Improvement of Self-Consumption Rates by Cogeneration and PV Production for Renewable Energy Communities
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe paper analyzes the possibility of increasing the self-consumption rate of electricity in an energy community located in Villafranca Padovana (Veneto, Italy). A 500 kWe biogas cogeneration system and a 64.5 kW photovoltaic system were considered in the authors' analysis.
The subject of the paper is important and deserves further study, but significant revisions are needed to improve clarity, organization, and scientific rigor.
1.The research question is not clearly defined, making it difficult for readers to understand the study’s primary objectives and novelty. The manuscript should explicitly state the research problem it aims to address and highlight its unique contributions compared to existing studies.
2.Lines 181-183: It is not clear from the manuscript whether the 500 kW biogas cogeneration system exists in the energy community or has been proposed.
3.Lines 145-146: Thermal energy demand (heat consumption) is an essential condition for a cogeneration system to be efficient. How do you justify the almost constant electricity production in Figure 1 (a) (winter/summer; night/day) if you have not taken into account the thermal energy demand in the energy community?
4.The results presented in Figures 4-10 are not based on a solid mathematical model. It is not entirely clear from the section "2. Materials and Methods" what methods were used for the study and what materials were used? Please be more specific.
5.Equations (1)-(4) should be moved to the section "2. Materials and Methods", and in the section "3. Results" only the results obtained using these equations should be given.
6.Lines 468-472: What are the benefits to the energy community by adding new residential members? You should justify with data, not just discuss in general.
Author Response
Comments 1:
The research question is not clearly defined, making it difficult for readers to understand the study’s primary objectives and novelty. The manuscript should explicitly state the research problem it aims to address and highlight its unique contributions compared to existing studies.
Response 1:
The objective of this paper is to quantify the variation in Self-Consumption Rate (SCR) and Self-Sufficiency Rate (SSR) (in %) for different production mixes of biogas and PV. The novelty of this study lies in analyzing these variations based on different production-to-consumption ratios. While the literature widely acknowledges that biogas can achieve significantly higher self-consumption than PV, no studies have specifically examined how SCR and SSR change as P/C ratio (“total annual production” / ”total annual consumption”) varies. For instance, when P = C, the difference in the self-consumption rate between a REC powered entirely by biogas and one powered entirely by PV is 40 percentage points. However, when P/C < 0.2, all mixed biogas-PV RECs achieve a self-consumption rate above 90%. As a result, the SCR gap between different REC configurations (mixed PV and biogas) shrinks from 40 percentage points to less than 10. In this paper, we have further clarified this aspect in greater detail. These predictions can support the design of RECs based on the characteristics of available biogas plants and the surface area potentially available for PV installations within the community. In practice, total consumption and total renewable production are often subject to specific constraints and are not necessarily equal (and therefore P/C is not necessarily = 1).
We have specified these points in sections “1. Introduction”, “4. Discussion” and “5. Conclusions”.
Comments 2:
Lines 181-183: It is not clear from the manuscript whether the 500 kW biogas cogeneration system exists in the energy community or has been proposed.
Response 2:
The REC is based on the enhancement of an existing biogas system in cogeneration configuration. The electrical power of the plant is shifted from 300 kW to 799 kW adding a new CHP plant of 500 kW. Only the 500 kW CHP biogas plant has been included then in the REC for energy production (the pre-existing 299 kW plant is not included).
The electricity produced by the new CHP plant is totally transferred to the grid and it can be shared with the members of the community. This new plant has been recently installed and therefore its actual electricity production profile is not completely and extensively available. Anyway, we have combined measured values of power supplied by pre-existing biogas plant with the available data of the new plant to foresee the hourly electricity production for the new CHP plant of 500 kW in relation to a whole reference period (one year).
This description has been added in the paper in subsection “2.3. The REC of Villafranca Padovana”.
Comments 3:
Lines 145-146: Thermal energy demand (heat consumption) is an essential condition for a cogeneration system to be efficient. How do you justify the almost constant electricity production in Figure 1 (a) (winter/summer; night/day) if you have not taken into account the thermal energy demand in the energy community?
Response 3:
In the new version of the paper, at the end of section “1. Introduction”, we have specified that the efficiency of a CHP system is strictly related to simultaneous use of electricity and heat, but in biogas plants the production is very much tied to availability of feedstock supply. In our case study the aim is to maximize the operation of the biogas plant and related CHP by exploiting the large availability of feedstock (organic waste) by the plant owner and nearby companies. Therefore, the operational strategy is to keep the biogas plant working at full production, feeding the electricity into the grid and using the heat locally.
Indeed, the Italian rules for biogas plant in RECs foresee that the thermal energy produced is recovered and is primarily self-consumed on site, to serve the company processes, or fed into an efficient district heating system. However, only the electricity produced and fed into the grid will be incentivized within the REC. Therefore, thermal production of CHP system is used as heating for the livestock systems but does not drive the cogenerator's production.
To recap and summarize these aspects, in subsection “2.3. The REC of Villafranca Padovana”, we have further specified that the full production management of the biogas plant allows to maximize the operation of the CHP and its related electrical and heat production for the following reasons:
- electrical production is fed into the grid and sold;
- a large supply of organic waste for the feedstock of biogas plant is available by the plant owner and nearby companies;
- thermal production is used as heating for the livestock farm systems.
Comments 4:
The results presented in Figures 4-10 are not based on a solid mathematical model. It is not entirely clear from the section "2. Materials and Methods" what methods were used for the study and what materials were used? Please be more specific.
Response 4:
We have specified that the mathematical model used for this study was depicted in previous work [Petrovich et al.] extensively. The method is highly precise because it is based on measured production and consumption curves with a 15-minute frequency. Anyway, we have summarized and defined the methods and the main KPIs implemented to evaluate the REC performances also in this paper (sections 2, 2.1 e 2.2).
Comments 5:
Equations (1)-(4) should be moved to the section "2. Materials and Methods", and in the section "3. Results" only the results obtained using these equations should be given.
Response 5:
Equations (1)-(4) have been moved to section "2. Materials and Methods" (and in particular in sub-section “2.2. The KPIs”), where we have explained the equations as follows:
Consumption of the entire REC is calculated as the sum of the consumptions of all members of the REC, and it corresponds also to total direct self-consumption plus total withdrawal of all the members (Ctot = SCdirtot + Wtot).
Production of the entire REC is calculated as the sum of the productions of all members of the REC, and it corresponds also to total direct self-consumption plus total injection of all the members (Ptot = SCdirtot + Ftot).
Considering a period of one day, as in Figure 6 in the “Results” section, SCR and SSR, previously defined, can be calculated for every day of the year as below:
SCRday = (SCdirtot,day + SEtot,day)/Ptot,day;
SSRday = (SCdirtot,day + SEtot,day)/Ctot,day.
Comments 6:
Lines 468-472: What are the benefits to the energy community by adding new residential members? You should justify with data, not just discuss in general.
Response 6:
In subsection “3.4. REC Improvement”, section “4. Discussion” and section “5. Conclusions”, we have specified that the self-consumption of the energy community (and the related incentives) increases by adding new residential members.
Since the production exceeds the community's consumption, it is advantageous to involve additional consumers to increase total self-consumption and further enhance the value of the produced electricity leveraging the Italian incentives. Including 550 residential members (apartments) into the actual REC, the community production equals community consumption (the Net ZEC point) because in the reference configuration there was a difference between production and consumption of about 1200 MWh and the average annual electricity consumption of an apartment in Italy is 2184 kWh, thus (2185 kWh * 550 = 1201 MWh).
In this way, the total self-consumption rate, and thus the shared energy incentivized by Italian regulations, was increased from 60% to 84%.
Reviewer 2 Report
Comments and Suggestions for AuthorsHere are my comments:
Make the research question/gaps clear as few bullet points in intro and then explain how your work cover/response these gaps. These gaps should be the direct result of your LR.
Just mentioning the tool as SIMUL-REC is not enough, open the applied method,constraint, optimization model (if applied), limitations, and reliability of the tool in enough detail.
Why these (KPIs)?
In result section, you present result. Any formula/etc should be explained in method. correct it.
In the end of the discussion add the limitation of your applied method.
Author Response
Comments 1:
Make the research question/gaps clear as few bullet points in intro and then explain how your work cover/response these gaps. These gaps should be the direct result of your LR.
Response 1:
While it is well established in the literature that RECs based on biogas production can achieve significantly higher self-consumption than those based on PV plants there are no studies, to the best of our knowledge, analyzing how the Self-Consumption Rate (SCR) and Self-Sufficiency Rate (SSR) change according to different production mixes of biogas and PV and according to the REC annual production/consumption variation.
The novelty of this paper lies in quantifying the variation in SCR and SSR (in %) for different production mixes of biogas and PV plant, depending on the REC (total annual) production-to-consumption ratio. The approach is an evolution of the one we already presented in our previous work [Petrovich et al.], extended to mixed renewable power sources. These predictions can support the design of RECs based on the characteristics of available biogas plants and the surface area potentially available for PV installations within the community. In practice, total consumption and total renewable production are often subject to specific constraints and are not necessarily equal (and therefore P/C is not necessarily = 1).
We have now specified this point in section “1. Introduction” and section "5.Conclusions".
Comments 2:
Just mentioning the tool as SIMUL-REC is not enough, open the applied method, constraint, optimization model (if applied), limitations, and reliability of the tool in enough detail.
Response 2:
We explained better in the paper the method we applied (we start from the 15-minute frequency production and consumption profiles and compute all the KPIs), also discussing the main methods in the literature (MILP, genetic algoritm, etc.) and and our parametric approach.
The limitations of the SIMUL-REC tool are related to the dependence of SCR and SSR on the production-to-consumption ratio. As a matter of fact, the approach and related results have not universal validity, but they remain valid until the production profile and the consumption profile of the RECs keep the same shape, varying magnitude.
This has been better explicited in the “introduction” and “materials and methods” sections.
Comments 3:
Why these (KPIs)?
Response 3:
This paper focuses on two main KPIs:
Self-Consumption Rate (SCR), because showing how much the power plants installed are locally exploited (low values of SCR involve that the power is mostly used outside the REC). This involves also lower impacts into the electric grid.
Self-Sufficiency Rate (SSR), because showing the degree of energetic independence of the REC (low values of SSR involve dependence on external and mostly fossil energy sources).
These two rates are the most used in literature, as also reported in the following pre-print: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4991932 (Assessment of Renewable Energy Communities: A Comprehensive Review of Key Performance Indicators).
Comments 4:
In result section, you present result. Any formula/etc should be explained in method. correct it.
Response 4:
We have specified that the mathematical model used for this study was extensively depicted in a previous work (reference [Petrovich et al.]). Anyway, we have now summarized and defined the main formulas and KPIs implemented to evaluate the REC performances also in this paper (sections 2, 2.1 e 2.2).
Comments 5:
In the end of the discussion add the limitation of your applied method.
Response 5:
The limitations of the approach based on the production-to-consumption ratio is that the results remain valid only when the total production curve and the total consumption curve do not change, varying the number of members.
This has been better explicited in the “introduction” and “materials and methods” sections.
Reviewer 3 Report
Comments and Suggestions for AuthorsAuthors are required to address the following technical comments:
The term "operational configurations" needs to be explicitly defined. Provide a clear explanation of the different scenarios analyzed, including the specific variables variations (e.g., load profiles, generation dispatch, etc.
The statement that "When total electricity production matches total electricity consumption, the self-sufficiency and self-consumption rates reach 80%" requires further justification. Explain the factors that prevent 100% rates in this ideal scenario. Are losses, grid interactions, or specific operational constraints accounted for?
The claim of "0.5 percentage points increase for every percentage point rise in cogeneration output mix" should be supported by statistical significance testing. A sensitivity analysis showing the robustness of this relationship to variations in input parameters is also recommended.
While the study mentions "Integrating residential consumers into the REC increases these rates to 84%," provide a more detailed analysis of the impact. Include information on the number of residential consumers, their load profiles, and the methodology used to calculate the increase.
Author Response
Comments 1:
The term "operational configurations" needs to be explicitly defined. Provide a clear explanation of the different scenarios analysed, including the specific variables variations (e.g., load profiles, generation dispatch, etc.
Response 1:
The term “operational” in the abstract was misleading. Therefore, we have removed it, and we have better explained the term “configuration” of the REC in the introduction (i.e. mix of members and production technologies of the REC). Moreover, we have reformulated some sentences of the abstract to provide a better explanation of the different scenarios analysed.
Comments 2:
The statement that "When total electricity production matches total electricity consumption, the self-sufficiency and self-consumption rates reach 80%" requires further justification. Explain the factors that prevent 100% rates in this ideal scenario. Are losses, grid interactions, or specific operational constraints accounted for?
Response 2:
We have removed this statement from the abstract to make clearer the description of the scenarios. Anyway, the statement about the self-sufficiency rate and self-consumption rate which reach 80% when total electricity production is equal to total electricity consumption is now discussed in depth at section “3.3. The SCR-SSR-PC Curve” of the paper.
We have specified that self-consumption rate = self-sufficiency rate = 100% can be reached only if consumption profile matches exactly (each hour) with the production profile, which is theoretically possible but not feasible in practice with non-programmable energy sources, such as PV, wind, etc., and without the use of storage systems.
Comments 3:
The claim of "0.5 percentage points increase for every percentage point rise in cogeneration output mix" should be supported by statistical significance testing. A sensitivity analysis showing the robustness of this relationship to variations in input parameters is also recommended.
Response 3:
These results (derived from the curve in Figure 9) are now compared with those obtained using a national average curve for non-domestic users (GSE curves, described in reference [GSE, 2022]), instead of the actual consumption profiles of the Villafranca Padovana members of the REC. The difference between the two curves is within 3 percentage points, indicating good agreement. This demonstrates that, on average, these results are valid for non-domestic members. The validity depends on PV production curves and geographical irradiation conditions, which have been calculated for Northern Italy. These calculations and observations have been included in the paper (see Figure 9).
Comments 4:
While the study mentions "Integrating residential consumers into the REC increases these rates to 84%," provide a more detailed analysis of the impact. Include information on the number of residential consumers, their load profiles, and the methodology used to calculate the increase.
Response 4:
We reported the number of residential members in the abstract (550 apartments).
The description of their consumption profile is available at the end of subsection “2.3. The REC of Villafranca Padovana”.
The methodology used to calculate the increase is presented at the beginning of the subsection “3.4. REC Improvement”.
Several simulations were carried out to improve the reference REC and increase the self-consumption and self-sufficiency rates. To this end, the first step was to add members to the REC to increase the total consumption and reach Ctot = Ptot (in the reference configuration, there was a difference of (Ptot - Ctot) = 1203 MWh). Residential members were chosen for inclusion in the REC because householders can be involved in an easier way than companies. The standard profile provided by GSE was adopted as their consumption profile. Since the average annual electricity consumption of an apartment in Italy is 2184 kWh [Branchetti et al.], the addition of 550 apartments was simulated (i.e., addition of about 1.2 GWh). This adjustment achieves Ptot = Ctot and SCR = SSR = 83.9%.
Reviewer 4 Report
Comments and Suggestions for AuthorsThe reviewers have raised the following concerns:
1. The paper's research content is already well-covered in existing literature. The authors need to clearly articulate their novel contributions rather than providing a general description of their work.
2. Figures 1 through 3 require more detailed explanations.
3. Technical abbreviations are used inconsistently throughout the paper—for example, "PV" alternates between "Photo-Voltaic" and "Photovoltaic."
4. The paper lacks comparative analysis with existing methods. Performance comparisons with traditional approaches should be presented and summarized in a table.
5. The limited number of equations in the paper raises concerns about its theoretical contributions.
Author Response
Comment 1:
The paper's research content is already well-covered in existing literature. The authors need to clearly articulate their novel contributions rather than providing a general description of their work.
Response 1:
The objective of this paper is to quantify the variation in Self-Consumption Rate (SCR) and Self-Sufficiency Rate (SSR) (in %) for different production mixes of biogas and PV. The novelty of this study lies in analyzing these variations based on different production-to-consumption ratios. While the literature widely acknowledges that biogas can achieve significantly higher self-consumption than PV, no studies have specifically examined how SCR and SSR change as P/C (“total annual production”/ ”total annual consumption”) varies. For instance, when P = C, the difference in the self-consumption rate between a REC powered entirely by biogas and one powered entirely by PV is 40 percentage points. However, when P/C < 0.2, all mixed biogas-PV RECs achieve a self-consumption rate above 90%. As a result, the SCR gap between different REC configurations (mixed PV and biogas) shrinks from 40 percentage points to less than 10. In this paper, we have further clarified this aspect in greater detail. These predictions can support the design of RECs based on the characteristics of available biogas plants and the surface area potentially available for PV installations within the community. In practice, total consumption and total renewable production are often subject to specific constraints and are not necessarily equal (and therefore P/C is not necessarily = 1).
We have specified these points in sections “1. Introduction”, “4. Discussion” and “5. Conclusions”.
Comments 2:
Figures 1 through 3 require more detailed explanations.
Response 2:
We have redefined the section and we have explained that the Figure 1 through 3 represent the average profiles during the day obtained starting from an actual or synthetic profile (1 hour frequency) for one year. This was averaged for every hour of the day (e.g. at 3 pm the value is the average of 365 values at 3 pm).
Comments 3:
Technical abbreviations are used inconsistently throughout the paper—for example, "PV" alternates between "Photo-Voltaic" and "Photovoltaic.".
Response 3:
We replaced all "Photo-Voltaic" and "Photovoltaic" words with “PV”, except for the first citation in the abstract and in the text of the paper.
Comments 4:
The paper lacks comparative analysis with existing methods. Performance comparisons with traditional approaches should be presented and summarized in a table.
Response 4:
We have explained more in depth and compared our approach with other approaches at the beginning of the section “2. Materials and Methods”, also adding a table to summarize the traditional approaches (Table 1).
Comments 5:
The limited number of equations in the paper raises concerns about its theoretical contributions.
Response 5:
We have specified that the mathematical model used for this study was extensively depicted in a previous work (reference [Petrovich et al.]). Anyway, we have summarized and defined the methods and the main KPIs implemented to evaluate the REC performances also in this paper (sections 2, 2.1 e 2.2).
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsMy comments have been addressed.
Author Response
Comments 1: My comments have been addressed.
Response 1: Very well. Thank you for your feedback.
Reviewer 3 Report
Comments and Suggestions for AuthorsThanks for your replies on my queries.
Comment:
Section 2.
Line 183 - The algorithms used to optimize these KPIs can be either exact or heuristic a “feasible” rather than optimal solution.
Line 188 - The approach adopted in this paper is not to optimize one or two KPIs, but rather to explore how these indicators depend on the REC’s production-to-consumption ratio and on the renewable energy mix, by conducting a sensitivity analysis.
Comment - Considering these descriptions, I suggest to include a flow chart of used algorithm / optimization process, which is adopted in this paper.
Author Response
Comments 1:
The English could be improved to more clearly express the research.
Response 1:
We revised the language, with particular attention to the sections integrated during the first revision.
Comments 2: Section 2.
Line 183 - The algorithms used to optimize these KPIs can be either exact or heuristic a “feasible” rather than optimal solution.
Line 188 - The approach adopted in this paper is not to optimize one or two KPIs, but rather to explore how these indicators depend on the REC’s production-to-consumption ratio and on the renewable energy mix, by conducting a sensitivity analysis.
Comment - Considering these descriptions, I suggest to include a flow chart of used algorithm / optimization process, which is adopted in this paper.
Response 2:
We have added a flow chart of used algorithm / methods, which are adopted in this paper.
We have located it at the end of subsection “2.2 Calculation methods and KPIs”, after the discussion of applied methodology and related KPIs.
Reviewer 4 Report
Comments and Suggestions for Authorsno more comments
Author Response
Comments:
no more comments
Response:
We included a flow chart of used algorithm / methods, to better explain the methodology applied in this paper for the calculation and assessment of REC’ KPIs.
We improved the overall writing style of the text.
