Fully Solar Residential Energy Community: A Study on the Feasibility in the Italian Context ^†

Abstract

Expanding the installation and use of renewable energy sources will help Europe reach its energy and climate goals. Additionally, users of small-scale photovoltaic systems will be essential to the energy transition by forming renewable energy communities (RECs). This paper offers a techno-economic analysis of the Italian REC incentive system and a suitable business model to encourage residential photovoltaic and battery installations and lower electricity costs. In this paper, we present a community model that includes a set number of prosumers, a growing number of consumers, and various configurations and management strategies for photovoltaic (PV) and battery systems. Key elements of novelty include (i) the implementation of a fully-solar REC with PV and storage under the Italian incentive scheme, (ii) the introduction a of novel centralized BESS control strategy based on firm generation that maximises energy sharing while minimising its grid impact, (iii) the economic profitability analysis of the PV and storage system for consumers and prosumers when different BESS control strategies are applied. The simulation results show that energy performance increases if a centralized battery management strategy is activated and more consumers join the community. In addition, the proposed business model shows that the best profitability is achieved when there are as many consumers as prosumers. Most importantly, the approach was extended to the extreme case of a “fully solar-powered” community, demonstrating that the REC model is viable even with the current PV and battery costs. Finally, we show that fully solar-powered communities can be easily implemented where homeowners have enough surface for PV installation and purchase a central battery through crowdfunding.

1. Introduction

The increase in renewable energy sources (mainly PV and wind) creates a new paradigm in the energy system, with consumers becoming prosumers, able to generate and use their electricity on site and share it with peers or sell it in a local market by becoming members of the so-called renewable energy communities (RECs) [1,2]. The rapid growth of distributed energy resources challenges the real-time balance between electricity supply and demand, necessitating flexibility, grid support services, and suitable market design. RECs could also peak-shave the grid load during times of high production/demand [3], mitigate the overvoltage events [4], reduce the losses [5,6], and provide other services [7], among which frequency stabilisation [8]. Peer-to-peer (P2P) energy trading among residential prosumers in a REC was presented considering different configurations (i.e., centralized or decentralized [9]), and different services (i.e., hour-ahead market, increasing local DER transactions and BRP-based reserve mechanism [10]). However, the role of energy communities extends beyond the energy domain and includes local job creation, economic development, and the generation of a sense of belonging, thereby improving the well-being of local citizens [11,12,13].

In Italy, renewable energy communities (RECs) incentivize energy sharing among members with economic benefits [14], aiming to accelerate the adoption of residential hybrid renewable energy systems, reduce natural gas imports, and lower electricity costs. Additionally, a 50% tax rebate over 10 years promotes the installation of residential renewable energy systems while decreasing battery costs, making behind-the-meter storage combined with rooftop solar PV increasingly viable from the economic standpoint [15].

In addition, RECs are expected to help reduce energy poverty, as consumers who are unable or unwilling to install PV systems can still reduce their electricity bills thanks to the government incentives.

The first Italian renewable energy community (REC), established in December 2020 under the Italian Law 8/2020, is presented in [16]. The REC includes both residential and public buildings, and the results show that 35–54% of the energy demand can be met by self-consumption (SC) of the PV production, 16% of which comes from the energy shared in the REC. In [17], a REC with 17 residential buildings located in Catania is analyzed, and it is shown that centralized PV systems produce the best economic results, with up to 34% emissions reduction. The work performed in [18] instead shows promising PV investment payback times (7.9–8.5 years) for a residential REC in northern Italy, considering different setups (with or without storage) and policies (priority to SC or energy sharing). RECs can also improve the self-production (SP) of multi-housing apartments, such as the one analysed in [19], located in Cagliari. Combined with other buildings, the SP increase is around 26%, and the CO₂ emissions decrease by 23%. In [20], the electricity bills of a multi-family housing building in Pisa are reduced by 10–20%, while in [21], the authors propose a “power-sharing model” for sharing renewables and other energy services within communities, suitable at both the building and community-levels. In industrial and commercial contexts, such as the ones analysed in (Cagliari) [22] and (Bolzano) [23], RECs can reduce the annual primary energy demand by 577 MWh and CO₂ emissions by 84 t in the first case, and increase the self-production (SP) and self-consumption (SC) of PV energy by 20% and 10% in the second. Finally, a REC with PV systems and a district heating network, located in the city of Corticella, is analysed in [24], with results showing reductions of the primary energy demand by 11%, and of the CO₂ emissions by 12%.

In the framework of the Italian’s implementation of the European directive about on RECs, we aim to extend our previous work from [25] by (i) analysing the techno-economic feasibility of a fully-solar REC with PV and storage under the current Italian REC incentive scheme, (ii) introducing a new BESS control strategy to maximise the energy sharing while minimising its grid impact, (iii) estimating the impact of the consumers/prosumers ratio if different BESS control strategies are applied.

In particular, we firstly show how to cost-optimally size the residential PV/BESS systems to produce 98% of the demand of a RECs composed entirely of prosumers. Then, we further demonstrate that, with the Italian incentive system, crowdfunding for a centralized battery using a centralised battery control strategy makes a “fully-solar” REC economically viable, even with the current system costs. Finally, we demonstrate two different control approaches to include consumers in fully solar RECs, quantify the economic benefits for prosumers and consumers, and finally point out the optimal number of consumers to include.

The following sections present: the REC model, the PV/battery energy sizing and management strategies/configuration, the simulation assumptions, and the techno-economic analysis results. Finally, the conclusions are presented.

2. Methodology

2.1. Renewable Energy Community Model

In this work, we first consider an initial REC composed of 30 prosumers with PV/BESS residential systems, then gradually increase the number of consumers. The analysis is performed for two communities with different PV/BESS self-production (SP) levels, i.e., two different fractions of the electricity demand covered by solar generation. For 30 prosumers with the same electricity demand, two configurations were considered based on self-production targets. For SP = 50%, a total PV capacity of 70.4 kWp and BESS capacity of 52 kWh are needed. For SP = 98%, a PV capacity of 207 kWp and BESS capacity of 260 kWh are required. All REC members (prosumers/consumers) are assumed to be in the same distribution grid. For this purpose, we used the PV production of the Bolzano airport experimental field (Italy), measured every 15 min during 2019, to calculate the corresponding PV power potential (1346 kWh/kWp). Then, a set of 300 residential load profiles for one year with 15-min time resolution was generated using the Load Profile Generator tool [26]. The variability in the consumption profiles is due to different user behaviors, household sizes, and levels of electrification (e.g., heating or mobility sector). We then create the community of residential prosumers by randomly selecting 30 load profiles with a consumption between 1615 kWh/yr and 4450 kWh/yr, and an average of 3160 kWh/yr. The generated profiles and household composition were verified to match the population statistics for the city of Bolzano, Italy [27].

2.2. Battery Storage Control Strategies

The evaluation of energy/economic key performance indicators (KPIs) of the modelled REC was carried out using two strategies, firstly introduced in [28] and then revised and extended in [4,23], to control the prosumers’ batteries. The peer-to-grid (P2G) strategy aims at maximizing SP at the individual prosumer level, while the peer-to-peer (P2P) one aims at maximizing “collective” SP, i.e., maximizing the benefits of photovoltaic energy for the entire REC. The latter control is applied with two different battery configurations: distributed storage, where each prosumer’s PV system has its own batteries (P2P) and centralized community storage for the entire PV system fleet (P2P-C), as illustrated in Figure 1. In the P2G control, the PV/BESS system operates in autonomous “self-production” mode, i.e., only the PV energy not used to meet the consumer demand or charge the battery can be fed into the grid and possibly shared with other community members. This is the simplest approach because it does not require a communication infrastructure between the REC members. Assuming that the REC members are connected to the same primary substation, the shared energy is simply the prosumers’ share of PV feed-in that is consumed simultaneously by the other members (creating an “additional” SC at the “community level”):

$$E{S}_{P2G}=min\{(Netloa{d}_{pros}+Loa{d}_{cons}),PV2Gri{d}_{pros}\}$$

(1)

where $PV2Gri{d}_{pros}$ is the prosumer’s PV over-generation (fed into the grid), and $Netloa{d}_{pros}$ and $Loa{d}_{cons})$ are the prosumers’ residual load and consumers’ demand. The residual demand of the entire REC (once each prosumer’s over-generation is shared among members) is:

$$Netloa{d}_{P2G}=(Netloa{d}_{pros}+Loa{d}_{cons})-E{S}_{P2G}$$

(2)

The P2P approach needs a centralized power plant controller that manages the PV/BESS system fleet as a single virtual power plant to maximise the REC-level self-consumption. Therefore, it requires not only PV generation, but also batteries, as advocated in the IRENA report [29]. In this case, the shared energy includes not only the redistribution of photovoltaic production not used directly by individual prosumers, but also the possibility of recharging all batteries with excess solar power or sharing battery discharge, resulting in an even wider flexibility pool compared to the P2G scenario.

All things considered, the energy shared with the P2P control can be computed as:

$$E{S}_{P2P}=(Netloa{d}_{P2G}-Netloa{d}_{P2P})+E{S}_{P2G}$$

(3)

where $Netloa{d}_{P2P}$ is the minimum achievable community residual load, given the prosumers’ fleet of PV/BESS systems, and $(Netloa{d}_{P2P}-Netloa{d}_{P2G})$ accounts for the additional energy shared by the PV and storage systems.

The centralized P2P configuration (P2P-C) represents an “extreme” form of P2P, in which a centralized storage facility acts as a single user fully supplied by the prosumers’ excess PV production. As a result, all PV energy fed into the grid and used to recharge the battery is metered and then re-distributed among the REC members. Therefore, the energy shared is:

$$E{S}_{P2P-C}=PV2BESS+E{S}_{P2G}$$

(4)

where $PV2BESS$ is the prosumers’ PV over-generation fed into the centralised storage system.

In addition, we compare the P2P-C control strategy (Equation (4)) with a combination of the P2P-C and P2G control system. This novel management strategy, called “peer-to-peer centralized firm generation” (P2P-CF), enables the PV systems to meet all the prosumers’ demand (through P2P-C BESS management) and then to share the remaining over-generation with consumers (P2G management of overproduction). In a nutshell, this strategy uses the P2P-C control for prosumers and the P2G control for consumers, combining the best aspects of the two controls. The following equations apply for P2P-CF:

$$E{S}_{P2P-CF}=min\{(Netloa{d}_{pros}+Loa{d}_{cons}),PV2Gri{d}_{P2P-C}\}$$

(5)

and

$$Netloa{d}_{P2P-CF}=(Netloa{d}_{pros}+Loa{d}_{cons})-E{S}_{P2P-CF}$$

(6)

where $PV2Gri{d}_{P2P-C}$ is the over-generation of the prosumers’ fully solar REC, and $Netloa{d}_{cons}$ is the residual load of prosumers, which is practically zero most of the time (since prosumers self-produce 98% of their demand). It is worth noting that, in fully solar RECs managed with the P2P-CF strategy, the PV fleet and centralized battery self-generate all prosumers’ demand, regardless of the number of consumer members included in the community. In contrast, in the fully solar RECs with the P2P-C strategy, the PV fleet/BESS systems are managed to maximize self-production at the community level. This implies that, as consumers join the community, prosumers will no longer be able to meet all their own consumption, as they need to share their generation with the other REC members.

3. Simulation Results

3.1. Parameters and Assumptions

We conducted simulations to evaluate residential RECs’ energy and economic performance when the number of consumers versus prosumers increases and different battery control strategies are used (described in Section 2.2). Specifically, starting with a community of 30 prosumers equipped with PV/BESS systems capable of generating either 50% or 98% of the REC electric demand, we evaluated energy shared (ES) among members, REC self-production (SP), and self-consumption (SC) when up to 40 consumer members are included. Next, we quantified economic KPIs such as the discounted payback time, and the prosumer and consumer cash flows resulting from the Italian incentive system, and from our business model. The proposed business model distributes the additional revenues due to the inclusion of new consumer members in the REC equally among households, regardless of their prosumer or consumer status. We adopted the parameters summarized in

Table 1. Economic and system parameters considered for the analysis, and adopted values.

	Variable	Value
PV system	CAPEX (<6 kWp) [30,31]	2500 €/kWp
	CAPEX (6 kWp < x < 20 kWp) [30]	1800 €/kWp
	OPEX	1.5*CAPEX
	Power loss rate	0.5%/yr
	Lifetime	30 years
BES system	CAPEX (2–4 kWh)	1000 €/kWh
	CAPEX (60–240 kWh)	800 €/kWh
	CAPEX (240–400 kWh)	640 €/kWh
	OPEX fixed cost	65 €/yr
	OPEX variable cost [32]	3.1 €/MWh
	Dept of discharge (DoD)	80%
	Round-trip-efficiency	90%
	Degradation	1.3%/yr
	Lifetime	5000 life cycle
	Replacement [30]	15 years
	Replacement cost [30]	65% CAPEX
Other costs	Tax rebate every 10 years	50%
	Energy sharing incentive [14]	0.118 €/kWh
	Weighted Average Cost Capital	4%
	Cost electricity [33]	0.21 €/kWh
	Sold energy [33]	0.05 €/kWh

, and detailed in [25].

3.2. PV and Battery Sizing

In the first part of the study (i.e., Section 3.3), we sized PV systems to produce the annual demand of each prosumer and battery capacity to achieve 50% SP. As a result, PV capacities range between 1.2–3.3 kWp while battery capacities range between 0.9–2.7 kWh, with an average value of 2.3 kWp and 1.7 kWh respectively. The value of 50% self-generation allows a discounted payback time of 25–27 years for this type of system, which is lower than its lifetime, but generally too high for the REC members (Figure 2).

In the second part of the study (i.e., Section 3.4), we cost-optimally size the 30 PV/BESS plants of the REC to supply 98% of the prosumer’s yearly demand (SP = 98%), thus making the REC “fully solar-powered”. Following the approach used in [34,35], we found that, by installing three times the PV capacity that was installed with the previous sizing, the system Levelized Cost of Energy (LCOE) is minimised. Indeed, the storage size is reduced to just guarantee one day of autonomy, as PV/BESS capacities range from 3.6 kWp/4.5 kWh to 9.9 kWp/12.4 kWh with an average value of 6.9 kWp/8.66 kWh (1.25 kWh/kWp). Figure 3 shows the results of the sizing process: PV over-sizing allows the reduction of the storage from seasonal to daily, decreasing the LCOE of the system by almost 100 times.

3.3. RECs of Prosumers with 50 % of SP

Before showing and commenting on the results with an increasing number of consumers, we summarize the aggregated yearly energy totals in the REC for the different analyzed BESS control strategies. Considering the configuration of SP = 50%, a total PV capacity of 70.4 kWp, and an effective total BESS capacity of 52 kWh has been considered. The electricity demand, which remains constant across the strategies, equals 94.80 MWh/yr. The results indicate that the P2P-C strategy is more effective in sharing energy among prosumers (with a value of 18.11 MWh/yr concerning the 1.685 MWh/yr of P2P and the 550 kWh/yr of P2G). Moreover, while P2G exports more energy to the grid, almost equal to 44.36 MWh/yr, the P2P and P2P-C strategies also show an increased utilization of PV energy directly for load and battery storage, which corresponds to 31.88 MWh/yr and 18.06 MWh/yr, respectively.

Table 2. Energy Share [MWh/yr] for different REC consumers.

# REC Consumers	P2G (MWh/yr)	P2P (MWh/yr)	P2P-C (MWh/yr)
0	0	0	20
5	2.5	7.5	22
10	5	10	25
20	10	15	30
30	15	22	35
40	18	28	35

and

Table 3. Self-production & Self-consumption [%] for different REC consumers.

# REC Consumers	SP (P2G) [%]	SP (P2P) [%]	SC (P2G) [%]	SC (P2P) [%]
0	50	50	50	50
5	48	46	55	64
10	44	41	60	64
20	41	37	64	73
30	37	34	73	78
40	34	30	78	84

instead show the energy shared, SP and SC values for different prosumers/consumers ratios.

Specifically, Table 2 shows that the inclusion of consumers with heterogeneous load profiles (as in the residential case) and the choice-specific REC controls and configurations are key to increasing energy sharing. If each prosumer maximizes its SP (P2G control), the shared energy grows up to 18 MWh/yr when 40 consumers are included. If the community manages to maximize the collective self-production (P2P), as expected, the amount of shared energy increases even more. Indeed, in the distributed BESS configuration (P2P), the energy shared among REC members increases to 28 MWh/yr with 40 additional consumers, while in the centralized BESS configuration (P2P-C), up to 35 MWh/yr. It is worth noting that the benefit of including consumer members is greater in the case of the P2P distributed configuration since, as the number of consumers increases, the shared energy grows very rapidly, converging to the value of the centralized P2P-C schema. Indeed, that value represents the maximum shareable energy within the REC, which, in the case of the P2P distributed storage configuration, can only be achieved with many consumers.

With the addition of consumers, the electricity demand supplied by prosumers’ PV/BESS systems (SP) decreases, while the share of solar generation consumed in the community (SC) increases. SP and SC also depend on the control strategy, as P2P control provides the optimal management of PV/BESS systems to achieve the minimum residual load at the community level. In contrast, these KPIs do not depend on the storage configuration (P2P or P2P-C) since the minimum residual load of the community relies only on the size of the PV/BESS, and not on the storage location.

This reasoning is confirmed by the results shown in Table 3, where SP decreases from 50% to 34% with P2G and 50% to 30% with P2P by adding 40 consumers. Similarly, SC rises from 50% to 78% and from 50% to 84% for P2G and P2P, respectively. We can conclude that the P2P control provides a lower grid feed-in and a higher energy resilience. Our business model includes public incentives for the additional shared energy due to more consumers, and the related benefit is shared equally among all the members. Therefore, as the shared energy grows when the number of consumers increases, the cash flow of the individual prosumers increases as well, decreasing the discounted payback time of their PV/BESS systems.

Table 4. Discounted PBT [yr] for prosumers and Energy Shared $FIT$ (€/kWh) vs. number of REC Consumers.

# REC Consumers	Discounted PBT [yr]			Energy Share $\mathit{FIT}$ (€/kWh)
	P2G	P2P	P2P-C	P2G	P2P	P2P-C
0	28	26	18	0.001	0.002	0.025
10	24	21	16	0.008	0.013	0.030
20	21	18	15	0.015	0.023	0.036
30	20	18	14	0.020	0.030	0.040
40	20	17	14	0.026	0.038	0.044

and

Table 5. Revenues per prosumer and consumer [€/yr] for different REC consumers.

# REC Consumers	Revenues Per Prosumer [€/yr]			Revenues Per Consumer [€/yr]
	P2G	P2P	P2P-C	P2G	P2P	P2P-C
0	400	415	480	0	0	0
10	443	476	531	43	60	51
20	469	511	561	69	96	81
30	476	520	568	76	105	88
40	484	530	576	84	115	96

quantify the discounted PBT, energy shared equivalent feed-in-tariff ($FIT$), and revenues for the REC members, as the number of consumers increases.

From Table 4 shows that the discounted PBT decreases from 28 to 20 years with P2G control and from 26 to 17 years or 18 to 14 years with P2P control in the distributed/centralized storage REC configurations. In short, even if the PV + BESS systems PBT is lower its lifetime (approximately 30 years), it is more economically profitable to choose a P2P scheme, that benefits prosumers and consumers simultaneously at the same time. These results also show that, with the Italian incentive system and our business model, a community composed of an equal number of prosumers and consumers maximizes the economic benefit of all members.

To better understand the magnitude of public funding to RECs, the Italian incentive on energy shared among members can be expressed as an “equivalent” feed-in tariff (FIT) on the community’s entire solar generation:

$$FIT={\displaystyle \frac{Incentiv{e}_{REC}·ES}{E_{pv}}}$$

(7)

where $Incentiv{e}_{REC}$ = 0.12 €/kWh, $ES$ is the annual energy shared among REC members, $E_{pv}$ is the annual PV energy generation. In short, we estimate what feed-in-tariff would produce a revenue equal to $Incentiv{e}_{REC}$. The right side of Table 4 produces the FIT values, and shows that the maximum incentive for shared energy (obtained with P2P-C) corresponds to a FIT between 0.025–0.045 €/kWh produced, which is more than four times lower than the value provided in 2011 by the last Italian PV incentive program (FIT = 0.176 €/kWh for PV systems smaller than 20 kWp and without storage [36]). This means that, to incentivize the prosumers in the REC, the state incentives could be lowered by 75% , which is a relevant benefit for society. It has to be noted that, at the end of 2025, the feed-in-tariff scheme for PV in Italy is not available anymore for prosumers, making it, de facto, more beneficial to join a REC [37].

The annual revenues of prosumers (due to energy savings/incentives) and consumers (incentives only) is reported in Table 5. When the number of consumers grows from zero to 40, the average revenues of prosumers increases from 400 to 484 €/yr (20%) with P2G control, from 415 to 530 €/yr (27%) with P2P control/configuration, and from 480 to 573 €/yr (19%) with P2P-C control/configuration. Depending on their number, consumers can earn up to 84 €/yr with P2G control and up to 115 €/yr or 96 €/yr with P2P or P2P-C control/configurations. Summing up, Italy’s incentive system for RECs and our business model represent a winning strategy both from an energy-saving and energy-poverty perspective. Prosumers increase their revenues by including consumers in the community, and enabling higher SC, while consumers who cannot invest in PV/BESS assets can significantly reduce their electricity bills by up to 13%, 17%, and 14% with the P2G/P2P/P2P-C control schemes.

It is important to note that, while the highest energy shared is obtained with P2P-C control/configuration, the highest consumer revenues are obtained with the P2P control. This is because consumer revenues are derived from the energy sharing incentive, and P2P control/configuration shows the greatest increase in shared energy when the number of consumers increases.

3.4. Fully Solar RECs

In light of the above results, we explore the techno-economic feasibility of prosumers’ RECs to achieve a high level of SP (98%) using the most profitable control and management configuration only (P2P-C). In addition, as in the previous case, we quantified the benefit of including consumers in this fully solar REC using the P2P-C and the P2P-CF strategies described in Section 2.2. Before showing and commenting on the results with an increasing number of consumers, we summarize the aggregated yearly energy totals in the REC for the different analysed BESS control strategies. Considering the configuration of SP = 98%, a total PV capacity of 207 kWp, and an effective total BESS capacity of 260 kWh has been considered. The electricity demand, which remains constant across the strategies, equals 94.80 MWh/yr. The results indicate that the P2P-C strategy is more effective in sharing energy among prosumers (with a value of 60.14 MWh/yr with respect to the 0.92891 MWh/yr of P2P). Moreover, while P2G exports more energy to the grid, almost equal to 44.36 MWh/yr, the P2P and P2P-C show better utilization of PV energy directly for load and battery storage.

Figure 4 shows the discounted pay-back time (a), and the prosumers/consumers revenues (b), for both the P2P-C and P2P-CF management strategies. Figure 5 instead, shows the energy shared and SC/SP values variation as the number of consumers increases.

Figure 5 shows that the energy shared between prosumers with centralized batteries is 60 MWh/yr, corresponding to almost 50% of the generation and 64% of the demand. The additional shared energy due to the inclusion of consumers in the fully solar REC is highly dependent on the control strategy. Simple P2P-C is much more effective than P2P-CF in maximizing the utilization of the energy produced and, consequently, achieving higher values of collective SC. This is because the P2P-C optimize the use of the centralized battery to meet the entire REC demand, while P2P-CF optimizes the use of the battery to provide 98% of the prosumers’ demand first, then to share the unused generation with consumers.

With no consumers, a discounted PBT of 19 years for prosumers is attainable under the current incentive scheme. Thanks to the energy sharing growth (Figure 5), the PBT decreases as the number of consumers increases, reaching 14 and 16 years for the P2P-C and P2P-CF controls, respectively. Prosumers’ revenues increase from 1175 €/yr to 1424 €/yr with the first strategy and to 1279 €/yr with the second. Consumers, instead, can reduce their electric bills by up to 248 €/yr (37%) with P2P-C, and 104 €/yr (17%) with P2P-CF. Again, the best prosumer-to-consumer ratio is one-to-one, and the most profitable control strategy remains P2P-C. Nevertheless, a substantial difference exists between P2P-C and P2P-CF: in the first one, the prosumers’ bi-monthly electricity bills are always zero, regardless of the number of participating consumers, since only their overproduction is shared with the consumers. In P2P-C instead, the BESS is managed to maximise the community-level energy sharing, so prosumers still pay for their net consumption every two months, then receive the energy sharing revenue at the end of the year. Even if the yearly energy sharing incentive far exceeds the yearly total energy cost, this could create issues for the prosumers, who only reap the BESS benefit at the end of the year. Due to the same reason, from the DSO’s point of view, the P2P-CF control strategy introduces less perturbation in the demand profile, as the residual load of prosumers is always zero.

Indeed, as shown in Figure 6, the P2P-C control could give rise to steep load ramps, while P2P-CF always reduces the average load and residual load duck curve/ramps (as prosumers’ demand disappears from the grid). Therefore, the second strategy is preferred from a grid management standpoint.

Finally, it is worth noting that fully solar RECs, even if economically feasible, require a three times larger area available for PV installation than in the 50% SP case. In particular, for the 50% self-consumption, 2.3 kWp for each prosumer with a rooftop surface requirement of about 18.5 m² needs to be considered; while for the 98% of self-consumption (fully solar REC), 6.9 kWp per prosumer and a surface requirement of 55 m² is required.Therefore, fully-solar RECs should be promoted especially in rural communities or single/multifamily residential neighborhoods where homeowners have enough rooftop surface. The central battery (which benefits from reduced costs due to its larger size) can be purchased through crowdfunding instead.

4. Conclusions

This paper expands our previous work from [25] by (i) examining the techno-economic feasibility of fully-solar residential Renewable Energy Communities (RECs) with battery energy storage systems (BESS), (ii) exploring different energy management strategies, and proposing new hybrid one (P2P-CF) to combine P2P-C for prosumers and P2G for consumers, (iii) including an increasing number of consumers in the REC, and analysing the REC economic profitability under Italy’s REC incentive scheme, which includes a 50% tax rebate over ten years and a compensation of 0.118 €/kWh shared and consumed in the REC. The main takeaways of this work are:

• In Italy, PV/BESS systems can be optimally sized to achieve nearly 100% SP by oversizing PV systems to produce three times the annual electricity demand, while using just one-day storage autonomy, which is 1.25 kWh/kWp. Thus, a fully solar community is feasible from a technical standpoint if the energy shared by the prosumers is consumed by another REC member.
• Including consumers in an REC decreases the PBT for prosumers by up to 5 years (1175–1424 €/yr revenue), while allowing consumers to reduce their energy bills by up to 104–248 €/yr (17–37%) % without investing in renewable energy systems. In the analysed case study, the optimal cost-benefit ratio for RECs is achieved with an equal number of consumers and prosumers.
• Among the analysed BESS control strategies, the P2P-C configuration is the most effective for energy sharing, making fully-solar RECs economically viable with the Italian incentive system. Despite current PV/BESS costs, a discounted PBT of 19 years over a 30-year expected lifetime is achievable. Using a centralized battery, which can be funded through crowdfunding, lower capital costs and higher energy shared values are attainable. The P2P-CF management of fully solar RECs with consumers is less profitable than the simple P2P-C but preferable from the grid management point of view, since it reduces the net residual load ramps on the power system.
• The revenue from shared energy incentives is equivalent to a feed-in tariff of 0.023–0.05 €/kWh produced by the PV/BESS residential systems, which is 3.5–7.5 times lower than the 2011 Italian feed-in tariff program. Consequently, REC incentives support the development of fully solar RECs with much lower public funding than single-user installations.

Future research directions include: (a) the consideration of residential-industrial communities, and their techno-economic feasibility, (b) the feasibility analysis with different regulatory frameworks, for example from other countries in the Europe, (c) the inclusion of further sources of flexibility to further improve the system resilience (e.g., electric vehicles), and (d) the consideration of grid services as a new revenue source for communities.