#
Optimal Integration of Renewable Sources and Latent Heat Storages for Residential Application^{ †}

^{*}

^{†}

## Abstract

**:**

## 1. Introduction

_{2}emissions by 5% [3]. Therefore, to meet the decarbonization challenge it is necessary to improve the energy performances of the envelope and to include high efficiency and renewable technologies.

_{2}emissions compared to traditional gas condensing boiler and heat pump technologies (up to 34% and up to 22% respectively). Arcuri et al. [11] formulated a model for selecting the optimal typology, size, and operative strategy of a trigeneration system for the civil user, analyzing different cogeneration plants. The mathematical model proposed is nonlinear since the analysis takes into account three nonlinear constraints: the variation in nominal efficiency and unit cost of the cogeneration plant in relation to its size and the decrease in nominal efficiency in part-load configuration. Despite greenhouse gas emission reductions due to higher efficiencies, most micro-CHPs are fueled by natural gas, leading to environmental concerns about local emissions. For this reason, several research efforts have been made studying the performance of small-scale CHPs powered by renewable resources. In Ref. [12] a review of the available solutions of micro combined heat and power systems based on renewable energy sources is presented.

_{2}emissions. Barbieri et al. [17] analyze the profitability of microCHP systems for a single-family dwelling installed in combination with an auxiliary boiler and a thermal energy storage unit. Among the obtained results, the reduction in primary energy consumption and the payback period of the technologies are analyzed as a function of the size of the thermal energy storage unit. There are also various studies that investigate the use of thermal energy storages to reduce the electrical power consumption during peak-load periods, especially with a focus on air conditioning systems. Ref. [18] presents a review on load shifting control using thermal energy storage systems, with a focus on phase change materials. According to this strategy, during periods with low or moderate power demand, thermal energy storage can be used to store heating/cooling thermal energy and then use it during periods with high power demand. Comodi et al. [19] propose a modeling/design computational tool applied to a residential microgrid. In addition to storage technologies, a photovoltaic system and a geothermal heat pump are present as generation technologies. According to the results of the study, the ability to store both thermal and electrical energy usually improves the performance of the building’s energy management. However, the high investment cost made them unprofitable for the case study analyzed. In more detail, while thermal energy storage can be profitable if also used for heating system management, batteries are still too expensive to be competitive in the residential market. Therefore, one strategy to be analyzed may be to investigate whether the installation of thermal storage, with its considerably lower investment costs and higher lifetime compared to batteries, can provide economic benefits.

- (a)
- A tool for the assessment of a seamless technology integration, depending on the characteristics of the demand and the site/type of installation;
- (b)
- A technique for the optimal management of the system. Renewable energy sources will be integrated with proper storage units, such as batteries and latent thermal storage units, which allows for reducing the dimension required for the installation.
- (c)
- In more detail, two novelties are introduced in the treatment of multi energy systems for residential applications:
- (d)
- Analysing whether the benefits of electrical storage can be partly achieved by using only the thermal storage;
- (e)
- Investigating how much impact the primary energy cost of the micro cogeneration unit has on the system design process.

- -
- Section 2 contains, on one hand, the explanation of the adopted methodology and, on the other hand, the description of the case study preceded by the description of the European project.
- -
- Section 3 presents the results of the analyzed cases and a comparison between them;
- -
- Section 4 includes a discussion of optimization results;
- -
- Section 5 draws conclusions obtained from the study.

## 2. Materials and Methods

#### 2.1. Methodology

#### 2.1.1. Optimal Operations

_{e_in}is the electricity purchased, c

_{e_out}is the electricity sold, c

_{gas_in}and c

_{biogas_in}are the natural gas and the biogas purchased respectively. These terms are obtained by multiplying the unit cost of the energy carrier times the energy absorbed by the system in the entire time evolution considered. These terms are all expressed in €/day. More in detail, each cost term is defined as follows (Equation (2))

- -
- Power flows (both electric and thermal) produced by each installed generation technology;
- -
- Power flows stored/released by thermal/electric storage.

#### 2.1.2. Combined Design and Operation Optimization

- (a)
- The fluxes of heat/electricity produced/consumed by each production/conversion energy system, which are 9 (photovoltaic, wind turbine, gas heat-only boiler, micro combined heat and power unit, heat pump, electric storage, thermal storage, electricity sold by the system, electricity purchased by the system);
- (b)
- The capacities of technologies to be installed, which are 7 (photovoltaic, wind turbine, gas heat-only boiler, micro combined heat and power unit, heat pump, electric storage, thermal storage).

- Optimization variables related to operations, which, as previously discussed in Section 2.1.1, are equal to the coefficient to be evaluated times the number of time frames considered for the simulation.
- Optimization variables consist in the investment contributions of the multi-energy system components.

_{e_in}), the electricity sold (c

_{e_out}), the natural gas purchased (c

_{gas_in}), the biogas purchased (c

_{biogas_in}), and the investment cost (c

_{inv}) are all expressed in €/day, as for the optimization described in Section 2.1.1. The parameters related to the cost for the energy supplied and to investment costs that appear in Equation (3) are detailed in Equations (4) and (5), respectively.

#### 2.2. The RE-COGNITION Project and Case Study

#### 2.2.1. The Project

#### 2.2.2. Case Study

^{2}. The aim of the case study is to analyze the potential of some technologies developed within RE-COGNITION, for the installation in the analyzed building (Figure 4).

- CASE 1: a vertical axis wind turbine (VAWT), a photovoltaic system (PV), a biogas-fed micro combined heat and power unit (mCHP), an air heat pump (HP), a gas-fueled heat-only boiler, and a latent heat thermal storage (LHTS).
- CASE 2: a vertical axis wind turbine (VAWT), a photovoltaic system (PV), a biogas-fed micro combined heat and power unit (mCHP), an air heat pump (HP), a natural gas-fueled heat-only boiler and electric storage (BESS).

^{3}–0.39 €/m

^{3}) [34]. For this reason, additional analyses are performed considering the entire variation range.

## 3. Results

#### 3.1. Operations Optimization

#### 3.2. Combined Design and Operation Optimization

#### 3.3. Impact of Biogas Cost on Optimization Results

^{3}.

^{3}is considered, the optimal daily management of the system changes considerably. For both cases, the electric heat pump (along with the thermal storage if available) almost completely satisfies the heat demand. In particular, in Case 1, the heat pump operates with large fluctuation of thermal power (i.e., strongly alternate operations) exploiting the availability of the thermal storage. In some timeframes, the EHP is switched on at nominal power and the thermal storage is charged, in other timeframes, the storage is discharged and the heat pump operates at a lower power level. In Case 2, as there is no possibility of using the thermal storage, the EHP is forced to follow the load. Only in the evening hours, when the peak of the electrical load occurs, the mCHP is used at nominal power for a few time steps. A considerable amount of electricity is purchased from the power grid to feed the electric heat pump and meet the daily electrical load. Finally, photovoltaic and wind power are always operated when respectively sun and wind are available, since, when the investment costs of the technologies are not considered, the energy produced is free.

^{3}). Results for Case 1 and Case 2 with a biogas price of 0.39 €/m

^{3}are shown in Figure 14 and Figure 15. The selected technologies are the same as in the results of the operation simulation with the exception of the mCHP, which is not installed in either Case 1 or Case 2. The advantage of using this component in the evening hours is not so profitable if, in addition to the operating costs, investment costs are also considered. Photovoltaic and wind power are installed for both cases. Finally, the strongly alternate operation of the heat pump in the presence of thermal storage also occurs for the Combined Design and Operations Optimization.

#### 3.4. Comparisons

- Benchmark Case (without storage);
- Operation Optimization Case 1 (with thermal storage);
- Operation Optimization Case 2 (with electric storage);
- Combined Design and Operation Optimization Case 1 (with thermal storage);
- Combined Design and Operation Optimization Case 2 (with electric storage) and a detail of the fraction covered by investment and operations.

^{3}are concerned, the use of the optimization allows to reduce costs of 13–24% (depending on the case) with respect to the Benchmark. More in detail, the Combined Design and Operation Optimization provides a solution with an operational cost slightly higher than in the case of Operation Optimization; however, the investment cost (that is included in the optimization) is significantly lower. The total cost reduction obtained adopting the Combined Design and Operation Optimization is 12% for Case 1 (with thermal storage installed) and 8% for Case 2 (with electric storage installed). Results achieved with Operation Optimization show that the installation of the electric storage is more convenient. Nevertheless, the Combined Design and Operation Optimization provides a better solution for Case 1 (with the thermal storage installed). This is because including the investment costs directly in the optimization process may significantly change the set of technologies that is more convenient to install. The total cost saving achieved by installing thermal storage instead of electrical storage is 2.5%. By contrast, if a biogas price equal to 0.39 €/m

^{3}is considered in the analysis, some additional considerations can be done. Under these circumstances, the cost reductions when comparing Case 1 and Case 2 with the Benchmark Case is up to 29%. Even in this case, if the results of the Combined Design and Operation Optimization are compared with those of the Operation Optimization, it can be seen that:

- -
- Operating costs increase by 1.3% for Case 1 and 0.8% for Case 2
- -
- Investment costs decrease by 24% for Case 1 and 27% for Case 2

^{3}, it is more convenient to include electrical storage in the energy system rather than thermal storage, while, if the Combined Design and Operation Optimization is performed, the opposite occurs. On the contrary, with a higher biogas cost (0.39 €/m

^{3}), this difference in terms of results between the two approaches no longer occurs since the installation of thermal storage is always preferred. In particular, if only operating costs are considered in the optimization, the reduction in terms of total cost reaches 6%, while, if investment costs are also assessed, the reduction is 4%. The results reported in Figure 14 and Figure 15 clarify the importance of the design stage in the overall cost of RES systems. In particular, the adoption of a Combined Optimization, including design and operation, allows substantial cost reduction that significantly enhances the pathway of existing buildings towards low energy buildings.

## 4. Discussion

## 5. Conclusions

^{3}and 0.39 €/m

^{3}.

^{3}and, consequently, higher than that initially assumed equal to 0.22 €/m

^{3}, it is no longer worthwhile to use the combined heat and power unit. Furthermore, when the Combined Optimization is performed, latent heat storage is more convenient to be used than the electric storage with a cost saving of about 2.5% with a biogas price of 0.22 €/m

^{3}and of 4.3% with a biogas price of 0.39 €/m

^{3}.

## Author Contributions

## Funding

## Conflicts of Interest

## References

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**Figure 3.**Schematic of the European project RE-COGNITION: (

**a**) First aim of the project: new renewable technologies development; (

**b**) Second aim of the project: platform development.

**Figure 4.**Technologies adopted in the work for the renewable production, conversion, and storage of energy.

**Figure 5.**Daily evolution of the dwelling consumptions for a typical cold winter day: (

**a**) electricity consumption; (

**b**) thermal consumption.

**Figure 8.**Daily consumption and production pattern for Case 1: thermal production (

**a**-up) consumption (

**a**-down); electricity production (

**b**-up) consumption (

**b**-down).

**Figure 9.**Daily consumption and production pattern for Case 2: thermal production (

**a**-up) consumption (

**a**-down); electricity production (

**b**-up) consumption (

**b**-down).

**Figure 10.**Daily consumption and production pattern in case of investment cost inclusion for Case 1: thermal production (

**a**-up) consumption (

**a**-down); electricity production (

**b**-up) consumption (

**b**-down).

**Figure 11.**Daily consumption and production pattern in case of investment cost inclusion for Case 2: thermal production (

**a**-up) consumption (

**a**-down); electricity production (

**b**-up) consumption (

**b**-down).

**Figure 12.**Daily consumption and production pattern for Case 1 (Operation Optimization) with a biogas price of 0.39 €/m

^{3}: thermal production (

**a**-up) consumption (

**a**-down); electricity production (

**b**-up) consumption (

**b**-down).

**Figure 13.**Daily consumption and production pattern for Case 2 (Operation Optimization) with a biogas price of 0.39 €/m

^{3}: thermal production (

**a**-up) consumption (

**a**-down); electricity production (

**b**-up) consumption (

**b**-down).

**Figure 14.**Daily consumption and production pattern for Case 1 (Combined Design and Operations Optimization) with a biogas price of 0.39 €/m

^{3}: thermal production (

**a**-up) consumption (

**a**-down); electricity production (

**b**-up) consumption (

**b**-down).

**Figure 15.**Daily consumption and production pattern for Case 2 (Combined Design and Operations Optimization) with a biogas price of 0.39 €/m

^{3}: thermal production (

**a**-up) consumption (

**a**-down); electricity production (

**b**-up) consumption (

**b**-down).

**Figure 16.**Daily cost for operations and investment for the Operational Optimization (for both Case 1 and Case 2) and Combined Design and Operation Optimization (for both Case 1 and Case 2) with a biogas price equal to 0.22 €/m

^{3}.

**Figure 17.**Daily cost for operations and investment for the Operational Optimization (for both Case 1 and Case 2) and Combined Design and Operation Optimization (for both Case 1 and Case 2) with a biogas price equal to 0.39 €/m

^{3}.

Technology | Acronym | Description |
---|---|---|

VERTICAL AXIS WIND TURBINE | VAWT | The technology is developed with a new aerodynamic design with the aim of guaranteeing high efficiency (typical of variable geometry when high wind velocity is reached) also in urban applications. This performance is reached using a passive system to dampen vibration suppression. The wind turbine is specifically design for the installation on the rooftop and in the ground (i.e., courtyards, garden) in order to guarantee safety for the building occupants. |

BUILDING INTEGRATED PHOTOVOLTAIC | BIPV | The innovative photovoltaic modules are designed to reduce the impact of the installation on buildings (especially already existing) and to guarantee an aesthetic appeal of the generation system. The technology and the approached adopted for the module coloration are such for keeping low the specific cost of the technology |

MICRO COMBINED HEAT AND POWER SYSTEM FED BY BIOGAS | mCHP | The technology requires a deep study for making mCHP suitable for a fuel characterized by a lower energy content per unit mass (and volume). Furthermore, changes in the design should be performed to allow stable combustion (and flexible). |

LATENT HEAT THERMAL STORAGE | LHTS | The latent heat storage consists in a tank filled with phase change material that absorbs heat through its melting and release heat through the solidification phase. This guarantee high energy density and therefore low space required for the installation. The main problem of the technology consists in the low thermal conductivity that makes the power available poor. The technology developed within the project is characterized by the adoption of fins that are properly designed such as they are tailored for the specific application, for enhancing the heat exchange between the material changing phase and the heat transfer fluid. |

Technology | Acronym | Power | Other Characteristics |
---|---|---|---|

VERTICAL AXIS WIND TURBINE | VAWT | The turbine has a nominal power of 6 kW (reached with wind speed larger than 10 m/s). | |

BUILDING INTEGRATED PHOTOVOLTAIC | BIPV | The photovoltaic installation considered has an overall nominal power of 24.2 kW. | The surface of the system is about 130 m^{2} (with 78 modules with a nominal power of 310 W each). |

MICRO COMBINED HEAT AND POWER SYSTEM FED BY BIOGAS | mCHP | This is biogas microturbine for heat and power generation characterized by an electric nominal power of 20 kW | |

NATURAL GAS BOILER | BOILER | This is a typical condensing gas boiler for space heating production. The nominal thermal power is 170 kW | |

AIR HEAT PUMP | HP | The air heat pump has a nominal thermal power of about 180 kW. | |

LATENT HEAT THERMAL STORAGE | LHTS | The total storable thermal energy is 70 kWh. | The latent heat storage is filled with paraffin wax. |

ELECTRIC STORAGE | BESS | The total storable energy is 26 kWh | Lithium-ion battery |

Technology | Details | Cost and Ref. | Lifetime and Ref. | ||
---|---|---|---|---|---|

Photovoltaics | - | 2280 (€/kW) | [27] | 20 | [27] |

Wind Turbine | Small scale | 6424 (€/kW) | [28] | 25 | [29] |

mCHP | Biogas microturbine | 1950 (€/kW) | [30] | 10 | [31] |

Heat Pump | Traditional air heat pump | 720 (€/kW) | [27] | 15 | [27] |

Natural Gas Boiler | Condensing boiler | 180 (€/kW) | [27] | 12 | [27] |

Latent Heat Thermal Storage | Paraffin wax Phase Change Material (PCM) | 50 (€/kWh) | [32] | 30 | [32] |

Electric Storage | Li-ion | 546 (€/kWh) | [33] | 10 | [33] |

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## Share and Cite

**MDPI and ACS Style**

Mancò, G.; Guelpa, E.; Verda, V.
Optimal Integration of Renewable Sources and Latent Heat Storages for Residential Application. *Energies* **2021**, *14*, 5528.
https://doi.org/10.3390/en14175528

**AMA Style**

Mancò G, Guelpa E, Verda V.
Optimal Integration of Renewable Sources and Latent Heat Storages for Residential Application. *Energies*. 2021; 14(17):5528.
https://doi.org/10.3390/en14175528

**Chicago/Turabian Style**

Mancò, Giulia, Elisa Guelpa, and Vittorio Verda.
2021. "Optimal Integration of Renewable Sources and Latent Heat Storages for Residential Application" *Energies* 14, no. 17: 5528.
https://doi.org/10.3390/en14175528