Multi-source input micro-grid control system and method based on data center

Abstract

The invention discloses a multi-source input micro-grid control system and method based on a data center in the technical field. The method comprises the following steps: receiving time input; judging a current time period type based on the time input; judging whether the generation power of the photovoltaic system is greater than all data center load power based on the current time period type; when the generated power of the photovoltaic system is larger than the load power of all the data centers, excessive power of the photovoltaic system is returned to the commercial power; and when the generated power of the photovoltaic system is not greater than the power of all the data center loads, adjusting the multi-source input system to supply power to all the data center loads. According to the time period type and the photovoltaic power generation power use condition, the load power supply mode of the data center is adjusted, economic preferential maximization control is achieved for users, stable operation of the load of the data center is guaranteed, and meanwhile electric charge of the whole data center is saved to the maximum extent.

Description

Technical Field

[0001] The present invention relates to a microgrid control system and method based on multi-source input of a data center, belonging to the technical field of microgrids. Background Art

[0002] Microgrid, also known as microgrid, refers to a small power generation and distribution system composed of distributed power sources, energy storage devices, energy conversion devices, loads, monitoring and protection devices, etc. The purpose of the microgrid is to achieve flexible and efficient application of distributed power sources and solve the problem of grid connection of a large number of distributed power sources in various forms. The development and extension of microgrids can fully promote the large-scale access of distributed power sources and renewable energy, realize highly reliable supply of various energy forms to loads, and is an effective way to realize active distribution networks, making the transition from traditional power grids to smart grids.

[0003] Affected by environmental factors such as weather, there is uncertainty in the input and output of the photovoltaic system, energy storage charging and discharging characteristics, and cogeneration power generation system in the microgrid. Without external software control intervention, the stable operation of the data center cannot be guaranteed. Summary of the invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a microgrid control system and method based on multi-source input of a data center, which fully utilizes the multi-source input system to adjust the power supply mode of all data center loads, and achieves control that maximizes economic benefits for users under the original control logic.

[0005] To achieve the above object, the present invention is implemented by adopting the following technical solutions:

[0006] In a first aspect, the present invention provides a microgrid control method based on multi-source input of a data center, which is executed by a microgrid control system and includes:

[0007] Receive time input;

[0008] Determine the current time period type based on time input;

[0009] Based on the current time period type, determine whether the photovoltaic system power generation is greater than the total data center load power;

[0010] In response to the photovoltaic system generating power being greater than the total data center load power, the excess power of the photovoltaic system is returned to the utility grid;

[0011] In response to the photovoltaic system generating power being not greater than the total data center load power, the multi-source input system is adjusted to supply power to the total data center load.

[0012] Furthermore, the multi-source input system includes a photovoltaic system, an energy storage system, a UPS uninterruptible power supply, a diesel generation system, city power, charging piles and a combined heat and power system, and the total data center load includes a refrigeration system, a cold storage system, a data center power load and an adjustable load.

[0013] Furthermore, the current time period type includes a peak time period, a flat time period, and a valley time period.

[0014] Furthermore, when the current time period type is a peak time period, after the microgrid control system starts the cold storage system to release cold, it determines whether the power generation of the photovoltaic system is greater than the power of all data center loads. In response to the fact that the power generation of the photovoltaic system is greater than the power of all data center loads, the excess power of the photovoltaic system is returned to the city power; in response to the fact that the power generation of the photovoltaic system is not greater than the power of all data center loads, the photovoltaic system, energy storage system, charging piles, combined heat and power supply and city power are controlled and adjusted to supply power to all data center loads.

[0015] Furthermore, when the current time period type is a peak time period, after the microgrid control system starts the cold storage system to release cold, it determines whether the power generation of the photovoltaic system is greater than the total data center load power. In response to the photovoltaic system power generation being greater than the total data center load power, the excess power of the photovoltaic system is returned to the city power; in response to the photovoltaic system power generation being not greater than the total data center load power, the photovoltaic system, energy storage system, combined heat and power supply and city power are controlled and adjusted to supply power to all data center loads.

[0016] Furthermore, when the current time period type is a flat time period, it is determined whether the power generated by the photovoltaic system is greater than the total data center load power. In response to the power generated by the photovoltaic system being greater than the total data center load power, the excess power of the photovoltaic system is returned to the city power supply; in response to the power generated by the photovoltaic system being not greater than the total data center load power, the maximum md value tracking system is started, and after initializing the energy storage system charging and discharging power and the charging and discharging power of the charging pile to 0, it is determined whether the latest collected md value is less than the current maximum md value of the month and the energy storage charging and discharging power and the charging and discharging power of the charging pile are both 0:

[0017] In response to the current total circuit md value being less than the maximum md value of the month and the energy storage charging and discharging power and the charging and discharging power of the charging pile being both 0, the photovoltaic system, the combined heat and power supply and the city power supply are controlled to supply power to all data center loads, the energy storage system and the charging piles, and it is determined whether the state of charge of the energy storage and the charging piles is less than the maximum state of charge of the energy storage and the charging piles. In response to the state of charge being not less than the maximum state of charge, the energy storage and the charging piles are turned off for charging. In response to the state of charge being less than the maximum state of charge, the photovoltaic, combined heat and power supply and city power supply systems are controlled to jointly supply power to the energy storage system, the charging piles, the refrigeration system, the power load of the data center and the adjustable load, and the power of the charging piles and the energy storage system is increased by 2% of the maximum required power, and it is re-determined whether the latest collected md value is less than the current maximum md of the month;

[0018] In response to the current total circuit md value being not less than the maximum md value of the month or the energy storage charging and discharging power and the charging and discharging power of the charging pile being not both 0, the energy storage and charging pile charging are turned off.

[0019] Furthermore, the current time period type is a valley time period, and it is determined whether the power generated by the photovoltaic system is greater than the power of all data center loads. In response to the power generated by the photovoltaic system being greater than the power of all data center loads, the excess power of the photovoltaic system is returned to the city power supply; in response to the power generated by the photovoltaic system being not greater than the power of all data center loads, the maximum md value tracking system is started, the cold storage system is started to release cold, and the photovoltaic system, city power, combined heat and power, charging piles and energy storage system are controlled to jointly supply power, and it is determined whether the md value of the current total circuit is greater than the maximum md value of the month. In response to the md value of the current total circuit being not greater than the maximum md value of the month, the joint power supply is continued, and in response to the md value of the current total circuit being greater than the maximum md value of the month, the energy storage and charging piles are turned off for discharge, and the photovoltaic, city power and combined heat and power supply are switched to supply power to the energy storage system, charging piles and all loads of the data center, and the combined heat and power supply process is adjusted and reduced until it is shut down.

[0020] In a second aspect, the present invention provides a microgrid control system based on multi-source input of a data center, comprising:

[0021] Data receiving module: receiving time input;

[0022] Time judgment module: judge the current time period type based on time input;

[0023] Power judgment module: Based on the current time period type, it determines whether the photovoltaic system power generation power is greater than the total data center load power;

[0024] Surplus power grid-connected module: When the power generated by the photovoltaic system is greater than the total data center load power, the excess power of the photovoltaic system is returned to the mains;

[0025] Power supply regulation module: In response to the photovoltaic system generating power being no greater than the total data center load power, the multi-source input system is regulated to supply power to the total data center load.

[0026] In a third aspect, the present invention provides a microgrid control device based on multi-source input of a data center, including a processor and a storage medium;

[0027] The storage medium is used to store instructions;

[0028] The processor is used to operate according to the instructions to execute the steps of any of the methods described above.

[0029] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of any of the above methods when executed by a processor.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] 1. In the context of multi-source input in the data center, the present invention makes full use of fixed assets such as photovoltaic systems, and maximizes economic benefits for users under the original control logic as much as possible, ensuring stable operation of the data center load while saving the electricity cost of the entire data center to the maximum extent. The entire process does not need to rely on external software control, and is responsive and stable;

[0032] 2. The present invention combines photovoltaic systems, energy storage systems, UPS uninterruptible power supplies, diesel generation systems, campus charging piles, combined heat and power systems, data center loads and control systems and connects the controllable interface to the large power grid. Under the original large operating logic, the photovoltaic system, energy storage system, and combined heat and power system are modeled, a Markov decision process is constructed, data is collected and trained on the operating logic, and a microgrid control system that can be based on multi-source inputs from the data center is constructed. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0034] Figure 1 A multi-source input microgrid system architecture of a microgrid control method based on multi-source input of a data center provided in Embodiment 1 of the present invention;

[0035] Figure 2 A diagram of the economic optimal control logic architecture of a microgrid system with multi-source input, according to a microgrid control method with multi-source input based on a data center provided in Embodiment 1 of the present invention. DETAILED DESCRIPTION

[0036] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present invention can be combined with each other without conflict.

[0037] The following detailed description is an exemplary description, which is intended to provide further detailed description of the present invention. Unless otherwise specified, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art to which the present invention belongs. The terms used in the present invention are only for describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present invention.

[0038] Embodiment 1:

[0039] See also Figure 1 This embodiment proposes a microgrid control method based on multi-source input of a data center, which is executed by a microgrid control system to control the photovoltaic system, energy storage system, UPS uninterruptible power supply, diesel generation system, city power, charging pile, combined heat and power system, bus, refrigeration system, data center power load, adjustable load and cold storage system (ice making system) connected to the bus in the microgrid, wherein the photovoltaic system power generation power is Ps, the energy storage system charging and discharging power is Pe, the charging and discharging power of the charging pile is Pc, the combined heat and power charging and discharging power is Pr, the city power charging and discharging power is Pt and the total data center load power is Pa (including the refrigeration system power Pz, the data center power load power Pf and the adjustable load power Pk). This system is used in a data center with a two-part billing system and a basic electricity fee that adopts maximum demand billing. The economic optimal control logic architecture of the microgrid control system under multi-source input is as follows: Figure 2 As shown:

[0040] First, the control system receives time input, obtains the status of all external systems, and configures peak, flat, or valley time periods, and determines whether the current time status is a peak, flat, or valley time period based on the time input.

[0041] 1. If the current time is determined to be a peak time period, the control system starts the cold storage system to release cold, and then determines whether Ps is greater than Pz+Pf+Pk. If Ps>Pz+Pf+Pk, the excess power of the photovoltaic system is returned to the mains to form surplus power for grid connection; if Ps≤Pz+Pf+Pk, then control and adjust Ps+Pe+Pc+Pr+Pt=Pz+Pf+Pk (at this time, the voltage order is photovoltaic>cogeneration>energy storage>charging pile>mains);

[0042] 2. If the current time is determined to be a peak time period, the control system starts the cold storage system to release cold, and then determines whether Ps is greater than Pz+Pf+Pk. If Ps>Pz+Pf+Pk, the excess power of the photovoltaic system is returned to the mains to form surplus power for grid connection; if Ps≤Pz+Pf+Pk, then control and adjust Ps+Pe+Pr+Pt=Pz+Pf+Pk (at this time, the voltage order is photovoltaic>cogeneration>energy storage>mains);

[0043] 3. If the current time is determined to be a flat time period, the control system determines whether Ps is greater than Pz+Pf+Pk. If Ps>Pz+Pf+Pk, the excess power of the photovoltaic system is returned to the mains to form surplus power for grid connection. If Ps≤Pz+Pf+Pk, the maximum md value tracking system is started, and after initializing the energy storage system charging and discharging power and the charging and discharging power of the charging pile to 0 (i.e., Penew=0, Pcnew=0), it is determined whether the latest collected md value is less than the current maximum md value of the month and the energy storage charging and discharging power and the charging and discharging power of the charging pile are both 0:

[0044] If the current md value of the total circuit is less than the maximum md value of the month and the energy storage charging and discharging power and the charging and discharging power of the charging pile are both 0, it will cause an increase in the basic electricity fee. Then, after controlling and adjusting Ps+Pr+Pt-Pz-Pf-Pk-(Penew+Pcnew)=0, it is determined whether the energy storage and charging pile state of charge (SOC) is less than the maximum state of charge of the energy storage and charging pile. If the state of charge is not less than the maximum state of charge, the energy storage and charging pile charging are turned off. If the state of charge is less than the maximum state of charge, the photovoltaic, combined heat and power supply and mains power system are controlled to jointly supply power to the energy storage system, charging pile, refrigeration system, data center power load and adjustable load (Ps+Pr+Pt=Pe+Pc+Pz+Pf+Pk), and the power of the charging pile and energy storage system is increased by 2% of the maximum required power, and it is re-determined whether the latest collected md value is less than the current maximum md of the month. It should be noted that the photovoltaic and combined heat and power generation system and the mains discharge power discharge the data center refrigeration system, data center power load, adjustable load power, and charging pile energy storage system. At this time, the received power of the energy storage and charging pile is 0. The maximum required power of the charging pile and energy storage system is increased by 2% in each subsequent cycle to constrain the discharge power of the energy storage and charging pile to prevent the one-time discharge power from being too large, thereby increasing the maximum demand of the mains md, and causing an increase in the basic electricity fee of the user.

[0045] If the current md value of the total circuit is not less than the maximum md value of the month, or the energy storage charging and discharging power and the charging and discharging power of the charging pile are not both 0, then the energy storage and charging pile charging will be turned off.

[0046] 4. If the current time is determined to be a valley time period, the control system determines whether Ps is greater than Pz+Pf+Pk. If Ps>Pz+Pf+Pk, the excess power of the photovoltaic system is returned to the mains to form surplus power for access to the grid. If Ps≤Pz+Pf+Pk, the maximum md value tracking system is started, the cold storage system is started to release cold, and the photovoltaic system, mains, combined heat and power, charging piles and energy storage system are controlled to jointly supply power (the duration can be set) to eliminate the impact of the maximum demand value caused by the opening of the cold storage system. At this time, the power supply priority is photovoltaic> combined heat and power> energy storage system> charging piles> mains. It is determined whether the md value of the current total circuit is greater than the maximum md value of the month. If the md value of the current total circuit is not greater than the maximum md value of the month, the joint power supply continues. If the md value of the current total circuit is greater than the maximum md value of the month, the energy storage and charging piles are turned off for discharge, and the photovoltaic, mains and combined heat and power are switched to supply power to the energy storage system, charging piles and all loads in the data center. The combined heat and power supply process is adjusted and reduced until it is turned off. Here, if the increase in md caused by the multi-source discharge system causes the largest increase in md, the charging operation of the energy storage and charging pile will be immediately shut down.

[0047] It should be noted that the md (Maximum Demand) value refers to the average maximum power value measured in the demand cycle within the specified time interval (the md value is also called the maximum demand value). The power bureau measures the maximum power value every 15 minutes to calculate the basic electricity fee. The two-part electricity fee consists of the basic electricity fee and the kilowatt-hour electricity fee. The total electricity fee = basic electricity fee + kilowatt-hour electricity fee. The basic electricity fee (yuan) = maximum demand (kilowatt) × basic electricity price (yuan / kilowatt·month), and the kilowatt-hour electricity fee (yuan) = monthly electricity consumption (kilowatt-hour) × electricity price (yuan / kilowatt-hour).

[0048] Due to the uncertainty of photovoltaic systems, energy storage charging and discharging characteristics, and combined heat and power generation system input and output, this technical solution constrains the input and output characteristics of each energy input port, and builds a Markov decision model to predict the charging and discharging characteristics of the input and output of the multi-energy source combination mode, providing stability support for the switching and scheduling of the power grid. The details are as follows:

[0049] Photovoltaic power generation uses the heat from the sun to change the charge state of semiconductors based on the photovoltaic effect, generating direct current to convert light energy into electrical energy. Photovoltaic power generation has the characteristics of simple structure and wide application range, and can be installed in plains, deserts, building roofs and other locations. The output power of photovoltaic power generation depends on the intensity of light radiation and ambient temperature. When solar photovoltaic power generation works at the maximum power point, the simplified mathematical model of the change of solar photovoltaic output power with light intensity and temperature can be expressed as:

[0050] P pv =XSI(1-0.005(T-25))

[0051] In the formula, p pv is the output power of photovoltaic power generation (kW), X is the conversion efficiency of the solar cell array (%), S is the array area (m2), I is the solar radiation intensity (kW / m2), and T is the ambient temperature (℃).

[0052] According to the above analysis and modeling of wind power and photovoltaics, renewable energy relies on natural resources to generate electricity, and its power output is affected by the environment. When conducting microgrid energy management research, it is necessary to collect environmental information for simulation.

[0053] Given that renewable energy sources such as wind power and photovoltaic power have strong uncertainty, it is easy to cause energy supply interruptions during periods of natural resource scarcity and wind and solar power abandonment during periods of abundant natural resources. Therefore, microgrids need to be equipped with energy storage devices to charge and store energy when renewable energy output is surplus, so as to realize the consumption of renewable energy. When renewable energy output is poor, the energy storage device discharges and supplies energy to meet the power load demand.

[0054] At present, the types of energy storage technologies are mainly divided into physical energy storage, electromagnetic energy storage and electrochemical energy storage. Physical energy storage is easily constrained by the geographical environment and needs to be adapted according to the environment in which the distributed power source is located. Electromagnetic energy storage requires the application of superconducting electromagnetic technology at extremely low temperatures, and its cost is relatively high. Electrochemical energy storage is widely recognized by the market because of its advantages of rapid charging and discharging, relatively low price and easy installation. Electrochemical energy storage is commonly based on batteries such as lithium-ion batteries and lead-acid batteries. Its industrialization is now relatively mature, and several MW-level battery energy storage stations have been established at home and abroad. Based on the advantages and characteristics of electrochemical energy storage, the energy storage device in this article takes batteries as the research basis, and its model is established as follows:

[0055]

[0056]

[0057] In the formula, are the charge and discharge states of the battery at time t, expressed as integer variables with a value range of [0, 1]; are the charging power and discharging power of the battery at time t (kW), are the maximum charging power and the maximum discharging power (kW), are the minimum discharge power and the minimum discharge power (kW), respectively, and X is the charge and discharge power of the battery at time t; is the state of charge of the battery at time t (%), are the maximum and minimum limits of the battery’s state of charge, respectively. E is the battery capacity (kWh); Xch , X disch are the charging and discharging efficiency of the battery, P t E is the discharge and charge power difference of the battery at time t.

[0058] As a controllable unit, energy storage devices not only need to consider the constraints of power output, but also have time constraints due to the influence of the charging and discharging power at the previous moment. In optimal scheduling, energy storage needs to choose the appropriate charging and discharging time according to the electricity price, load and surplus and shortage of renewable energy to achieve the optimization goals of economic operation and peak shaving.

[0059] Combined Heat and Power (CHP) in data centers is an energy-efficient technology that uses waste heat generated by data centers for heating or other thermal energy needs while providing electricity. It can control the output AC power by the input amount of waste heat. Combined Heat and Power (CHP) in data centers is an energy-efficient technology that uses waste heat generated by data centers for heating or other thermal energy needs while providing electricity. After successful startup, combined heat and power can output stable electric power and will not cause power shock when connected to the grid. It is a stable and controllable distributed power source. This paper uses the constant efficiency model as the mathematical model of combined heat and power to facilitate the calculation of fuel costs and economic analysis:

[0060] P out =R r H ng X mt

[0061]

[0062] Where P out is the output active power (kW), is the maximum output active power (kW), R r is the gas consumption (Nm3), X mt is the power generation efficiency of the generator set, H ng is the calorific value of natural gas (kWh / Nm3).

[0063] Deep reinforcement learning consists of an agent, an environment, rewards, and actions. The agent will continuously explore in an unknown environment and act on the environment. The environment will then give rewards to the agent, and the agent will then update its action strategy based on the rewards. With continuous interaction with the environment and reward feedback updates, the agent will eventually learn the action strategy with the maximum cumulative reward. The deep reinforcement learning framework uses a 4-tuple<S,A,P,R> And strategy π constructs a Markov decision process to express it:

[0064] State space S = {s0, s1, s2, s3, ... sT}: It is composed of the information of the current environment, which refers to the information obtained by the agent from the environment. The state of the environment in which the agent is in time period t is st, (t = 0, 1, 2, ... T).

[0065] Action space A = {a0, a1, a2, a3...aT}: describes the action representation of the agent. The agent makes choices in the action space based on the current state. The action performed by the agent in time period t is at.

[0066] State transition probability p=p[St+1=s'|St=s,At=a]: is a conditional probability, which refers to the probability that the environment enters the next state s' from the current state s after accepting action a.

[0067] Reward function R: r(s,a) represents the immediate benefit of the environment being in a certain state or the agent taking a specific action. After the agent takes action a according to state s, the environment feeds back the reward value to the agent. The reward value r(s,a) is calculated according to the reward function R. The reward function describes the current task and the desired goal, and its size shows the quality of action a in the current state s.

[0068] Strategy π: refers to the function that the agent uses to decide the next action a based on the current state s. It can be described by the probability of taking the possible action a in state s π(a|s)=Pπ(At=a|St=s).

[0069] Based on the above components, the Markov decision process can be described as an agent that performs action at according to state st under strategy π, and transfers to the next state st+1 with probability Pπ(At=a|St=s), while receiving feedback r(st,at) from the environment. The purpose of solving the Markov decision process is to obtain the optimal strategy π* to obtain the maximum cumulative return:

[0070]

[0071] Embodiment 2:

[0072] A microgrid control system based on multi-source input of a data center can implement a microgrid control method based on multi-source input of a data center described in Embodiment 1, including:

[0073] Data receiving module: receiving time input;

[0074] Time judgment module: judge the current time period type based on time input;

[0075] Power judgment module: Based on the current time period type, it determines whether the power generated by the photovoltaic system is greater than the total data center load power;

[0076] Surplus power grid-connected module: When the power generated by the photovoltaic system is greater than the total data center load power, the excess power of the photovoltaic system is returned to the mains;

[0077] Power supply regulation module: In response to the photovoltaic system generating power being no greater than the total data center load power, the multi-source input system is regulated to supply power to the total data center load.

[0078] Embodiment three:

[0079] The embodiment of the present invention further provides a microgrid control device based on multi-source input of a data center, which can implement a microgrid control method based on multi-source input of a data center described in the first embodiment, including a processor and a storage medium;

[0080] The storage medium is used to store instructions;

[0081] The processor is used to operate according to the instructions to perform the steps of the following method:

[0082] Receive time input;

[0083] Determine the current time period type based on time input;

[0084] Based on the current time period type, determine whether the photovoltaic system power generation is greater than the total data center load power;

[0085] In response to the photovoltaic system generating power being greater than the total data center load power, the excess power of the photovoltaic system is returned to the utility grid;

[0086] In response to the photovoltaic system generating power being not greater than the total data center load power, the multi-source input system is adjusted to supply power to the total data center load.

[0087] Embodiment 4:

[0088] The embodiment of the present invention further provides a computer-readable storage medium, which can implement the microgrid control method based on multi-source input of a data center described in the first embodiment, and a computer program is stored thereon, and when the program is executed by a processor, the steps of the following method are implemented:

[0089] Receive time input;

[0090] Determine the current time period type based on time input;

[0091] Based on the current time period type, determine whether the photovoltaic system power generation is greater than the total data center load power;

[0092] In response to the photovoltaic system generating power being greater than the total data center load power, the excess power of the photovoltaic system is returned to the utility grid;

[0093] In response to the photovoltaic system generating power being not greater than the total data center load power, the multi-source input system is adjusted to supply power to the total data center load.

[0094] It is known from common technical knowledge that the present invention can be implemented by other embodiments that do not deviate from its spirit or essential features. Therefore, the above disclosed embodiments are only illustrative in all respects and are not exclusive. All changes within the scope of the present invention or within the scope equivalent to the present invention are included in the present invention.

[0095] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0096] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the process in the flowchart. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0097] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0098] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A microgrid control method based on multi-source input of a data center, characterized in that: Executed by the microgrid control system, including: Receive time input; Determine the current time period type based on time input; Based on the current time period type, determine whether the photovoltaic system power generation is greater than the total data center load power; In response to the photovoltaic system generating power being greater than the total data center load power, the excess power of the photovoltaic system is returned to the utility grid; In response to the photovoltaic system generating power being not greater than the total data center load power, the multi-source input system is adjusted to supply power to the total data center load.

2. The microgrid control method based on multi-source input of data center according to claim 1 is characterized in that: The multi-source input system includes a photovoltaic system, an energy storage system, a UPS uninterruptible power supply, a diesel generation system, city power, charging piles and a combined heat and power system. The total data center load includes a refrigeration system, a cold storage system, a data center power load and an adjustable load.

3. The microgrid control method based on multi-source input of data center according to claim 2 is characterized in that: The current time period types include a peak time period, a peak time period, a flat time period and a valley time period.

4. The microgrid control method based on multi-source input of data center according to claim 3 is characterized in that: When the current time period type is a peak time period, after the microgrid control system starts the cold storage system to release cold, it determines whether the power generation of the photovoltaic system is greater than the power of all data center loads. In response to the power generation of the photovoltaic system being greater than the power of all data center loads, the excess power of the photovoltaic system is returned to the city power; in response to the power generation of the photovoltaic system being not greater than the power of all data center loads, the photovoltaic system, energy storage system, charging piles, combined heat and power supply and city power are controlled and adjusted to supply power to all data center loads.

5. The microgrid control method based on multi-source input of data center according to claim 3 is characterized in that: When the current time period type is a peak time period, after the microgrid control system starts the cold storage system to release cold, it determines whether the power generation of the photovoltaic system is greater than the total data center load power. In response to the photovoltaic system power generation being greater than the total data center load power, the excess power of the photovoltaic system is returned to the city power; in response to the photovoltaic system power generation being not greater than the total data center load power, the photovoltaic system, energy storage system, combined heat and power supply and city power are controlled and adjusted to supply power to all data center loads.

6. The microgrid control method based on multi-source input of data center according to claim 3 is characterized in that: When the current time period type is a flat time period, it is determined whether the power generation of the photovoltaic system is greater than the total data center load power. In response to the power generation of the photovoltaic system being greater than the total data center load power, the excess power of the photovoltaic system is returned to the city power supply; in response to the power generation of the photovoltaic system being not greater than the total data center load power, the maximum md value tracking system is started, and after initializing the energy storage system charging and discharging power and the charging and discharging power of the charging pile to 0, it is determined whether the latest collected md value is less than the current maximum md value of the month and the energy storage charging and discharging power and the charging and discharging power of the charging pile are both 0: In response to the current total circuit md value being less than the maximum md value of the month and the energy storage charging and discharging power and the charging and discharging power of the charging pile being both 0, the photovoltaic system, the combined heat and power supply and the city power supply are controlled to supply power to all data center loads, the energy storage system and the charging piles, and it is determined whether the state of charge of the energy storage and the charging piles is less than the maximum state of charge of the energy storage and the charging piles. In response to the state of charge being not less than the maximum state of charge, the energy storage and the charging piles are turned off for charging. In response to the state of charge being less than the maximum state of charge, the photovoltaic, combined heat and power supply and city power supply systems are controlled to jointly supply power to the energy storage system, the charging piles, the refrigeration system, the power load of the data center and the adjustable load, and the power of the charging piles and the energy storage system is increased by 2% of the maximum required power, and it is re-determined whether the latest collected md value is less than the current maximum md of the month; In response to the current total circuit md value being not less than the maximum md value of the month or the energy storage charging and discharging power and the charging and discharging power of the charging pile being not both 0, the energy storage and charging pile charging are turned off.

7. The microgrid control method based on multi-source input of data center according to claim 3 is characterized in that: The current time period type is a valley time period, and it is determined whether the power generated by the photovoltaic system is greater than the power of all data center loads. In response to the power generated by the photovoltaic system being greater than the power of all data center loads, the excess power of the photovoltaic system is returned to the city power supply; in response to the power generated by the photovoltaic system being not greater than the power of all data center loads, the maximum md value tracking system is started, the cold storage system is started to release cold, and the photovoltaic system, city power, combined heat and power, charging piles and energy storage system are controlled to jointly supply power, and it is determined whether the md value of the current total circuit is greater than the maximum md value of the month. In response to the md value of the current total circuit being not greater than the maximum md value of the month, the joint power supply is continued, and in response to the md value of the current total circuit being greater than the maximum md value of the month, the energy storage and charging piles are turned off for discharge, and the photovoltaic, city power and combined heat and power supply are switched to supply power to the energy storage system, charging piles and all loads of the data center, and the combined heat and power supply process is adjusted and reduced until it is turned off.

8. A microgrid control system based on multi-source input from a data center, characterized in that: include: Data receiving module: receiving time input; Time judgment module: judge the current time period type based on time input; Power judgment module: Based on the current time period type, it determines whether the power generated by the photovoltaic system is greater than the total data center load power; Surplus power grid-connected module: When the power generated by the photovoltaic system is greater than the total data center load power, the excess power of the photovoltaic system is returned to the mains; Power supply regulation module: In response to the photovoltaic system generating power being no greater than the total data center load power, the multi-source input system is regulated to supply power to the total data center load.

9. A microgrid control device based on multi-source input of a data center, characterized in that: including processor and storage medium; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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