Two different management control logics, named System Led and Market Led, for combined RES-BESS generators connected to the LV utility grid are described in the following. The control logics have been implemented with the aim of:

• Increasing the self-consumption quota in order to minimize the exchange of energy between the end-user and the grid;

• Reducing the yearly energy bill, fully exploiting the advantages of Time of Use (ToU) tariffs.

According to the System Led control logic, the Energy Management System (EMS) installed at the end-user’s facility acquires:

• The energy generated by the PV system (E_p1);

• The energy generated by the wind system (E_p2);

• The energy consumption of the building (E_c);

• The BESS State of Charge (SoC) (E_st).

On the basis of these data, the EMS command the combined RES-BESS system according to the flow chart represented in Figure 1.

Figure 1.

Block diagram representing the System Led control logic

In the case that the total production exceeds the building’s energy consumption and SoC of the batteries is lower than the maximum SoC (Est_max), the energy in excess is stored in the batteries, otherwise is injected into the grid.

On the contrary, in the case that the energy production is lower than the energy consumption of the building, if the SoC is higher than the minimum SoC (Est_min) the batteries supply the building, otherwise, the required energy is taken from the grid.

As formulated, the System Led algorithm is not able to take into account the effect of ToU tariffs and consequently, it cannot be used for an optimal economic exploitation of the BESS.

For this reason, a second control logic has been defined, named Market Led algorithm. This control logic is based on the variations of the electricity price during the day (and the week). The Market Led control logic has been defined considering the three pricing periods for Italian end-users [21], [22] reported in Table 1.

The end-users’ EMS, equipped with an internal clock and calendar, is set for recognizing the pricing period at every moment of the day.

In this case, the Market Led control logic operates according to the flow chart in Figure 2. When the building’s electricity consumption is lower than the electricity production from the generating unit, different situations can happen:

Figure 2.

Block diagram representing the Market Led control logic

• During pricing period F1, the energy in excess is injected into the grid because the selling price is the highest and the end-user can achieve the maximum revenue;

• During pricing period F2, the production in excess is stored in the batteries. In this case, the charge of the batteries rises till E_{st_max}/2. When this limit is exceeded, the production in excess is injected into the grid;

• During pricing period F3, the energy in excess is stored in the batteries again. In this case the charge of the batteries rises till E_{st_max}. When this limit is reached, the energy in excess is injected into the grid.

• On the contrary, when the building’s consumptions exceed the generated electricity:

• During pricing period F3, the grid supplies the building because the electricity price is the lowest and the cost for the end-user is minimum;

• During pricing period F2, the energy is taken from the batteries till the SoC is over E_{st_max}/2 and when the SoC gets below this value, the energy is taken from the grid;

• During pricing period F1, the energy is taken from the batteries till the SoC is over E_{st_max}, when the SoC gets below this value the energy is taken from the grid.

Three simple performance indexes have been defined for comparing the System and Market Led strategies. Indeed, their definition has been led by the purpose of providing a clear and simple set of indicators that can be easily understood even by non-technicians, in order to promote the diffusion of the culture of RES-based system among a broader public.

The three indexes are:

• Energy saving index (EnS);

• Economic saving index (EcS);

• Carbon dioxide (CO₂) reduction index (CO₂R).

The hybrid system is installed at the administrative offices building of the Municipality of Valderice, located close to Trapani (geographical coordinates: 38.02 N 12.36 E) in Italy (Figure 3).

Figure 3.

The administrative offices buildings of the Municipality of Valderice

The building is characterized by four floors and has a flat roof and external fixtures made of anodised aluminium and single glass without shutters. The covering of the building has a sufficiently regular shape and has a useful surface of about 400 m², with parapet walls and an elevator fence (Figure 4).

Figure 4.

Rooftop of the building

The building is supplied by the LV utility grid through a three-phase connection with available power of 20 kW, is equipped with a centralized gas boiler and has single air-conditioning units only in some rooms.

The study of the solar radiation map and wind speed allows the characterization of the site chosen. The building insists on a geographic area characterized by solar PV productivity of about 1,650 kWh/kWp per year and wind productivity of about 2,000 kWh/kW per year.

After performing the energy characterization of the building, the rationalization and energy efficiency measures and the areas available for the installation of the plants have been identified and, on the basis of the available budget, the optimal size of the systems micro-generation and electrical storage system have been calculated and the necessary components and devices have been chosen.

Thus, the prototype is composed of:

• A 8 kWp PV system in polycrystalline silicon, consisting of 32 × 250 W_p modules divided into two strings;

• A 1 kW Vertical-Axis Wind Turbine (VAWT);

• An electrical storage with capacity of 2 kWh (Li-ion batteries) integrated into one of the two inverters of the PV system;

• A solar-thermal system with flat collectors and a 250 liters tank for hot water storage serving 4 bathrooms and replacing electric water heaters;

• An indoor lighting controller for the offices, in order to contain the relative electrical consumption.

The following Figures 5–8 show the main components of the prototype.

Figure 5.

PV field

Figure 6.

1 kW wind turbine

Figure 7.

Thermal solar collectors with tank

Figure 8.

Technical room

The hybrid power plant benefits from a net-metering contract.

Tables from 2 to 4 report the technical data of the PV and wind generators.

As shown in Table 3, the PV system comprises two 4 kW inverters instead of only one 8 kW device. This choice has been made with the aim of comparing the performance of the two inverters in the presence and in the absence of storage.

Figure 9 shows the actual daily energy produced by the PV system compared with the expected values calculated by simulations.

Figure 9.

Average daily electricity production profile from PV: experimental and simulated data

Thanks to the energy meters installed at the point of common coupling with the distribution grid and at the output terminals of the hybrid generators, both the energy produced by the hybrid system and the energy demand of the building have been measured for one year. By using these data, the four indexes defined above are calculated. Table 5 reports the results of the calculation of EnS and EcS.

The values in Table 5 show that due to the installation of the hybrid system the building has yearly energy savings of about 68% and yearly economic savings of about 64%.

Finally, considering the Italian energy mix, the coefficient for converting the electricity consumptions into avoided emissions of CO₂ gas is equal to 494.30 g CO₂/kWh [23]. This implies that CO₂R = 1.97 t CO₂/year.

A MATLAB code has been written for simulating the behaviour of the RES-BESS system of Valderice, receiving as input the real monitored production data reported above.

With regard to the consumption of the building, the following occupancy schedule has been assumed for calculating it: from 8:00 to 14:00 from Monday to Friday, from 16:00 to 18:00 on Tuesday and Thursday. The offices have been assumed closed on Saturday and Sunday with no electricity consumption on these days. Starting from the real average yearly consumption of the building of about 32,000 kWh, and from the occupancy schedule above, the following daily consumptions have been assumed for the simulations: 124 kWh for Mon., Wed., Fri., 170 kWh for Tue., Thu., and 0 kWh for Sat., Sun.

The daily load profiles built starting from the above assumptions and used in the simulations are reported in Figure 10.

Figure 10.

Daily load profiles of the building (red line for Mon., Wed., Fri., green line for Tue., Thu.)

The comparison between the two control logics has been done considering one week as an example. Figure 11 reports the daily production of the hybrid system in a week of May 2016. The red curve has been obtained as average of the real consumptions from Monday to Friday.

Figure 11.

Daily production profile of the hybrid system (weekdays: red line, Saturday: blue line, Sunday: green line)

The comparison is done considering only the power produced by the PV system given that the wind system does not supply the batteries. Nevertheless, the control logics are also applicable to the case of wind turbine connected to the BESS and the results of the study are not influenced by the actual configuration of the system under examination.

Six cases are considered:

• CASE 1: the electricity price is equal to 0.11 EUR/kWh, 0.0969 EUR/kWh and 0.077 EUR/kW in the three pricing periods and the daily consumptions are derived by Figure 10;

• CASE 2: the electricity price is equal to 0.11 EUR/kWh, 0.0969 EUR/kWh and 0.077 EUR/kW in the three pricing periods and the daily consumptions are 50% of those considered in CASE 1;

• CASE 3: the electricity price is equal to 0.22 EUR/kWh, 0.0969 EUR/kWh and 0.077 EUR/kW in the three pricing periods and the daily consumptions are derived by Figure 10;

• CASE 4: the electricity price is equal to 0.22 EUR/kWh, 0.0969 EUR/kWh and 0.077 EUR/kW in the three pricing periods and the daily consumptions are 50% of those considered in CASE 3;

• CASE 5: the electricity price is equal to 0.39 EUR/kWh, 0.0969 EUR/kWh and 0.077 EUR/kW in the three pricing periods and the daily consumptions are derived by Figure 10;

• CASE 6: the electricity price is equal to 0.39 EUR/kWh, 0.0969 EUR/kWh and 0.077 EUR/kW in the three pricing periods and the daily consumptions are 50% of those considered in CASE 6.

Table 6 reports the revenues and the costs due to the sale of electricity between the building and the utility, evaluated for the System Led and the Market Led algorithms. The electricity price has been assumed equal to 0.11 EUR/kWh, 0.0969 EUR/kWh and 0.077 EUR/kWh for pricing periods F1, F2 and F3, respectively (CASE 1).

The percentage economic saving of the Market Led algorithm with respect to the System Led algorithm is 0.56%. Therefore, in the considered case the new algorithm is not able to give a significant advantage with respect to the classical one.

Nevertheless, the performance of the Market Led algorithm depends on the rate between the production and the demand of the building. Considering the same system with consumptions equal to 50% of those represented in Figure 10, the results in Table 7 are obtained (CASE 2).

The percentage economic saving of the Market Led algorithm with respect to the System Led algorithm is about 10%.

It is important also to investigate how the Market Led algorithm behaves in presence of high differences between F1 and F23 electricity prices. Therefore, simulations have been carried out with the two different consumption profiles considered above and imposing the following electricity prices: 0.22 EUR/kWh, 0.0969 EUR/kWh and 0.077 EUR/kWh for pricing periods F1, F2 and F3, respectively. The elaboration gives the results reported in Table 8 (CASE 3) and Table 9 (CASE 4).

The percentage economic saving of the Market Led algorithm with respect to the System Led algorithm is about 1.2% and 18% for the third and fourth considered cases, respectively.

Finally, other two extreme cases are presented (CASE 5 and CASE 6 reported in Table 10 and Table 11). The following prices are considered: F1 0.39 EUR/kWh, F2 0.0969 EUR/kWh, F3 0.077 EUR/kWh. Finally, Table 12 reports the comparison of the results for the six examined cases.

In particular, Table 12 shows that:

• In case of low difference between peak and off-peak prices, the Market Led algorithm does not provide any significant benefit for the end-user with respect to the System Led algorithms. Moreover, increasing the size of the storage with respect to the electricity consumptions, poorly increase producer’s revenue;

• In case of high difference between peak and off-peak prices, the Market Led algorithm assures higher revenues to the producer and the benefits increase when consumptions are lower (or, alternatively, if the storage capacity increases).