched syngas and a CO₂-enriched purge gas are obtained. Finally, a Pd-catalytic membrane separates high purity hydrogen from the remaining part of the syngas.

From an energy point of view, the system is powered by the chemical energy of the residual biomass and external electricity. Electric power is obtained from a PV plant, which is supported by the grid to ensure the continuous operation of the plant. The electricity powers up the compressor upstream of the catalytic membrane, and it can also be converted to supply thermal energy to the anaerobic digester, pyrolizer, and the two reformers.

To increase the energy independence of the plant from the grid, a TES is included. The role of the TES is to maximize the exploitation of the PV, converting the electricity surplus into heat that can be later used to supply the thermal energy demand of the plant.

Details of the component models are reported in the Appendix A. The pyrolysis [28,29] and PV models have been validated in comparison with experimental data in previous works [30]. The AD and membrane reactor performance parameters have been assumed from the literature studies, while the reforming model developed in MatLab is validated in this work, as reported in the results section.

Three different scenarios are compared in this work. In Scenario 1, the whole plant is powered only by the grid. This scenario is taken as a reference condition for comparison with the plant powered by renewable energy. In Scenario 2, the plant demand is supplied not only by the grid but also by a photovoltaic system. Finally, in Scenario 3, a TES supports the system’s operation by supplying heat energy stored from the surplus of the PV system. Moreover, waste heat recovery is also explored. There are three different sources: the cooling of hydrogen-rich syngas before the condensation of the membrane reactor, the bio-oil latent heat [31], and the cooling process of the flow at the outlet of the membrane reactor. These heat fluxes are used in the plant for the steam generator’s pre-heating. Furthermore, the demand for energy from the pyrolysis reactor is self-produced by burning the biochar, which has a low heating value of approximately 28 MJ/kg, according to [31].

The system design is based on the pyrolysis reactor. In fact, the pyrolysis model used in this paper was developed and validated for a lab-scale shaftless screw reactor presented by the authors in previous works [28,29]. The model is designed for an inlet mass flow of 1 kg/h, which is the constraint used to size the other components of the plant. The PV maximum power is set to satisfy twice the plant’s design maximum load to ensure good operation stability. The main parameters describing the design are reported in

Table 1. Main design parameters of the plant. The geometrical and operating parameters of the pre-reformer and reformer are taken from the reference [32].

Anaerobic Digester		Pyrolizer		PV System
Temperature [°C]	35 ± 2	length [m]	0.25	Panel power (W)	285
Specific Methane Production $\left[\raisebox{1ex}{${\mathrm{Nl}}_{{\mathrm{CH}}_4}$}\!\left/ \!\raisebox{-1ex}{${\mathrm{kg}}_{\mathrm{vs}}$}\right.\right]$	237	diameter [m]	0.02	Numbers of panels	63
Hydraulic Retention Time [Days]	41	Screw rotational speed [rpm]	45	System power (kW)	18
Organic Load Rate $\left[\raisebox{1ex}{${\mathrm{kg}}_{\mathrm{vs}}$}\!\left/ \!\raisebox{-1ex}{${\mathrm{m}}_{}{}^3·\mathrm{day}$}\right.\right]$	2	temperature [°C]	500
Pre-reformer		Reformer		TES
Length [m]	0.7	Length [m]	0.7	Capacity [kWh]	700
Diameter [mm]	12.7	Diameter [mm]	12.7	Initial capacity [kWh]	300
Temperature [°C]	378.05	Temperature [°C]	866	T max [°C]	1200
Steam/Carbon	1	Steam/Carbon	2	Heat loss in 24 h	<2%

, while a more detailed description of the model is presented in the Appendix A.

2.2. Feedstock

According to the EU Directive 2018/2001 [33] and recent scientific literature, only residual biomasses were investigated in this study. The advantages of the use of residual biomass are several: (i) no competition with the food and feed sectors; (ii) no additional emissions for their production; and (iii) the possibility to avoid post-treatment for their disposal.

In the proposed plant, a combination of two residual biomasses is taken as input: quinoa residues and wastewater sludge. The types of biomass and the operating conditions of the process are taken from the study proposed by Tayibi et al. [6]. Data on specific methane production, organic load, proximate analysis, and detailed analysis of the digestate are reported in

Table 2. Elemental and proximate analysis, polymeric composition, and low heating value of the biomasses. The proximate analysis provides the weight percentages (%wt) of the dry matter (DM) and volatile substances (VS). The characterization of the biomasses is taken from Ref. [6] to allow a direct comparison of the results of the present study.

Parameters	Quinoa Residues	Wastewater Sludge
DM (%wt)	90.1 ± 0.1	18.7 ± 0.1
VS (%wt,DM)	88.9 ± 0.3	79.6 ± 2.2
C (%wt)	43.3 ± 0.2	41.2 ± 0.2
H (%wt)	6.0 ± 0.1	6.2 ± 0.2
N (%wt)	0.2 ± 0.0	7.0 ± 0.2
S (%wt)	0.1 ± 0.0	0.6 ± 0.0
O (%wt)	40.5 ± 0.3	41.2 ± 0.5
Cellulose (%wt)	24.6 ± 0.4	-
Hemicellulose (%wt)	14.1 ± 0.5	-
Lignin (%wt)	7.0 ± 0.3	-
Ash (%wt)	10.0 ± 0.2	3.8 ± 0.4
Mass flow (kg/year)	2972	19,550
Low Heating Value (MJ/kg)	14.05	-

. The feedstock mixture of quinoa residues and wastewater sludge is divided in terms of volatile matter fraction, with 45% for quinoa and 55% for wastewater sludge, respectively.

2.3. Power Demand

The power demand is evaluated for each subsystem. It depends mainly on the working temperature and weather conditions, as reported in

Table 3. Power demand of the system components. The drying power is derived from [34], while the power of the other components is directly evaluated from the simulation.

Component	Power [W]
Pre-reformer	1700
Reformer	3000
Steam generation	1020
Compressor	364
Pyrolizer	263
Drying	3120
AD	Depending on weather conditions (temperature)
Storage	Depending on weather conditions (PV production)

. The power demand of the components is calculated as the output of the numerical model (described in the Appendix A) or taken from the literature.

2.4. KPIs of the Plant

In this section, the key performance indicators (KPIs) used to evaluate the performance of the plant are described. A literature analysis was made to support the selection and make the results easily comparable with other studies such as the work reported in Prestipino et al. [4], Gadsbøll et al. [21], and Bach et al. [5].

2.4.1. Hydrogen Yield

The main goal of the plant is the production of hydrogen. This makes the hydrogen yield an important parameter for evaluating the performance of the plant [4]. It can be easily calculated by integrating over the operating period the mass flow of the hydrogen (${\dot{m}}_{H_2}$) and of the biomass dry matter of (${\dot{m}}_{bio,dr{y}_{ }}$) (Equation (1)):

$$Y_{H_2,mass}=\frac{\dot{{\displaystyle \int }}{m}_{H_2} dt}{\dot{{\displaystyle \int }}{m}_{bio,dry} dt}.$$

(1)

2.4.2. CO₂ Emissions

The plant’s design and operation aim at achieving a minimum carbon footprint. From this perspective, it is crucial to evaluate the net CO₂ emissions of the system. The positive contribution is related to the carbon footprint of the electrical energy withdrawn from the grid, while the negative contribution is the CO₂ produced by biomass conversion and captured, and integrated over the whole operating period. In particular, the CO₂ considered is the carbon dioxide flow, which is separated through the membrane after the reformer and captured. In this work, the energy consumption and related CO₂ emissions of the transportation and storage of the captured carbon dioxide are not considered. However, the potential carbon negativity of the downstream process is accounted for in order to give a perspective on the potential of the process. The CO₂ emitted due to the combustion of char is instead considered neutral, and therefore it is not accounted for in the equation. The footprint of the system is evaluated in Equation (2). In the present calculations, the specific CO₂ emission by the grid was taken to be equal to 213.4 $\frac{{\mathrm{g}}_{{\mathrm{CO}}_2}}{\mathrm{kWh}}$, according to the current Italian energy mix [35]. For the emission related to the life cycle assessment (LCA) of the PV system, a specific CO₂ emission of 48 $\frac{{\mathrm{g}}_{{\mathrm{CO}}_2}}{\mathrm{kWh}}$ is considered according to [36].

$$m_{C{O}_2,tot}=e_{C{O}_2,grid}·E{n}_{grid}+e_{C{O}_2,PV}·E{n}_{PV,tot}-{\displaystyle \int }{\dot{m}}_{C{O}_2,fluegas}dt ,$$

(2)

where:

• $e_{C{O}_2,grid}$ is the specific CO₂ emission of the electricity in the grid;
• $E{n}_{grid}$ is the yearly electricity withdrawn from the central grid;
• $e_{C{O}_2,PV}$ is the specific CO₂ emission of the electricity of the PV;
• $E{n}_{PV,tot}$ is the yearly electricity production from the PV;
• ${\dot{m}}_{C{O}_2,fluegas}$ is the carbon dioxide mass flow in the flue gas after reforming.

2.4.3. Plant Efficiency

The overall efficiency of the plant (Equation (3)) is calculated as a direct measure of the biomass conversion effectiveness [4,21]. As can be observed in Equation (3), both the energy from the grid and the chemical energy of the residual biomasses are taken as inputs. The energy output of the system consists of the chemical energy of the hydrogen produced, the organic fraction of the bio-oil, as well as the residual energy surplus stored in the TES.

The $LH{V}_{H_2}$ is assumed to be equal to 33.3 $\left[\raisebox{1ex}{$\mathrm{kWh}$}\!\left/ \!\raisebox{-1ex}{${\mathrm{kg}}_{{\mathrm{H}}_2}$}\right.\right]$ [37].

The $LH{V}_{Oi{l}_{}}$ is assumed to be equal to 6.3 $\left[\raisebox{1ex}{$\mathrm{kWh}$}\!\left/ \!\raisebox{-1ex}{${\mathrm{kg}}_{\mathrm{Oil}}$}\right.\right]$ [38].

$${\eta }_{ }=\frac{m_{H_2}·LH{V}_{H_2}+E_{stored ,TES}+m_{oil}·LH{V}_{oil}}{E_{ee}+m_{quinoa}·LH{V}_{quinoa}}$$

(3)

where:

• $m_{H_2}$ is the yearly hydrogen mass production;
• $LH{V}_{H_2}$ is the low heating value of hydrogen;
• $E_{stored,TES}$ is the difference between the final and initial energy content in TES;
• $m_{oil}$ is the yearly oil organic fraction mass production;
• $LH{V}_{oil}$ is the low heating value of the organic fraction of the oil;
• $E_{ee}$ is the energy produced by PV or absorbed from the grid;
• $m_{quinoa}$ is the yearly quinoa mass feed (only quinoa is accounted for since the sludge does not have a proper heating value);
• $LH{V}_{quinoa}$ is the low heating value of quinoa.

2.4.4. Total Specific Energy Consumption (TEC) for H2 Production

Another key parameter is the energy consumption for hydrogen production. The total energy contribution is considered, accounting also for the thermal energy content of the biomass. This value can be calculated in terms of the mass (Equation (4)) and volume (Equation (5)) of the hydrogen produced.

$$TE{C}_{mass}{}_{ }=\frac{m_{quino{a}_{ }}·LH{V}_{quinoa}+E_{ee}}{m_{H_2,tot}}$$

(4)

$$TE{C}_{vol}=\frac{m_{quino{a}_{ }}·LH{V}_{quino{a}_{ }}+E_{ee}}{Vo{l}_{H_2,tot}}$$

(5)

where:

• $E_{ee}$ is the energy produced by PV or absorbed from the grid;
• $m_{quinoa}$ is the yearly quinoa mass feed (only quinoa is accounted for since the sludge does not have a proper heating value);
• $LH{V}_{quiona}$ is the low heating value of biomass;
• $m_{H_2}$ is the yearly hydrogen mass production;
• $Vo{l}_{H_2,tot}$is the yearly hydrogen normal volume production.

2.4.5. Electrical Specific Energy Consumption (EEC) for H2 Production

Another interesting KPI is the specific energy consumption, which accounts only for electrical energy. Indeed, electrical energy is the only primary energy input in the system since the chosen feedstock is a mixture of residual biomasses. This parameter allows the comparison of the system’s performance with that of other hydrogen production technologies, such as the electrolyzer. Moreover, this value can be calculated both in terms of mass (Equation (6)) and volume (Equation (7)) of the hydrogen produced as follows:

$$EE{C}_{mass}{}_{ }=\frac{E_{ee}}{{\displaystyle \int }{\dot{m}}_{H_2} dt} ,$$

(6)

$$EE{C}_{vol}=\frac{E_{ee}}{{\displaystyle \int }{\dot{Vol}}_{H_2} dt} .$$

(7)

2.4.6. Specific CO₂ Emissions

To generalize the results of the system, the specific value of the emission is calculated per unit mass of hydrogen produced. The values of the overall parameter evaluated in Equation (3) are divided by the total hydrogen production, as reported in Equations (8) and (9) [4], as follows:

$$e_{C{O}_2,mass}=\frac{e_{C{O}_2,grid}·E{n}_{grid}+e_{C{O}_2,PV}·E{n}_{PV,tot}-{\displaystyle \int }{m}_{C{O}_2,fluegas}dt}{{\displaystyle \int }{\dot{m}}_{H_2} dt} ,$$

(8)

$$e_{C{O}_{2,Vol}}=\frac{e_{C{O}_2,grid}·E{n}_{grid}+e_{C{O}_2,PV}·E{n}_{PV,tot}-{\displaystyle \int }{m}_{C{O}_2,fluegas}dt}{{\displaystyle \int }{\dot{Vol}}_{H_2} dt} .$$

(9)

where:

• $e_{C{O}_2,grid}$ is the specific CO₂ emission in the electricity of the grid;
• $E{n}_{grid}$ is the yearly electricity withdrawn from the central grid;
• ${\dot{m}}_{C{O}_2,fluegas}$ is the carbon dioxide mass flow in the flue gas;
• $e_{C{O}_2,PV}$ is the specific CO₂ emission of the electricity of the PV;
• $E{n}_{PV,tot}$ is the yearly electricity production from the PV;
• $m_{H_2}$ is the yearly hydrogen mass production;
• $Vo{l}_{H_2,tot}$ is the yearly hydrogen normal volume production.

2.4.7. Self-Consumption (SC)

As one of the most significant differences between the three scenarios is the contribution of renewable energy sources (RES), the system self-consumption (Equation (10)) is measured. This parameter can give an idea of the effectiveness of the exploitation of renewable energy.

$$SC=\frac{E{n}_{PV}+E{n}_{TES}}{E{n}_{tot}}$$

(10)

where:

• $E{n}_{PV}$ is the yearly photovoltaic electricity directly utilized by the system;
• $E{n}_{TES}$ is the yearly energy of TES utilized by the system;
• $E{n}_{tot}$ is the yearly energy consumption of the system.

3. Results and Discussion

3.1. Validation of the Reforming Model

Bio-oil is composed of several hydrocarbon compounds; however, only a few species are usually considered in the literature, such as acetic acid, ethylene glycol, and acetone [39]. The reforming section has been implemented according to the model proposed by Vagia et al. [39] and tested at a temperature ranging from 400 to 1300 K with a steam-to-carbon ratio (S/C) of six for validation against the results shown in [39].

In Figure 2, Figure 3 and Figure 4, the results of the validation analysis are reported. To prevent carbon deposition in the catalyst, usually the pre-reformer stage works with a steam-to-carbon ratio of at least two. Although the maximum deviation from the reference is 28%, if we consider the working temperature of the pre-reformer, the maximum deviation does not exceed 5%, as shown in Figure 2, Figure 3 and Figure 4. This is within the limits of the present analysis and has been considered good agreement between the behavior of the model and the reference.

3.2. Evaluation of the KPIs

The KPIs of the process plant are evaluated for the three different scenarios described in the methodology section. Most of them remain fixed since they are characteristics of the plant itself and do not depend on its operating conditions; they are reported in

Table 4. KPIs of the plant independent from the scenarios analyzed.

Performance Parameters
$m_{H_2,mass}$	$\left[\mathrm{kg}/\mathrm{year}\right]$	340
$Y_{H_2,mass}$	$[\%]$	5.37%
${\eta }_{ }$	$\left[{\%}_{}\right]$	18.91%
$TE{C}_{mass}{}_{ }$	$\left[\raisebox{1ex}{$\mathrm{kWh}$}\!\left/ \!\raisebox{-1ex}{${\mathrm{kg}}_{{\mathrm{H}}_2}$}\right.\right]$	315.17
$TE{C}_{vol}$	$\left[\raisebox{1ex}{$\mathrm{kWh}$}\!\left/ \!\raisebox{-1ex}{${\mathrm{Nm}}^3·{\mathrm{H}}_2$}\right.\right]$	28.12
$EE{C}_{mass}{}_{ }$	$\left[\raisebox{1ex}{${\mathrm{kWh}}_{\mathrm{ee}}$}\!\left/ \!\raisebox{-1ex}{${\mathrm{kg}}_{{\mathrm{H}}_2}$}\right.\right]$	192.35
$EE{C}_{vol}$	$\left[\raisebox{1ex}{${\mathrm{kWh}}_{\mathrm{ee}}$}\!\left/ \!\raisebox{-1ex}{${\mathrm{Nm}}^3·{\mathrm{H}}_2$}\right.\right]$	17.16

.

The efficiency of the conversion process in terms of energy consumption leads to an electrical specific energy consumption of 17.16 kWh/Nm³_H2, which is significantly higher than the value that can be achieved by an electrolyzer, characterized by a value of approximately 3–4 kWh/Nm³_H2 [40,41]. This is driven by the need to have several energy-intensive processes in order to obtain pure hydrogen from residual biomasses. Moreover, the plant produces not only hydrogen but also a crude oil fraction, which can be used for energy purposes after further upgrading to obtain drop-in fuels. On the other hand, the results achieved in hydrogen yields are remarkable (5.37%) compared to those of other similar conversion systems. For example, a maximum of 4.01% of mass hydrogen yield is obtained by the gasification system proposed in [4], with a much lower concentration of hydrogen purity, approximately 25% vol. Regarding the anaerobic digestion system, as reported in the review of M. Aziz [42], the hydrogen mass yield is always below 3%, significantly lower than the results of this article. This proves that only anaerobic digestion of the feedstock, which is the most suitable treatment for such wet residual biomasses, does not allow the exploitation of all the hydrogen potential, and the combination with a thermochemical treatment allows for good synergies. Indeed, the 55.5% of the total hydrogen production in the proposed plant design is due to the subsequent treatment of pyrolysis by-products, which allows for an increased hydrogen yield compared to the single AD [4], see Figure 5a. This synergy is also observed in other works that combine anaerobic digestion and pyrolysis. In fact, the mass yield of the system that combines anaerobic digestion of corn stover with alkaline pyrolysis reaches a hydrogen mass yield of about 25.9 mmoL/g, or about 5.2% [kg/kg] [43], comparable with the proposed approach. Our approach shows improvement when compared with the work proposed in [44], where a 3% hydrogen yield is reported for a two-stage reactor (pyrolysis and steam reforming) that processes a similar biomass (wheat straw).

Regarding the KPIs that are more variable among the different scenarios, the values are reported in

Table 5. KPIs of the plant-dependent from the scenarios analyzed.

Performance Parameters
		Scenario 0	Scenario 1	Scenario 2
$m_{C{O}_2,tot}$	$\left[\mathrm{kg}/\mathrm{year}\right]$	10,592	8536	5210
$e_{C{O}_2,mass}$	$\left[\raisebox{1ex}{${\mathrm{kg}}_{{\mathrm{CO}}_2}$}\!\left/ \!\raisebox{-1ex}{${\mathrm{kg}}_{{\mathrm{H}}_2}$}\right.\right]$	31.2	25.1	15.3
$e_{C{O}_{2,Vol}}$	$\left[\raisebox{1ex}{${\mathrm{kg}}_{{\mathrm{CO}}_2}$}\!\left/ \!\raisebox{-1ex}{${\mathrm{Nm}}^3·{\mathrm{H}}_2$}\right.\right]$	2.78	2.24	1.37
$SC$	[%]	0	19%	42.8%

, where the key role of the TES is evident. In fact, all values increase dramatically with the introduction of the TES into the system. The emission value is decreased to about 75% of the reference scenario for the case with PV only and drops further to 43% of the reference case in the configuration with PV and TES. As a matter of fact, the self-consumption of Scenario 2 is increased significantly (from 19% to almost 43%), confirming the positive effect of the TES in maximizing the non-programmable RES exploitation in the case studied.

The energy fractions from the different sources are shown in Figure 5b. It is evident that for all the scenarios, the energy from the grid has a major contribution that is reduced to a minimum of 60% with both PV and TES implemented. The PV system powers the plant for about 18% of the overall energy demand, while the TES contributes an even more significant percentage (up to 22%).

4. Conclusions

In this work, an integrated thermochemical plant from residual biomass for the poly-generation of energy carriers, with particular focus on hydrogen, has been evaluated by a preliminary energy and power demand analysis. The effect of the energy supply system is evaluated in terms of energy conversion efficiency, carbon dioxide emissions, and hydrogen production.

The main findings of this work can be summarized according to the following points:

• TES is a key component to achieving a larger self-consumption path for the plant and reducing the carbon footprint of the hydrogen production, reaching a 42.8% self-consumption (SC) value;
• The proposed plant can achieve a specific electrical energy consumption of 17.16 $\left[\raisebox{1ex}{$\mathrm{kWh}$}\!\left/ \!\raisebox{-1ex}{${\mathrm{Nm}}^3·{\mathrm{H}}_2$}\right.\right]$, which is higher if compared to current electrolyzer technologies but can be obtained by valorizing residual low-energy biomasses.
• There is a good synergy in the plant process, reaching a hydrogen yield of 5.37%, demonstrated also by the balance between the hydrogen recovery potential from biogas and pyrolysis products (respectively 44.5% and 55.5%).