CN107608237B - Hardware resource optimization control method based on photovoltaic system semi-physical simulation - Google Patents
Hardware resource optimization control method based on photovoltaic system semi-physical simulation Download PDFInfo
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Abstract
The invention provides a hardware resource optimization control method based on photovoltaic system semi-physical simulation, and relates to the technical field of electrical engineering. A hardware resource optimization control method based on photovoltaic system semi-physical simulation firstly judges the number of CPUs (central processing units) required by each process, and if the number of CPUs required by each process is larger than that of CPUs of a photovoltaic system, the photovoltaic system is optimized. And calculating the weight of each task process of the photovoltaic system to obtain the running priority of each process, and finally obtaining the optimized running time of each process, thereby realizing the hardware resource optimization of the photovoltaic system semi-physical simulation. According to the hardware resource optimization control method based on photovoltaic system semi-physical simulation, the occupation and the processing time of hardware resources are controlled and optimized according to each process, the phenomenon that multiple processes share the same CPU can be effectively avoided, the running speed of the system process is obviously improved, and the system is more stable.
Description
Technical Field
The invention relates to the technical field of electrical engineering, in particular to a hardware resource optimization control method based on photovoltaic system semi-physical simulation.
Background
With the development of global economy, new energy power generation technology is also rapidly advanced. Solar energy, which is the most widespread and clean in resource amount, is one of the most potential renewable energy sources. In the 21 st century, the solar photovoltaic power generation industry in the world develops rapidly, the market application scale is continuously enlarged, and the solar photovoltaic power generation industry plays an increasingly important role in the development of subsequent energy. However, as the scale of the photovoltaic system connected to the power grid is enlarged, the problem of imbalance of hardware resource distribution is more obvious, so that the performance of hardware is reduced, the operation rate of the system is reduced, and the further development of the photovoltaic power generation system is greatly limited. Therefore, there is a need for efficient control and allocation of hardware resources.
Existing hardware resources are divided into computing resources and storage resources. A computing resource, i.e., a CPU (Central processing unit). From a system perspective, having multiple CPUs or one multicore CPU means that multiple tasks can be performed simultaneously. External memory is managed through standard I/O (input/output), and internal memory is accessed directly by the CPU through the system bus.
In the prior art, the hardware performance is limited, a large amount of hardware performance resources are occupied by some processes, the situation that one CPU is shared by multiple tasks may occur, redundant CPUs are idle, and the phenomenon cannot be effectively avoided by the existing optimization method.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a hardware resource optimization control method based on photovoltaic system semi-physical simulation, which realizes reasonable distribution of hardware resources.
A hardware resource optimization control method based on photovoltaic system semi-physical simulation comprises the following steps:
step 1: constructing a semi-physical simulation system of the photovoltaic system, and measuring simulation parameters of the simulation system;
the simulation parameters comprise: node number P of circuit topology structure diagram related to photovoltaic system hardware resourcesjNumber of branches PZThe number W of differential equations to be calculated when the differential equations of the RLC circuit of the photovoltaic system are solvedgThe number B of virtual meters required in input and output control of the photovoltaic systemxThe total number N of CPUs used for the photovoltaic system physical simulation;
step 2: the method comprises the following steps of calculating the number of hardware resources (CPU) required by three processes of circuit topology generation, RLC circuit differential equation solution and virtual instrument control in the photovoltaic system semi-physical simulation process, and specifically comprises the following steps:
step 2.1: calculating the quantity of CPUs (central processing units) required by circuit topology generation in the photovoltaic system semi-physical simulation process;
in the photovoltaic system semi-physical simulation process, a calculation formula of the number of CPUs required by the generation of a circuit topological structure is shown as the following formula:
wherein, PnGenerating the required number of CPUs, P, for a circuit topologyjAnd PZThe number of nodes and the number of branches of the circuit topology structure chart are respectively;
step 2.2: calculating the number of CPUs (central processing units) required by solving the RLC circuit differential equation in the photovoltaic system semi-physical simulation process;
in the photovoltaic system semi-physical simulation process, a calculation formula of the number of CPUs required by the differential equation of the RLC circuit in the solution is shown as the following formula:
wherein, WnNumber of CPUs, W, required for RLC circuit differential equation solutiongIs the number of differential equations, PjAnd PZThe number of nodes and the number of branches of the circuit topology structure chart are respectively;
step 2.3: calculating the number of CPUs (central processing units) required by control of a virtual instrument in input and output control in the semi-physical simulation process of the photovoltaic system;
in the photovoltaic system semi-physical simulation process, a calculation formula of the number of CPUs (central processing units) required by virtual instrument control in input and output control is shown as the following formula:
wherein, XnNumber of CPUs required for virtual meter control, BxThe number of the virtual instruments is;
and step 3: judging whether the total number of CPUs (Central processing units) required by running of each process in the photovoltaic system semi-physical simulation process is larger than the total number N of CPUs used for photovoltaic system physical simulation, if so, executing the step 4, and otherwise, ending the hardware resource optimization control of the photovoltaic system semi-physical simulation;
and 4, step 4: the method for calculating the time required by running each process for one cycle in the CPU operation processing in the photovoltaic system semi-physical simulation comprises the following specific steps:
step 4.1: the weight of the CPU occupied by each process in the photovoltaic system semi-physical simulation during the independent operation is calculated, and the calculation formula is as follows:
in the formula, ximThe number of CPUs required for the ith process to operate independently in the mth operating cycle within 2 hours, wherein m is 1, 2 … 5;iweight of the ith process, i is 1, 2, … n, n is the total number of processes in the photovoltaic system semi-physical simulation, βiβ is the influence factor of the process weight in the current running period of the ith process on the number of CPUs required by the next running period of the processiThe value of (A) is shown as follows:
step 4.2: calculating the time T required by each process of CPU operation processing to run for one periodiThe calculation formula is as follows:
wherein, TniThe time of one cycle for the operation of the ith process;
and 5: the hardware resource use condition in photovoltaic system semi-physical simulation is optimized, and the specific method comprises the following steps:
when the total amount of the CPU is less than the total amount of the CPU required by each process, the priority function of the process is used for sequencing the processes from high to low according to the priority degree, and the priority function is shown as the following formula:
wherein, YkiIs the priority function of the ith process, k is the prioritized sequence number of the ith process, k is 1, 2, … n, TiIs the operation time of the ith process,iis the weight of the ith process;
in the running process of each process of the photovoltaic system semi-physical simulation, the process with high priority runs firstly, and the running time function T' of each optimized process is as follows:
wherein ζ ═ ekK is the sequence number of the ith process according to the priority;
step 6, in the photovoltaic system semi-physical simulation, after hardware resource allocation and optimization are carried out on the system, comparing the running time of each process without hardware resource control, if the running time of each process after optimization is less than the running time before optimization, ending the optimization of the photovoltaic system semi-physical simulation system, otherwise, executing the step again, and adjusting the influence factors β of each processiAnd (4) re-optimizing the semi-physical simulation photovoltaic system.
According to the technical scheme, the invention has the beneficial effects that: according to the hardware resource optimization control method based on photovoltaic system semi-physical simulation, the number of the required CPUs is distributed according to the weight of each process, the condition that one CPU is shared by multiple tasks is avoided, resources are reasonably distributed, and the system running speed is increased. When the total amount of the CPU is less than the total amount of the CPU required by each process, the processes are subjected to priority sequencing according to the priority function of the processes, so that the processes with high priorities run first, the processing efficiency of the system is improved, and the system is more stable.
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Fig. 1 is a flowchart of a hardware resource optimization control method based on photovoltaic system semi-physical simulation according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
A hardware resource optimization control method based on photovoltaic system semi-physical simulation is disclosed, as shown in FIG. 1, and comprises the following steps:
step 1: constructing a semi-physical simulation system of the photovoltaic system, and measuring simulation parameters of the simulation system;
the simulation parameters comprise: number of nodes P of circuit topology structure diagram related to hardware resources of photovoltaic systemjNumber of branches PZNumber W of equations when differential equation of RLC circuit is solvedgNumber of virtual meters B required for input/output controlxThe total number N of CPUs used for the photovoltaic system physical simulation;
in the embodiment, the parameters influencing the CPU occupation are measured and monitored, the measurement time interval is one hour, and the precision of the parameters influencing the CPU occupation measured in the time interval is higher. After detection, the number P of nodes of the circuit topology structure chartj20, number of branches PZTo 35, when the differential equation of the RLC circuit is solvedNumber of differential equations W to be calculatedgIs 5, and the number of virtual meters BxThe total number N of CPUs used in the physical simulation of the photovoltaic system is 10, and 12.
Step 2: the method comprises the following steps of calculating the number of hardware resources (CPU) required by three processes of circuit topology generation, RLC circuit differential equation solution and virtual instrument control in the photovoltaic system semi-physical simulation process, and specifically comprises the following steps:
step 2.1: calculating the quantity of CPUs (central processing units) required by circuit topology generation in the photovoltaic system semi-physical simulation process;
the number P of nodes in the circuit topology structure chartjNumber of sum branches PZThe number of CPUs P required for generating the circuit topologynComprises the following steps:
step 2.2: calculating the number of CPUs (central processing units) required by solving the RLC circuit differential equation in the photovoltaic system semi-physical simulation process;
number of differential equations WgNode number P of circuit topology structure chartjNumber of sum branches PZCalculating the number W of CPUs required for solving the RLC differential equationnAs shown in the following formula:
step 2.3: calculating the number of CPUs (central processing units) required by control of a virtual instrument in input and output control in the semi-physical simulation process of the photovoltaic system;
the number of the virtual meters is BxCalculating the number X of CPUs required by the control of the virtual instrumentnComprises the following steps:
according to the result of the calculation of the detection data, the circuit topology structure generates the required CPU number Pn3.8, the differential equation of the RLC circuit solves the required number of CPUs Wn5.3, deficiencyNumber X of CPUs required for controlling analog instrumentn＝4.9。
And step 3: judging whether the total number of CPUs (Central processing units) required by running of each process in the photovoltaic system semi-physical simulation process is greater than the total number N of CPUs used for photovoltaic system physical simulation, if so, executing the step 4, otherwise, ending the hardware resource optimization control of the photovoltaic system semi-physical simulation;
in this embodiment, the total number of the CPUs required for generating the circuit topology structure, solving the RLC circuit differential equation, and controlling the virtual instrument is 14, which is greater than the total number of the CPUs used for the photovoltaic system physical simulation by 12, so that step 3 needs to be performed to perform optimal control on hardware resources of the photovoltaic system semi-physical simulation.
And 4, step 4: the method for calculating the time required by running each process for one cycle in the CPU operation processing in the photovoltaic system semi-physical simulation comprises the following specific steps:
step 4.1: the weight of the CPU occupied by each process in the photovoltaic system semi-physical simulation during the independent operation is calculated, and the calculation formula is as follows:
in the formula, ximThe number of CPUs required for the ith process to operate independently in the mth operating cycle within 2 hours, wherein m is 1, 2 … 5;iweight of the ith process, i is 1, 2, … n, n is the total number of processes in the photovoltaic system semi-physical simulation, βiβ is the influence factor of the process weight in the current running period of the ith process on the number of CPUs required by the next running period of the processiThe value of (A) is shown as follows:
step 4.2: calculating the time T required by each process of CPU operation processing to run for one periodiThe calculation formula is as follows:
wherein, TniThe time of one cycle for the operation of the ith process;
in this embodiment, the calculation result in step 2 is used to calculate the weight of the CPU occupied by each process in the photovoltaic system semi-physical simulation when all the processes are running simultaneously, and the weight calculation is determined β according to the current weight occupiediValue of (a), default βiTaking 0.01, and calculating the operation time T of each processi。
Calculating the weight of the generation process of the circuit topology structure as1The CPU processing time of this process is T0.321About for 9 min; the weight of the differential equation solving process of the RLC circuit is2The CPU processing time of this process is T0.442About 13 min; the weight of the virtual instrument control process is3The CPU processing time of this process is T0.413≈11min。
And 5: the hardware resource use condition in photovoltaic system semi-physical simulation is optimized, and the specific method comprises the following steps:
when the total amount of the CPU is less than the total amount of the CPU required by each process, the priority function of the process is used for sequencing the processes from high to low according to the priority degree, and the priority function is shown as the following formula:
wherein, YkiIs the priority function of the ith process, k is the prioritized sequence number of the ith process, k is 1, 2, … n, TiIs the operation time of the ith process,iis the weight of the ith process;
in the running process of each process of photovoltaic system semi-physical simulation, the process with high priority runs first, and the time function T of running of each process after optimizationi' is:
wherein ζ ═ ekK is the numberSequence numbers of i processes according to the priority;
step 6, in the photovoltaic system semi-physical simulation, after hardware resource allocation and optimization are carried out on the system, comparing the running time of each process without hardware resource control, if the running time of each process after optimization is less than the running time before optimization, ending the optimization of the photovoltaic system semi-physical simulation system, otherwise, executing the step again, and adjusting the influence factors β of each processiAnd (4) re-optimizing the semi-physical simulation photovoltaic system.
In this embodiment, the priority function value Y of the circuit topology generating process is obtained by calculation11Priority function value Y of RLC circuit differential equation solving process 12.52212.1, the value of the priority function of the virtual meter control process is Y3311.4, the priority degrees are sorted from high to low into a generation process of a circuit topology, an RLC circuit differential equation solving process and a virtual instrument control process.
The estimated processing time after the generation process of the circuit topological structure is optimized is T1' approximately equals 5.3min, and the processing time after the differential equation solving process of the RLC circuit is optimized is T2' approximately equals 8.1min, and the processing time after the control process of the virtual instrument is optimized is T3′≈6.4min。
From the calculation results, in the photovoltaic system semi-physical simulation, the running time of each process can be shortened by 35-50% compared with the running time of each process without hardware resource control after the system performs hardware resource allocation and optimization.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions and scope of the present invention as defined in the appended claims.
Claims (4)
1. A hardware resource optimization control method based on photovoltaic system semi-physical simulation is characterized by comprising the following steps: the method specifically comprises the following steps:
step 1: constructing a semi-physical simulation system of the photovoltaic system, and measuring simulation parameters of the simulation system;
the simulation parameters comprise: node number P of circuit topology structure diagram related to photovoltaic system hardware resourcesjNumber of branches PZThe number W of differential equations to be calculated when the differential equations of the RLC circuit of the photovoltaic system are solvedgThe number B of virtual meters required in input and output control of the photovoltaic systemxThe total number N of CPUs used for the photovoltaic system physical simulation;
step 2: the method comprises the following steps of calculating the number of hardware resources (CPU) required by three processes of circuit topology generation, RLC circuit differential equation solution and virtual instrument control in the photovoltaic system semi-physical simulation process, and specifically comprises the following steps:
step 2.1: calculating the quantity of CPUs (central processing units) required by circuit topology generation in the photovoltaic system semi-physical simulation process;
step 2.2: calculating the number of CPUs (central processing units) required by solving the RLC circuit differential equation in the photovoltaic system semi-physical simulation process;
step 2.3: calculating the number of CPUs (central processing units) required by control of a virtual instrument in input and output control in the semi-physical simulation process of the photovoltaic system;
and step 3: judging whether the total number of CPUs (Central processing units) required by running of each process in the photovoltaic system semi-physical simulation process is larger than the total number N of CPUs used for photovoltaic system physical simulation, if so, executing the step 4, and otherwise, ending the hardware resource optimization control of the photovoltaic system semi-physical simulation;
and 4, step 4: the method for calculating the time required by running each process for one cycle in the CPU operation processing in the photovoltaic system semi-physical simulation comprises the following specific steps:
step 4.1: the weight of the CPU occupied by each process in the photovoltaic system semi-physical simulation during the independent operation is calculated, and the calculation formula is as follows:
in the formula, ximThe number of CPUs required for the ith process to operate independently in the mth operating cycle within 2 hours, wherein m is 1, 2 … 5;iweight of the ith process, i is 1, 2, … n, n is the total number of processes in the photovoltaic system semi-physical simulation, βiβ is the influence factor of the process weight in the current running period of the ith process on the number of CPUs required by the next running period of the processiThe value of (A) is shown as follows:
step 4.2: calculating the time T required by each process of CPU operation processing to run for one periodiThe calculation formula is as follows:
wherein, TniThe time of one cycle for the operation of the ith process;
and 5: the hardware resource use condition in photovoltaic system semi-physical simulation is optimized, and the specific method comprises the following steps:
when the total amount of the CPU is less than the total amount of the CPU required by each process, the priority function of the process is used for sequencing the processes from high to low according to the priority degree, and the priority function is shown as the following formula:
wherein, YkiIs the priority function of the ith process, k is the prioritized sequence number of the ith process, k is 1, 2, … n, TiIs the operation time of the ith process,iis the weight of the ith process;
in the running process of each process of the photovoltaic system semi-physical simulation, the process with high priority runs firstly, and the running time function T' of each optimized process is as follows:
wherein ζ ═ ekK is the sequence number of the ith process according to the priority;
step 6, in the photovoltaic system semi-physical simulation, after hardware resource allocation and optimization are carried out on the system, comparing the running time of each process without hardware resource control, if the running time of each process after optimization is less than the running time before optimization, ending the optimization of the photovoltaic system semi-physical simulation system, otherwise, executing the step again, and adjusting the influence factors β of each processiAnd (4) re-optimizing the semi-physical simulation photovoltaic system.
2. The hardware resource optimization control method based on photovoltaic system semi-physical simulation according to claim 1, wherein: step 2.1 the calculation formula for generating the required number of CPUs by the circuit topology structure is shown as follows:
wherein, PnGenerating the required number of CPUs, P, for a circuit topologyjAnd PZThe number of nodes and the number of branches of the circuit topology structure chart are respectively.
3. The hardware resource optimization control method based on photovoltaic system semi-physical simulation according to claim 1, wherein: step 2.2 the calculation formula of the number of CPUs required for solving the differential equation of the RLC circuit is shown as follows:
wherein, WnNumber of CPUs, W, required for RLC circuit differential equation solutiongIs the number of differential equations, PjAnd PZThe number of nodes and the number of branches of the circuit topology structure chart are respectively.
4. The hardware resource optimization control method based on photovoltaic system semi-physical simulation according to claim 1, wherein: step 2.3, a calculation formula of the number of CPUs required by the control of the virtual instrument in the input and output control is shown as the following formula:
wherein, XnNumber of CPUs required for virtual meter control, BxThe number of the virtual meters.
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