DESCRIPTION

[0001 ] The present invention relates to the technical field of monitoring electrical plants and more particularly it relates to a data processing method for associating unique identi fication codes with electrical signals provided by devices of electrical plants .

[0002 ] As it is known, some electrical plants , such as for example the plants for generating electrical energy from renewable sources comprise a very high number of devices , in particular electrical and/or electromechanical and/or electronic and/or optoelectronic devices . Examples of plants of the above-mentioned type are represented by photovoltaic or wing plants for generating electrical energy . Each one of the above-mentioned devices is generally capable of providing electrical signals , for example measurement electrical signals or status electrical signals .

[0003 ] In order to monitor the operation of an electrical plant , for example to evaluate the performances and/or ascertain the correct operation of the electrical plant , it is necessary to monitor the electrical signals provided by the devices of the electrical plant , for example by querying the devices by a control centre , for example by a remote control centre . The monitoring of the electrical signals is performed by dedicated software known to the person skilled in the art , which for example allow to monitor in real time the electrical signals .

[0004 ] However, before being able to monitor the electrical signals it is necessary to generate for each electrical signal a unique identi fication code allowing a monitoring software to identi fy uniquely each electrical signal . Said unique identi fication code generally is a string of alphanumeric characters . The generation of the unique identi fication codes generally follows rules imposed by one or more International standards .

[0005 ] The unique identi fication codes generally are strings having tens of alphanumeric characters . Each electrical plant can have tens or hundreds of electrical devices and for each one thereof generally it is requested to monitor several electrical signals . The generation of the complete lists of the unique identi fication codes for all electrical signals of interest in an electrical plant with average si ze can request the generation of tens of thousands of unique identi fication codes , for example 80 , 000 identi fication codes . Even in an electrical plant having limited or average complexity, the generation of the unique identi fication codes to be assigned to the several electrical signals is particularly burdensome , both from the economical point of view and from the point of view of the requested time , since such generation is performed manually by the responsible operators , who have to be suitably trained in advance . Moreover, even by using expert operators , the above-mentioned generation is af fected by errors which can j eopardi ze the possibility of monitoring some electrical s ignals of interest , since the human error is always possible even by using adequately trained and quali fied personnel .

[0006 ] The obj ect of the present invention is to provide an extraordinary ef fective data processing method allowing to reduce drastically the costs and the time requested for the generation of the unique identi fication codes and further allowing to reduce the possibi lity of making errors .

[0007 ] This and other obj ects are achieved by a data processing method for associating unique identi fication codes with electrical signals provided by devices of electrical plants as defined in claim 1 in its most general form, and in the claims depending therefrom in some particular embodiments .

[0008 ] The invention will be better understood from the following detailed description of embodiments thereof , made by way of example and then in no way for limiting purposes in relation to the enclosed drawings, wherein:

- figure 1 shows an example of simplified functional block diagram of a possible not limiting embodiment of an electrical plant comprising a plurality of devices;

- figure 2 shows an exemplified flow diagram of a not limiting embodiment of a data processing method for associating unique identification codes with electrical signals provided by the devices of the electrical plant.

[0009] In the enclosed figures, equal or similar elements were indicated by the same numeral references.

[0010] In figure 1 a simplified functional block diagram of a possible not limiting embodiment of an electrical plant 10 comprising a plurality of devices 1, ..D was represented. In particular, figure 1 shows a plant scheme of the electrical plant 10. In the particular example represented in figure 1, said plant scheme is a unifilar scheme .

[0011] According to an embodiment, the electrical plant 10 is a plant for producing electrical energy, for example a photovoltaic or wind plant. According to additional embodiments, the electrical plant 10 is an electrical substation or a battery energy storage system - BESS. According to additional embodiments, the electrical plant

10 could be an industrial electrical plant. [0012] The plurality of devices 1,...,D comprises electrical devices belonging to different types of devices, wherein each type of device corresponds to a respective level Lj inside the plant scheme, wherein j is an integer comprised between 1 and M and wherein LI (j = l) is a first level upstream of the plant scheme and wherein LM (j=M) is a last level downstream of the plant scheme. M is an integer having any size, for example higher than or equal to 5, higher than or equal to 7, higher than or equal to 10.

[0013] For example, in case the electrical plant 10 is a photovoltaic plant equipped with string inverters:

- the devices 1 of first level LI (j=l) are AT/MT transformers each one thereof is associated with a respective portion of the photovoltaic plant;

- the devices 2 of second level L2 (j=2) are the lines with average voltage of each bar of the AT/MT transformers of the first level LI;

- the devices 3 of the third level L3 (j=3) are the conversion units associated with each line with average voltage of the second level L2;

- the devices 4 of the fourth level L4 (j=4) are the panels with average voltage for each conversion unit of the third level L3;

- the devices of the fifth level L5 (j=5) are the AC cassettes for each panel with average voltage of the fourth level L4;

- the devices D of the sixth and last level L6 (j = 6, then, in this case M=6) are the string inverters associated with the AC cassettes of the fifth level L5.

[0014] For example, in case the electrical plant 10 is a photovoltaic plant equipped with centralized inverters, the devices of the electrical plant 10 are divided into the nine levels L1-L9 shown hereinafter:

Level LI - AT/MT transformers each one thereof is associated with a respective portion of the photovoltaic plant ;

Level L2 - Lines with average voltage of each bar of the AT/MT transformers of the first level LI;

Level L3 - Conversion units associated with each line with average voltage of the second level L2;

Level L4 - Transformers MT/BT for each conversion unit of level L3;

Level L5 - Inverters associated with the MT/BT transformers of level L4;

Level L6 - Modules constituting the inverters of level L5; Level L7 - Field cassettes of the modules of level L6;

Level L8 - Modules constituting the field cassettes of level L7;

Level L9 - The devices of the ninth and last level (then, in this case M=9) are the strings of the modules of level of the electrical plant 1 can be queried to provide at least an electrical signal. For example, the devices 1,...,D can be queried by a monitoring centre, for example by a remote monitoring centre. The electrical signals provided by the devices 1,...,D for example are measurement signals and/or status signals, for example signals for measuring electrical quantities, such as voltages, currents, electric power, etc. Generally, the electrical signals bear information about the status or the operation of the devices 1,...,D and for this they can be defined as status or operation electrical signals.

[0016] In order to be able to monitor and/or control the electrical plant 10, in particular the devices 1, ..,D of the electrical plant 10, it is necessary to associate in advance a unique identification code with each electrical signal provided by each device 1, ..,D which one wants to monitor or control. Such unique identification code actually is a unique tag assigned to the respective electrical signal. The unique identification code comprises encoded data which allow to identify uniquely the electrical signal, both the device providing said electrical signal, and the positioning of the device inside the plant scheme. [0017 ] For example , for photovoltaic and wind electrical plants the Applicant developed and adopted a rule for defining the unique identi fication codes called EDM (Enel Data Model ) , based thereupon each unique identi fication code has a process section encoded in accordance to the standard ISO / IEC 81346 and a section of logical node , encoded in accordance to the standard IEC 61850 for photovoltaic plants and in accordance to the standard IEC 61400 for wind plants .

[0018 ] By now making j oint reference to figures 1 and 2 exempli fying and not limiting embodiments of a data processing method 100 for associating a unique identi fication code with each one of a plurality of electrical signals provided by the plurality of devices 1 , ..., D of the electrical plant 10 will be now described .

[0019 ] The data processing method 100 comprises a step 101 of arranging, that is providing, a processing unit and a storage unit operatively connected thereto . For example , the processing unit is , or comprises , one or more industrial computers , one or more mainframe computers , a computer cluster , one or more personal computers . The storage unit preferably comprises non-volatile storage unit .

[0020 ] The data processing method 100 is implemented by a software adapted and configured to define a bidimensional matrix of alphanumeric characters representative of the plant scheme of the electrical plant 10. Such bidimensional matrix, herein also called "final matrix" or "final bidimensional matrix", is defined by the data processing method 100 for subsequent steps at the end thereof provisional bidimensional matrixes are obtained, until defining the final bidimensional matrix representative of the plant scheme.

[0021] In this context under the term "alphanumeric" both combinations directly implemented with numbers and/or letters, and other types of graphic representations assignable thereto (bar codes, QR code, etc.) are meant. [0022] The data processing method 100 further comprises the steps of:

Fl (LI) - receiving as input Fl (Lj) , wherein j = l, a total number N_L1 of devices 1 of the first level LI and storing said total number N_L1;

F2 (L1) - defining F2 (Lj) , wherein j = l, a first bidimensional provisional matrix Mx_l having a number of rows equal to the total number N_L1 and a number of columns equal to M;

F3 (L1) - in each element of a first column vector with size N_L1 of the first bidimensional provisional matrix Mx_l storing F3 (Lj) , wherein j=l, at least a respective alphanumeric character adapted to identify uniquely in the first bidimensional provisional matrix Mx_l a respective device 1 of first level LI.

[0023] For example, one assumes that the electrical plant 10 is a photovoltaic plant with string inverter. In this case, for example, the software implementing the data processing method 100 determines that the number of levels M is equal to six. The number of levels can be determined automatically by the software or entered by a user by means of an HMI (Human Machine Interface) interface, for example by means of a keyboard and/or a mouse or a similar or equivalent device. In step Fl (LI) , then in step Fl (lj) wherein j = l, a user enters the total number N_L1 of the devices of the first level LI. In the example of figure 1 the total number N_L1 of devices of first level is equal to 2. This involves that in this example the electrical plant 10 has two AT/MT transformers.

[0024] Once known the number of levels M=6 and the number of devices of first level N_L1=2, in step F2 (L1) , for example through allocation of a respective data structure in memory, a provisional bidimensional matrix Mx_l having a number of rows equal to N_L1=2 and a number of columns equal to M=6 is defined. In the herein described example one decided to construct the bidimensional final matrix by keeping fixed the number of columns equal to M=6 and by varying progressively the number of rows at each level but it is clearly possible to invert the situation, by obtaining a transposed bidimensional final matrix with respect to the one obtainable with the herein described data processing method 100 . In the speci fic case of the example of figure 1 , the first provisional matrix Mx_l then is a matrix 2x6 of the type illustrated in the herebelow shown table , wherein in the table the first row was added only by way of description to show the number o f level and wherein then the matrix at issue is represented only by the empty cells of the matrix of the herebelow illustrated table :

[0025 ] The data processing method 100 in the subsequent step F3 ( Lj ) , wherein j =l , stores in each element of a first column vector, having a number of elements equal to the number of rows N_L1=2 of the first bidimensional provisional matrix Mx_l , at least a respective alphanumeric character adapted to identi fy uniquely in the first bidimensional provisional matrix Mx_l a respective device 1 of first level LI . In the speci fic example , the above- mentioned first column vector is a column vector having two rows and in particular the column vector corresponding to the first level LI . [0026] For example, in the first column vector, for the first device 1 of level LI the alphanumeric character A is stored and for the second device of level LI the character B is stored. The first column vector then is the vector [A, B] . In this case, the first provisional bidimensional matrix Mx_l at the end of step F3 (L1) then becomes:

[0027] Then, one goes to the subsequent level L2 and in step F1 (L2) , that is step Fl (Lj) wherein j=2, is received as input, for example by an operator entry, for each one of the devices 1 of level LI the number of devices 2 of level L2 which in the plant scheme are operatively connected immediately downstream of the respective device 1 of level LI. A total number N_L2 of devices 2 of level L2 is calculated. For example, a user enters that to the first device of level LI "A" three devices of level L2 are connected and that to the second device of level LI two devices of level L2 are connected. In this case, the total number N_L2 of the devices of level L2 then is equal to five. The devices of level 2 for example are the lines with average voltage of each bar of the AT/MT transformers of the first level LI. In the specific case of the example of figure 1, a second provisional matrix Mx_2 is then defined which then is a matrix 5x6 of the type illustrated in the herebelow reported table (also in this case the first row of the table was added only by way of description to show the number of level) :

[0028]

[0029] Advantageously, the elements added in the first column vector (level LI) to vary the number of rows of the bidimensional matrix are filled up with alphanumeric characters equal to those of the immediately preceding elements and then it is obtained:

[0030] The data processing method 100 in the subsequent step F3 (L2) , then F3 (Lj) wherein j=3, stores in each element of a second column vector with si ze N_L1=6 of the second bidimensional provisional matrix Mx_2 at least a respective alphanumeric character adapted to identi fy uniquely in the second bidimensional provisional matrix Mx_2 a respective device 2 of first level L2 . It is clear that the second column vector is a vector immediately adj acent to the first column vector . In the speci fic example the above-mentioned second column vector is the column vector corresponding to the second level L2 .

[0031 ] For example , in the column vector of level L2 :

- for the first device 2 of level L2 the alphanumeric character 1 is stored; for the second device of level L2 the alphanumeric character 2 is stored; for the third device of level L2 the alphanumeric character 3 is stored; for the fourth device of level L2 the alphanumeric character 1 is stored; for the fi fth device of level L2 the alphanumeric character 2 is stored .

In this case , the second provisional bidimensional matrix

Mx_2 at the end of step F3 ( L2 ) then becomes ( still by excluding the first row of table ) :

[0032 ] It ' s worth noting that the unique alphanumeric codes Al , A2 , A3 , Bl , B2 obtained by combining the codes along one same row of the second provisional bidimensional matrix Mx_2 are suf ficient to identi fy uniquely the respective devices of level L2 by further speci fying the positional relation in the plant scheme with respect to the preceding level LI . In fact , the unique alphanumeric code Al identi fies a first device of level L2 connected upstream of the first device 1 "A" of level LI , the unique alphanumeric code A2 identifies a second device of level L2 connected upstream of the first device 1 "A" of level LI , the unique alphanumeric code A3 identi fies a third device of level L3 connected upstream of the first device 1 "A" of level LI , the unique alphanumeric code Bl identi fies a first device of level L2 connected upstream of the second device 1 "B" of level LI , the unique alphanumeric code B2 identifies a second device of level L2 connected upstream of the second device 1 "B" of level LI .

[0033 ] It is further to be noted that when passing from a preceding level to a subsequent level , that is in the passage leading to define a subsequent provisional matrix starting from a preceding provisional matrix , the number of rows is never decreased, but it is always increased or, in a theoretically possible hypothesis , but unlikely to occur from practical point of view, remains equal . In other words , in the subsequent iterations provisional matrixes are generated, the number of rows thereof is never decreasing . For example , i f for a given device of level LI any device of level L2 did not exist immediately downstream, in the second provisional matrix constructed for level L2 a row corresponding to the provisional matrix constructed for level LI would be however kept , which row for example could be filled up with a dedicated alphanumeric character ( for example " 0" or " *" ) , or with a dedicated alphanumeric string ( for example "N/A" or "null" ) or it could be left empty . The fact of however keeping a row, that is the fact of never decreasing the number of rows from an iteration to the subsequent one , would then allow in each case to reach the process end, since for example in the construction of the provisional matrix of further subsequent level , for example of level L3 , the number of rows to be provided would be equal to that o f the number of the devices of level L3 placed downstream of a device of level LI even in absence of the devices of level L2 placed downstream of the above-mentioned device of level LI .

[0034] Still by making reference to the example of figure

1, by performing the steps described above for level L3 (then j=3) , a total number of devices N_L3 of level 3 equal to ten is obtained.

[0035] The second provisional matrix Mx_2 is then expanded, even in this case by increasing the number of rows, to define a third provisional matrix with size 10x6: whose elements up to level L3 are for example compiled until defining the third provisional matrix L3 represented hereinafter (still by excluding the first row of table) :

[0036] The elements of level L3 for example are the conversion units associated with each line with average voltage of the second level L2. [0037] In the data processing method 100 the steps Fl (LI) ,

F2 (Lj) , F3 (Lj) are repeated iteratively identically or analogously to what described above until the last level LM, wherein then j=M.

[0038] For example, still with reference to the plant scheme of figure 1, after step F3 (Lj) wherein j=4 a fourth provisional matrix of the type illustrated in the herebelow reported table is obtained (still by excluding the first row of table) .

[0039] The devices of level L4 are for example the MT/BT transformers for each conversion unit of level L3. It is clear that, for example, the code A121 identifies uniquely the first MT/BT transformer "1" of the second conversion unit "2" of the first line with average voltage "1" of the first AT/MT transformer "A". [0040 ] For the sake of exposure brevity, one will avoid to repeat the description of the subsequent iterative steps of the construction of the final bidimensional matrix . I t is clear that in case of the electrical plant 10 of figure 1 , wherein the total number of devices D of the last level is equal to 26 , a final bidimensional matrix having 26 rows and LM columns will be obtained . For example , i f the number of levels M=7 , then the final bidimensional matrix will be a matrix having a si ze equal to 27x7= 182 , that is a matrix of 26 rows and 7 columns .

[0041 ] The data processing method 100 further comprises a step 102 of storing the final bidimensional matrix Mx_M in the storage unit .

[0042 ] The data processing method 100 further comprises a step 105 for accessing a computer library containing for each electrical signal a partially precompiled identi fication code . The data processing method 100 further comprises a step 106 of completing for each electrical signal the compilation of the partially precompiled identi fication code by using directly or indirectly alphanumeric characters corresponding to elements of the final bidimensional matrix Mx_M and associating the respective so-obtained completed unique identi fication code with each electrical signal .

[0043 ] The above-mentioned computer library for example is a database inside thereof partially precompiled alphanumeric strings are stored, each one associated with a respective electrical signal . The computer library for example is stored in an Oracle database . The computer library for example includes hundreds or thousands of partially precompiled alphanumeric strings .

[0044 ] For example , in the above-mentioned computer library, each partially precompiled alphanumeric string has a format in accordance to the third row of the herebelow illustrated table . Said format coincides with the format of the unique identi fication codes which the data processing method 100 assigns to the electrical signals .

[0045 ] In the particular example , the string has a so- called process section and a so-called logical node section . For example , the process section is encoded according to the standard ISO / IEC 81346 and logical node section is encoded according to the standard IEC 61850 for photovoltaic plants and according to the standard IEC 61400 for wind plants . At least part of the alphanumeric characters of the process section are obtained starting from the elements of the bidimensional final matrix and the process section, once completed, allows to identi fy a speci fic device in the plant scheme and its relative arrangement with respect to other devices which are upstream of the plant scheme .

[0046 ] Conveniently, a prefix CJ ("Conj oint Designation" ) of the process section allows to identify uniquely an electrical plant through a string CCTPPPP which can be obtained for example once known the plant installation nation ( alphanumeric characters CC, "Country Code" ) , the plant technology ( character T , which is set for example to W for wind generation plants or to S for photovoltaic generation plants ) and the name assigned to the plant ( characters PPPP ) . For example , the prefix CJ for the photovoltaic plant in South Africa designated "Tom Burke" is ZASTOMB, wherein " ZA" is the International code CC of South Africa, "S" designates the wind technology and "TOMB" a string obtained from name "Tom Burke" .

[0047 ] The section " logical node" represents the leaf node of the database and it allows to identi fy a speci fic type of electrical signal which can be provided by a speci fic type of electrical device , by designating for example the measured quantity, the measurement unit or attributes related to the measurement format . For example , the logical node field "AAAA" designates the speci fic type of electrical device , the instance field "nn" designates the represented measurement type ( for example 1 i f the measurement is instantaneous, 2 if the analog values are

RMS real values, 3 for the peak values, 4 for the fundamental RMS values, 5 for the minimum values, 6 for the maximum values, 7 for the average values, and so on according to the reference table) , the "data object" field A. . aa designates the measured quantity (for example A...aaa = Amp if the measured quantity is the current or A..aaa = TotVA if the measured quantity is the apparent tension) and the data attribute field a...Aa designates the measurement format (for example a..Aa = mag.f if the signal bears a measurement of the width in floating point) . Therefore, an example of the logical node section compilation can be: BC001. DPVA1. Amp .mag . f . Preferably, the logical node section is a string which for each electrical signal in the library is wholly compiled.

[0048] Preferably, from the alphanumeric characters stored in the elements of the final bidimensional matrix it is possible to compile the process section, and in particular the fields BL1, BL2,... which represent different levels of breakdown ("BL" is an acronym of "Breakdown Level") . For example, in case the unique identification code, that is the unique tag, has to be assigned to an electrical signal which is provided by a device which in the plant scheme is placed downstream of a device of level LI "A" and in case both the line identified by the level L2 "2", the conversion cabin identi fied by the level L3 " 1" , the inverter identi fied by the level L4 " 1" , then the functional application of the corresponding row of the matrix allows to generate the plurality of signals present in library, whose logical node requires the expansion as far as the column L4 . For example CD .MA0201 .MSEO 1 . BAO 01 . DINV1 . VolEsp . mag . f for the "Set Point of voltage in CC" , CD .MA0201 .MSE01 .

BA001 . DINV1 . PNV . phsA. cVal . mag . f for the "Voltage of Step A in CA" or CD .MA0201 .MSE01 . BE001 . DINV1 . Hz . mag . f for the "Frequency of the alternating current" and so on, by functionally applying each row of the matrix to the plurality of signals present in library, requiring the same si ze of the plant matrix . [0049 ] In each case , it is important noting that the aboveillustrated examples are not limiting and the speci fic compilation, in step 106 , of the partially compiled alphanumeric codes stored in the computer library with i , or based upon data contained in the bidimensional definitive matrix is within the comprehension of the person skilled in the art who knows the speci fic encoding format used for de fining the unique identification codes to be assigned to the electrical signals .

[0050 ] As already at least partially explained, according to an embodiment the partially compiled code stored in the computer library comprises a prefix to be compiled . In the present example , the above-mentioned prefix was denominated Conj oint Designation ( CD) . Advantageously, the completing step 106 comprises the operations of : receiving as input data for defining said prefix comprising the following data : plant installation nation, plant technology type and plant name ;

- processing digitally said data received to determine automatically the prefix based upon a prefix compilation algorithm;

- compiling automatically all prefixes CD of the partially compiled identi fication codes of all electrical signals of a same plant so that they are all equal to said pref ix determined automatically .

[0051 ] For example , the data for defining the prefix are entered by a user through an input device , such as for example a mouse or a keyboard .

[0052 ] According to a particularly advantageous embodiment , after the step 102 of storing the final bidimensional matrix Mx_M the data processing method 100 comprises a step of receiving as input 103 a selected level L . Such level for example is entered by a user . In such embodiment , the step 106 for completing the compilation of the unique identi fication code is performed only for electrical signals provided by electrical devices belonging to levels comprised between the first level LI included and the selected level Lj included . In this way, it is advantageously possible to generate the unique identi fication codes only for some levels of the electrical plant , with significant saving in time and computational resources . This can be useful for example when, for contingent needs , it is sufficient to monitor only the signals provided by devices arranged in some highest level s of the electrical plant .

[0053 ] In accordance to an additional particularly advantageous embodiment , the data processing method 100 further comprises a step 104 of receiving as input a selected sub-set of one or more types of electrical signals . A user for example can select from a list , which is shown on a graphic interface , only some categories of signals . For example , a user can select electrical signals bearing information on currents and temperatures or signal s correlated to one or few measurement parameters of a quantity to be measured, for example by selecting the parameter "rms value" and/or the parameter "peak value" and by excluding for example the parameter " instantaneous value" . Thanks to the possibility provided by the above- mentioned step 104 , the step 106 for completing the compilation of the unique identi fication code can be performed only for the electrical signals belonging to the types of the selected sub-set . Even in this case , considerable advantages in terms of time and resources for the compilation are obtained .

[0054 ] According to an advantageous embodiment , the data processing method 100 , after the step 106 for completing for each electrical signal the compilation of the unique identi fication code , comprises a step 107 of storing for each electrical signal the respective completed unique identi fication code . In this way, the unique identi fication codes are generated once and for all and they can be used for the subsequent monitoring over time of the electrical plant 10 , except then the pos sibility of regenerating them, wholly or partially, for occurred configuration variations of the electrical plant 10 .

[0055 ] It is observed that an obj ect of the present invention is also a method for monitoring an electrical plant 10 comprising a step of querying devices 1 , 2 , ..., D of said electrical plant 10 to receive electrical signals o f status or operation of said devices , wherein the querying step is performed for each one of said electrical signals by using unique identi fication codes assigned to each one of said electrical signals according to the embodiments of the above-mentioned data processing method 100 .

[0056 ] Based upon what illustrated above , it is then possible to understand that a data processing method 100 of the above-described type allows to achieve fully the above-mentioned obj ects with reference to the state o f known art .

[0057 ] The construction of the final bidimensional matrix results to be lighter than the extensive listing comprising all data of all consultable electrical signals for a very big electrical plant such as for example a photovoltaic plant of industrial scale .

[0058 ] The generation and the implementation of the above- mentioned final matrix then can be managed, for example , even simply in the cloud thus determining a considerable saving in computational resources and memory and thus defining a clear saving in time of elaboration processes .

[0059 ] Moreover, thanks to the proposed solution, only the signals to be modelled can be selected ( that is the electrical signals therewith the unique identi fication code is to be associated) depending upon the speci fic reference level and only these are processed and in cased stored in storage unit by determining a signi ficative decrease in information to be processed with respect to the same procedure adopted by analysing all items of the final bidimensional matrix compiled with the extensive listing comprising all data o f all consultable electrical signals .

[0060 ] In this way it is possible to have a synthetic digital fingerprinting of the electrical plant and to obtain quickly and ef fectively identi fication codes of selected electrical signals . Thanks to the proposed solution it is possible to reduce compilation time , processing and storing resources to be used to produce the identi fication codes and to monitor selectively the wished electrical signals .

[0061 ] Additionally, the final matrix can be applied quickly and ef fectively to di f ferent types of wished formats of tag since it is suf ficient to modi fy coherently the corresponding library and to re-define the partially compiled codes stored in the library depending upon the wished language standards .

[0062 ] Advantageously, starting from the final matrix it is possible to obtain sub-matrixes with reduced si zes which in terms of rows and/or columns could be potentially of di f ferent lower orders than the final matrix, thus allowing to consult and to modi fy dynamically in a particularly ef fective way .

[0063 ] Additionally, the use of the above-described data processing method 100 requires a limited competence and technical precision by a user to produce a precise and reliable compilation .

[0064 ] In this way the Applicant estimated that the compilation time aimed at defining the final matrix can be extraordinary reduced (about 1/500) with respect to the compilation time required to a skilled person who compiles an extensive listing implemented on a computer.

[0065] Still, thanks to the proposed technical solution it is guaranteed that each row of the final bidimensional matrix is a row vector which detects uniquely inside the plant scheme the position of the device, whose tag identifies the respective electrical signal.

[0066] Moreover, the extremely synthetic and essential representation of the final matrix easily allows to model new electrical signals (correlated to new not original electrical devices) , during the increase in the production plant, without requiring any analysis or deep modification of the already performed modelling.

[0067] Even during reading the electrical signals provided by plant devices which, while performing similar functions, are characterized by different technical/constructive features (and then they require different modelling) , the final matrix of the plant can continue to represent it integrally: the matrix will consist of n sub-matrices, as many as there are devices with different technical features at the same time put into operation (for example string inverters and centralized inverters, weather station devices present in the weather stations or positioned in the field, and so on) . [0068] Such approach then eases:

- the automatic insertion of the new tags at the same time of the increase in the plant sizes, indifferently from the possible mixture of the features of the installed devices;

- the subsequent ease detection of the devices (and then, of the related tags of the signals) , both taken singularly and by clusters/ type (detected by the columns of the matrix) .

[0069] The data in fact can be consulted and identified dynamically: each element of the matrix transposed starting from the grid overlapped to the plant, overlaps in each element thereof to the arrangement of the totality of the plant elements participating in the process of energy transformation, thereto the production plant is assigned. [0070] Therefore, as in the plant matrix one passes from the first towards the last column, in the same way in the unifilar scheme one goes through the inverse process of energy transformation, that is from the highest to the lowest voltage level. If ideally a grid is overlapped on to the plant scheme, in which each cell of the grid coincides with the plant devices along the unifilar scheme, the transposition of such grid detects each one of the matrix elements.

[0071] Such schematization, by codifying the plant scheme, eases the consultability thereof, by simplifying the possibility of reaching all devices present in the plant scheme .

[0072 ] Without prej udice to the principle of the invention, the embodiments and the embodiment details could be widely varied with respect to what was described and illustrated by pure way of example and not for limitative purpose , however without leaving the scope of the invention as defined in the enclosed claims .