Dynamic Reconfiguration Systems for PV Plant: Technical 2 and Economic Analysis 3

: Solar plants suffer of partial shading and mismatch problems. Without considering the 9 generation of hot spots and following security issues, a monitor system for the health of a PV plant should 10 be useful to drive a dynamic reconfiguration system (DRS) to solve bottlenecks due different panels 11 shading. In the years, different DRS architectures have been proposed, but no suggestion about costs and 12 benefits have been provided. Starting from technical subjects such as differences of the topologies driving 13 the hardware complexity and number of components, this paper identifies the cost of DRS and its lifetime, 14 and basing on these issue it faces an economic analysis for a 6 kWp PV plant in different countries of 15 United Europe, in which dissimilar incentives policies have been considered.

In this section, a brief state of art of the Dynamic Reconfiguration Systems (DRS) and a technicaleconomic analysis, of the four-case studied, are reported.

98
The first case under test has been presented in [22]. The authors propose an optimised Switch Set (SWS) 99 topology for reconfiguration of PV panels based on Particle Swarm Optimization (PSO) algorithm. Figure 1 100 shows the optimised topology structure suggested by the authors, in which there are four lines and ten

114
The number of switches required for the case 2 can be evaluated as:

115
(2) In [24] a Photovoltaic Array Switching algorithm is presented. This algorithm, in order to find the best 116 configuration of a PV array, is based on the use of only two parameters: the array load voltage and the PV 117 module's temperature. The study has been focused on the evaluation of the performance of four PV

121
The number of switches necessary in case 3 is equal to:

122
(3) The last case taken into account in this work is presented in [25]. The case 4 is a system configuration 123 approach using adaptive architecture based on a switching matrix. The adaptive strategy is based on the fact 124 that the switching matrix allows to rearrange the active PV modules in series into multiple strings to meet 125 the required voltage level. Figure 4 shows the proposed switching matrix of the case 4.

128
Also, in this case, the number of switches of the matrix depends by the number of modules in the PV array.

129
The number of switches can be expressed as:

130
(4) where the terms 2dc and 2inv represent the switches to connect the PV array with the inverter and the dc 131 converter.

132
In the next section, the cost estimation analysis is reported.

135
The cost of each reconfigurator system has been evaluated on the basis of the direct proportionality 136 between the number of switches composing the system and the cost of the technology needed to produce it. For each of the four considered reconfiguration cases, a cost estimation of the reconfiguration system 138 has been carried out according to the following procedure: for each case, the required amount of for each of the selected components, a price is given, as provided by a major distributor of electronics [26] 142 Generally, the hardware of a dynamic reconfigurator basically consists of three different parts: the 143 switching matrix, the sensing network and the driving circuit.

144
The switching matrix includes all the switches that are used in the reconfiguration system. Taking      Note that each driver is supposed to drive one MOSFET.

195
In 204 Table 6 reports the data referring to both types of switches and to the four considered cases of 205 reconfiguration, obtained from (5). Note that the number of total reconfigurations Ryr has been considered 206 the same for all the cases. According to that, the total cost evaluation, including the overall system, is considered and reported in Table   210 7 for different cases of years to come before the switches are changed. Table 7. Cost evaluation according to the estimated endurability, as reported in Table 6  The economical contributions concerning the switches and the overall system, as reported in Table 7, 214 arise from the data reported in Table 1 and Table 2 respectively.

215
Note that the configurations with the lowest number of switches are less convenient if the only price of 216 the switches is considered, supposed that in the same number of years they require to be changed a higher 217 number of times. On the contrary, if the total cost of the reconfigurator is considered, the cases with the 218 lowest number of switches are the most convenient. Indeed, the initial price in terms of sensors, drivers and

219
MOSFETs is generally higher if the number of mechanical switches is higher, due to the higher hardware 220 complexity.

221
Note as well as that if a low number of switches is associated to a more complex algorithm, so that the 222 reconfiguration frequency is higher, the frequency of maintenance increases. As example, Table 8 Figure 6 shows the effect of a shadow due to the presence of a pole by considering a PV DRS scheme.

241
The hypothesis is that each panel has three lines of cells and is connected to the DRS. DSR is connected to a 242 two channels inverter.

260
In order to test the DRS, an artificial shadow has been created.  Table 10 recapitulates the behavior of the DRS with shading and without; P1-P5 are the powers of the not shadowed panels, P6 is the power of the shadowed one in three cases, I is the current of the system in the different cases taken into account.

279
New voltages indicate the new power conditions. The DRS is able to regroup similar irradiated panels

286
In the following part three cases are evaluated: case 1, only a line has been interrupted; case 2, two lines 287 were interrupted; case 3, the whole panel is shadowed.

288
By excluding the shaded panels there will be 16.7% of losses. DRS can enable the power increases 289 shown in Table 11.

293
Data presented in Table 11 can be plotted in Figure 10

306
Case 3 shows the real performance of the DRS. Between loads C and D the maximum power point is 307 performed. By considering the overall behavior of two shaded strings used simultaneously, a possible 308 performance increase between 12 and 25% can be stated.

312
The previously obtained performances, consider only a shaded panel, and the logic is to maintain it 313 (partially shaded) or exclude it (totally obscured). Now if two panels are shaded there is the possibility of 314 placing in parallel. Panels named 6 and 7, can be re-configured to ensure the maximum current of the arrays.

315
This feature requires a more evolved DRS, which can put in parallel panels belonging to different arrays, the 316 sum of which currents is equal to the current of not obscured panels.

320
This feature is useful only when it considers the case 2 as shown in Table 13.

321
The performances of different DRS are a mixture of the ones presented in Tables 12 and 13.

322
For the economic analysis the increased power given by the reconfigurator is taken as an increase of the 323 energy produced during the day.
In order to carry out a complete study, the economic analysis presented in this paper take into account the benefits of an economic investment in PV field with innovative devices such as a DRS. The NPV allows 331 to evaluate the economic convenience of an investment for a specific period from a sum of cash flows 332 actualized at time zero. In (6) the mathematic expression to evaluate the NPV is reported.

344
In this study, only residential PV systems have been taken into account with 6 kWp of power. This

351
Regarding the cost of the PV plant, the average estimated price for this type of plant is about 2500 352 €/kWp (included installation).

353
In Table 14 the economic data about the PV plant under test are summarized.  The economic data for each country (average consumption per capita, production facility, energy cost 365 and incentives) have been referred of a PV plant installed in the capital of each countries. Moreover, has 366 been considered a family composed by four people that lives in the capital of each countries. In Table 15 the 367 considered economic data are reported.

379
The inverter represents the heart of the production from the solar energy. In particular, as well known,

428
considering an increment of the power equal to 20%, the NPV values obtained are reported in Table 17.