CN116128193A - A park micro-grid scheduling method and scheduling system based on blockchain technology - Google Patents

Abstract

The invention discloses a park micro-grid dispatching method and a dispatching system based on a block chain technology; the method comprises the steps of constructing a blockchain network, and taking each unit of a park micro-grid as each node of the blockchain network; acquiring an information group, integrating all information in the information group through an intelligent contract to acquire an integrated information set, and storing the integrated information set into a blockchain network through the intelligent contract; taking the minimum total cost of operation of the park micro-grid as a target, constructing constraint conditions at the same time, and establishing an economic dispatch model of the park micro-grid; and then optimizing the integrated information set by using an economic dispatching model to obtain an optimized dispatching scheme, and issuing the optimized dispatching scheme to each node of the block chain network. According to the method, the transparency and the accuracy of the data are improved, and the scheduling data are stored in the block chain, so that the safety of the data is ensured, the scheduling decision time is shortened, and the timeliness is improved.

Description

A park microgrid dispatching method and dispatching system based on blockchain technology

Technical Field

The present invention relates to the technical field of park microgrid scheduling, and further to a park microgrid scheduling method and scheduling system based on blockchain technology.

Background Art

In recent years, my country's electrification level has been continuously improving, and the demand for electricity has also been growing, while the problems of fossil energy depletion, energy crisis and environmental pollution have become increasingly serious. In order to alleviate the contradiction between the growing demand for electricity and the gradual depletion of traditional energy, renewable energy technology has developed rapidly, but renewable energy is easily affected by natural factors and has randomness and volatility. Large-scale access will bring shocks and fluctuations to the large power grid. Park microgrids, as an effective carrier for renewable energy access, can promote the local consumption of renewable energy and reduce the adverse effects of its output volatility on the power grid.

However, traditional centralized power dispatching has problems such as low data transparency and low data security. In addition, it is difficult for each unit to obtain real-time, accurate and comprehensive data, resulting in low prediction accuracy, long decision-making time and poor timeliness of the dispatching center, which in turn causes large power losses and affects power transmission efficiency.

In view of this, this application is hereby filed.

Summary of the invention

In view of the problems of low data transparency, low security, long decision-making time and poor timeliness in power dispatching in the prior art, the present invention provides a campus microgrid dispatching method and dispatching system based on blockchain technology. The method is based on blockchain network technology, obtains information of each unit in the campus microgrid, improves data transparency and accuracy, and stores dispatching data in the blockchain, thereby ensuring data security, reducing dispatching decision time and improving timeliness.

In order to achieve the above-mentioned invention object, the present invention provides the following technical solutions:

First aspect

The present invention provides a park microgrid scheduling method based on blockchain technology, comprising the following steps:

S1: Build a blockchain network, where each node of the blockchain network represents each unit of the park microgrid, including power generation units, power consumption units, battery units, and grid interaction units;

S2: Obtain an information group, and integrate the information in the information group through a smart contract to obtain an integrated information set, which is then stored in the blockchain network by the smart contract. The information group includes power generation forecast information of the power generation unit, power consumption forecast information of the power consumption unit, parameters and status information of the battery unit, tie line constraint information of the power grid interaction unit, and power grid electricity price information;

S3: Taking the minimization of the total cost of the park microgrid operation as the goal, while building constraints, an economic dispatch model for the park microgrid is established;

S4: Use the economic dispatch model to optimize the integrated information set and obtain the optimal dispatch solution;

S5: Send the optimized scheduling plan to each node of the blockchain network.

In this scheme, based on the blockchain network, smart contracts are designed to realize information interaction. Each node in the blockchain network can obtain data and historical data in real time to improve the accuracy of prediction and the transparency of data. Based on the integrated information set, an economic dispatch model of the park microgrid is established under the constraints of cost and other conditions. The integrated information set is optimized using the economic dispatch model to obtain the optimized dispatch plan; the optimized dispatch plan is sent to each node of the blockchain network to realize the dispatch optimization of the park microgrid. The optimized dispatch plan and data information are stored in the blockchain to ensure data security. Timely acquired data can reduce the dispatch decision time and improve timeliness.

Furthermore, in step S2, after obtaining the information group, the following steps are also included: confirming the validity of each information in the information group, taking the valid information as the information to be integrated, and only after confirming the validity of the information can subsequent operations be performed to ensure the accuracy of the subsequent scheduling plan.

Furthermore, validity means that each information in the information group meets a preset range. Information outside the range is abnormal information, has no validity, and needs to be obtained again.

Furthermore, in step S3, the constraints include: power balance constraints, wind turbine operation constraints, photovoltaic unit operation constraints, micro gas turbine unit operation constraints, battery energy storage unit constraints or at least one of the interconnection line exchange power constraints. The park microgrid selects appropriate constraints based on the equipment it has.

Furthermore, the power balance constraint is the balance between load and output power, as follows:

表示风力发电的功率，

表示光伏发电的功率，

表示微型燃气轮机发电的功率，

表示购电功率，

表示购电状态，

表示切负荷功率，

表示切负荷状态，

表示储能充电功率，

表示储能充电状态，

表示购电功率，

表示购电状态，

表示储能放电状态，

表示储能放电功率，

表示t小时时段内预测的总负荷值；in,

is the power of wind power generation,

Represents the power of photovoltaic power generation,

represents the power generated by the micro gas turbine,

Indicates the purchased power,

Indicates the power purchase status.

Indicates load shedding power,

Indicates load shedding state.

Indicates the energy storage charging power,

Indicates the energy storage charging status,

Indicates the purchased power,

Indicates the power purchase status.

Indicates the energy storage discharge state,

represents the energy storage discharge power,

It represents the total load value predicted in the t-hour period;

Wind turbine operation constraints:

Among them, P _wtmax represents the upper limit of wind power output;

PV unit operation constraints:

Among them, P _pvmax represents the upper limit of photovoltaic power generation output;

Micro gas turbine unit operation constraints:

Among them, _Pmtmax and _Pmtmin represent the upper and lower limits of the micro gas turbine output; and the climbing rate will also constrain the micro gas turbine output:

Among them, P _mt,down represents the downward climbing power of the micro gas turbine, and P _mt,up represents the upward climbing power of the micro gas turbine;

Battery energy storage unit constraints:

In order to ensure periodic scheduling, the initial remaining capacity of the battery every day should be equal to the remaining capacity at 24h time:

At time t, the battery is not in the charging and discharging state at the same time:

There are power constraints when charging and discharging batteries:

Wherein, P _dis,min represents the lower limit of one-time discharge of the battery, P _dis,max represents the upper limit of one-time discharge of the battery, P _cha,min represents the lower limit of one-time charge of the battery, and P _cha,max represents the upper limit of one-time charge of the battery;

Tie line switching power constraints:

At time t, the working state constraints of the connection lines of the park microgrid are:

Constraints on power exchange between the campus microgrid and the grid:

P _buy,min represents the lower power limit of electricity purchased from the large power grid, P _buy,max represents the upper power limit of electricity purchased from the large power grid, P _sell,min represents the lower power limit of electricity sold to the large power grid, and P _sell,max represents the upper power limit of electricity sold to the large power grid.

Furthermore, the integrated information set is optimized based on the economic dispatch model, including the following steps: a linearized model is generated using mixed integer linear programming, and a large-scale solver is used to solve the linearized model, wherein the expression of the linearized model is as follows:

Furthermore, in step S5, the optimized scheduling plan is sent to each node of the blockchain network with a preset time interval T as a period, where T is a positive integer ≥ 1; within the period of time interval T, the park microgrid operates according to the scheduling plan.

Furthermore, after step S5, when each node operates according to the optimized scheduling plan, if the power generation information obtained is different from the power generation information of the optimized scheduling plan, steps S3 to S5 are repeated to obtain a new scheduling plan and re-adapt the environment to obtain the minimum park operation cost.

Second aspect

The present invention relates to a park microgrid dispatching system based on blockchain technology, comprising: a blockchain network module, wherein each node in the blockchain network module comprises each unit of the park microgrid, wherein the unit comprises a power generation unit, a power consumption unit, a battery unit and a unit interacting with a power grid; an information acquisition module, wherein the information acquisition module can obtain an information group, and integrate the information group through a smart contract module to obtain an integrated information set, wherein the smart contract module uploads the integrated information set to the blockchain network module, wherein the information group comprises power generation prediction information of the power generation unit, power consumption prediction information of the power consumption unit, the battery unit's own parameters and status information, and the tie line constraint information and power grid electricity price information of the unit interacting with a power grid; a construction module, wherein the construction module takes the minimization of the total operating cost of the park microgrid as a goal, and constructs constraint conditions at the same time, and establishes an economic dispatching model of the park microgrid; an optimization module, wherein the optimization module optimizes the integrated information set using the economic dispatching model to obtain an optimized dispatching scheme; and an allocation module, wherein the allocation module sends the optimized dispatching scheme to each node of the blockchain network module.

The third aspect

An embodiment of the present invention relates to a storage medium, which stores a computer program. When the computer program runs in an electronic device, the processor of the electronic device loads and executes any one of the above-mentioned campus microgrid scheduling methods based on blockchain technology.

Compared with the prior art, the present invention has the following advantages and beneficial effects:

The present invention relates to a park microgrid dispatching method based on blockchain technology, which comprehensively considers the characteristics of each unit of the park microgrid, constructs a blockchain network, improves the accuracy and transparency of data, and uses smart contracts to realize information interaction. Compared with the traditional dispatching mode, each node in the park microgrid can obtain historical data and dispatching plans through smart contracts, which improves the transparency of data information and the accuracy of predicted data; under the economic dispatching model of the park microgrid provided by the present invention, the optimal dispatching plan can be obtained, and the optimized dispatching plan and data information are stored in the blockchain to ensure data security. The timely acquired data can reduce the dispatching decision time and improve timeliness; and the power generation unit in the park microgrid outputs at maximum power, and the battery adjusts the output according to different electricity price periods, avoiding the purchase of electricity at peak electricity prices, reducing the operating cost of the park microgrid, and improving the economic effect and output flexibility.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

FIG1 is a basic flow chart of a park microgrid scheduling method based on blockchain technology provided by an embodiment of the present invention;

FIG2 is a detailed flow chart of a park microgrid scheduling method based on blockchain technology provided by an embodiment of the present invention;

FIG3 is a flowchart of a blockchain network provided by an embodiment of the present invention;

FIG4 is an example diagram of real-time electricity prices of a large power grid provided by an embodiment of the present invention;

FIG5 is a schematic diagram of a day-ahead forecast of wind power and load provided by an embodiment of the present invention;

FIG6 is a schematic diagram of a day-ahead dispatching scheme for a campus microgrid provided by an embodiment of the present invention;

FIG7 is a diagram showing the output ratio of each unit in a park microgrid provided by an embodiment of the present invention;

FIG8 is a comparison diagram of the output of photovoltaic units in a park microgrid provided by an embodiment of the present invention;

FIG9 is a comparison diagram of wind turbine output in a park microgrid provided by an embodiment of the present invention;

FIG10 is a diagram showing energy changes of a battery energy storage unit in a campus microgrid provided by an embodiment of the present invention.

DETAILED DESCRIPTION

The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is apparent to one of ordinary skill in the art that these specific details are not necessarily employed to practice the present invention. In other instances, well-known structures, circuits, materials, or methods are not specifically described in order to avoid obscuring the present invention.

Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "one embodiment," "an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. In addition, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any suitable combination and/or sub-combination. In addition, it will be appreciated by those of ordinary skill in the art that the figures provided herein are for illustrative purposes and that the figures are not necessarily drawn to scale. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.

Example

As the most basic database technology, blockchain technology has the characteristics of high transparency, data immutability, and high degree of decentralization. It can improve the data transparency and prediction accuracy of the campus microgrid, ensure the security of scheduling data, and is of great significance to the campus microgrid system containing multiple distributed nodes.

At present, scholars at home and abroad have conducted a lot of research on the application of blockchain technology in the energy field. Regarding the application of blockchain technology in power grid dispatching, Zhu Yongsheng and other scholars proposed a decomposed multi-objective evolutionary algorithm to deal with the two conflicting goals of fuel costs and pollution emissions under environmental economic dispatch on the basis of existing dispatching, and obtained a solution that makes the two objective functions optimal at the same time, and used this solution to optimize the power environmental economic dispatching. Hu Wei and other scholars combined blockchain technology to establish a power supply and demand dispatching optimization model for the problems of large network loss and difficult energy regulation in traditional dispatching, and used a co-evolutionary algorithm to solve the model. Finally, the effectiveness of the dispatching scheme was verified by the blockchain proof of work mechanism. Foreign scholars proposed a fully distributed algorithm based on the alternating multiplier method (ADMM), the projected gradient method and the average consistency, which divides the dispatching problem into several sub-problems and solves them by the average consistency method and the projected gradient method. The results show that the algorithm can effectively solve the optimal dispatching strategy for the power generation unit, the park interconnection line and the energy storage unit in the park microgrid under any initial state. Some scholars have also established a new dispatching mode by integrating parallel intelligent technology, realizing the safe operation of complex power grids, expanding the capabilities of system operators, and obtaining the optimal dispatching strategy.

Existing research has taken into account the service life of battery energy storage units and the characteristics of electric vehicles, and mainly focuses on optimizing the dispatching strategy of the dispatching center; however, traditional centralized dispatching has problems such as low data transparency and low data security, and the dispatching center takes a long time to make decisions and has poor timeliness. Therefore, this embodiment provides a campus microgrid dispatching method based on blockchain technology, which enables each unit in the campus microgrid to obtain comprehensive and accurate data, improves data transparency and accuracy, and stores the dispatching data in the blockchain to ensure data security.

As shown in FIG1 , an embodiment of the present invention provides a campus microgrid scheduling method based on blockchain technology, comprising the following steps:

S1: Build a blockchain network, where each node of the blockchain network represents each unit of the park microgrid, including power generation units, power consumption units, battery units, and grid interaction units;

S2: Obtain an information group, and integrate the information in the information group through a smart contract to obtain an integrated information set, which is then stored in the blockchain network by the smart contract. The information group includes power generation forecast information of the power generation unit, power consumption forecast information of the power consumption unit, parameters and status information of the battery unit, tie line constraint information of the power grid interaction unit, and power grid electricity price information;

S3: Taking the minimization of the total cost of the park microgrid operation as the goal, while building constraints, an economic dispatch model for the park microgrid is established;

S4: Use the economic dispatch model to optimize the integrated information set and obtain the optimal dispatch solution;

S5: Send the optimized scheduling plan to each node of the blockchain network.

In step S1, each unit of the park microgrid jointly forms a node set of the blockchain network. When joining the blockchain network, these units need to submit their own relevant information to the blockchain network, such as their own ID, energy type, account information, electricity demand, installed capacity, maximum power generation quota, geographical location, etc. The function of this information is to authenticate the blockchain network, represent the identity and participate in the dispatch of the park microgrid. This information and data is the core foundation of the power dispatch of the park microgrid; in the blockchain network, if a new block needs to be generated to save data information within a certain time period, it needs to be broadcast to the entire network, and all nodes need to receive the information and fully verify it; if the information passes the verification and reaches a consensus in the entire network, a new block will be generated and published to the entire blockchain network, and extended to the original blockchain, as shown in Figure 2.

Each node in the blockchain network stores the complete data of the blockchain, and each block stores all the information data in the blockchain network within a certain period of time: the power generation unit that outputs power, the size of the output, the location of the power unit that receives the power, the size of the load, the location information, and the price of power from the large power grid. The information format of each node in the blockchain network is as follows:

The information format of the power generation unit is:

GU=(ID _GU ,P _GU ,C _GU ,T _GU ,U _GU ,δ _GU ,L _GU );

Where GU is the data information of the power generation unit, ID _GU is the identity obtained after verification when the power generation unit joins the blockchain network, P _GU represents the power generation quota of the power generation unit, C _GU represents the cost information of the power generation unit, T _GU represents the energy type of the power generation unit, U _GU represents the current start and stop status of the power generation unit, δ _GU represents the climbing rate of the power generation unit, and L _GU represents the location information of the power generation unit.

The information format of the power consumption unit is:

CU＝(ID _CU ,P _CU ,L _CU );

Among them, CU is the data information of the power user unit, ID _CU is the identity obtained after verification when the power user unit joins the blockchain network, P _CU represents the demand of the power user unit, and L _GU represents the location information of the power user unit.

The information format of the battery unit is:

B=(ID _B ,P _B ,C _B ,U _B ,δ _B );

Where B is the information of the battery unit, ID _B is the identity obtained after verification when the battery joins the blockchain network, P _B represents the power generation quota of the battery energy storage system, _CB represents the cost information of the battery energy storage system, U _B represents the current charge and discharge status of the battery energy storage system, and δ _B represents the maximum charge and discharge quota of the battery energy storage system.

The information format of the unit interacting with the power grid is:

LLX＝(P _LLX ,C _LLX );

Among them, P _LLX represents the ability to exchange power with the large power grid, and C _LLX represents the real-time electricity price of the large power grid.

By applying blockchain technology in the dispatching of park microgrids, the data and dispatching plans of the park microgrid can be stored safely and effectively in the blockchain network. By designing smart contracts with the function of realizing information interaction, the upload and download of data information can be realized, and the information of each node can be collected and uploaded to the blockchain network. When the optimized dispatching plan is generated, it is sent to each node of the network through smart contracts. The blockchain network becomes the data storage center and information interaction center of the park microgrid.

In step S2, the smart meter is used to monitor the nodes participating in the blockchain network in real time and collect information groups, which are then uploaded to the blockchain network. The energy management system connected to the blockchain network confirms the validity of the information in the information group and confirms that the information meets the preset range. Information outside the range is abnormal information and has no validity and needs to be re-acquired. As shown in Figure 2, information within the preset range is valid information, and the valid information is used as information to be integrated to obtain an integrated information set, which is stored in the blockchain network by the smart contract.

First, each power-consuming unit conducts load forecasting autonomously and submits forecasting information to the blockchain network; then the generator set provides forecasting information. The generator sets in this embodiment include wind turbines, photovoltaic generators and micro gas turbine generators. Wind turbines and photovoltaic generators conduct output forecasting based on weather and historical data. The smart contract records all information until all information is submitted. The battery unit submits information, and the network obtains its main performance parameters. The smart contract records information until all information is submitted. The unit interacting with the power grid provides information, and the validity of the information provided needs to be confirmed. After obtaining a complete set of integrated information, proceed to the next step.

In step S3, there are multiple distributed energy sources in the park microgrid, including uncontrollable power generation units and controllable power generation units mainly based on photovoltaic and wind power: micro gas turbine power generation units, in addition to power generation units, energy storage equipment must be set up; on the premise of meeting the load demand of the park microgrid, energy can also be sold or purchased from the external network. The day-ahead scheduling of the park microgrid sets a cycle of 24 hours, and uses 1 hour as the scheduling time interval. It is stipulated that all data is unchanged within a one-hour interval, and the operation plan of the park microgrid for the next day is planned. The plan includes the output plan of the distributed power source, the running and stopping status, the charging and discharging status of the energy storage system, and the interaction plan with the large power grid.

光伏机组发电功率

微型燃气轮机发电功率

购电功率

售电功率

储能放电功率

储能充电功率

切负荷功率

风力发电状态

光伏机组发电

微型燃气轮机发电

储能充电状态

储能放电状态

售电状态

购电状态

切负荷状态

园区微电网中各单元的工作状态如下表所示：According to the output characteristics of each power generation unit, the constraints of climbing and unit start and stop, the one-time charging and discharging capacity of the battery energy storage unit, the capacity constraints of the external network interconnection line, and the load shedding that occurs when the demand cannot be met, the mathematical model of each distributed output unit, battery energy storage unit and interconnection line is established. The variables that need to be optimized are: wind power generation power

Photovoltaic unit power generation

Micro gas turbine power generation

Power purchase

Power sold

Energy storage discharge power

Energy storage charging power

Load shedding power

Wind power generation status

Photovoltaic power generation

Micro gas turbine power generation

Energy storage charging status

Energy storage discharge state

Power sales status

Power purchase status

Load shedding state

The working status of each unit in the park microgrid is shown in the following table:

Table 1 Working status table

Table 2 Working status table

In each hour, assuming that the power generation and power consumption of the park microgrid equipment in this time period are fixed values, the goal is to minimize the total cost of the park microgrid operation, and the objective function constructed is:

表示t小时这一时刻园区微电网向电网购电时的电价，

表示在t小时这一时刻园区微电网向电网售电的电价，C_cut表示切负荷惩罚的单位费用。Among them, C _wt represents the unit cost of wind power, C _pv represents the unit cost of photovoltaic power, and C _mt represents the unit cost of gas turbine.

It represents the electricity price when the park microgrid buys electricity from the grid at hour t,

It represents the electricity price sold by the park microgrid to the grid at the moment of t hour, and _Ccut represents the unit cost of load shedding penalty.

Renewable distributed energy uses inexhaustible resources such as wind and sunlight to generate electricity, and its power generation cost is very small; the cost of the micro gas turbine unit includes the cost of fuel consumption and the cost of starting and stopping, and the battery energy storage unit does not consider the cost caused by the reduction of life during operation. When the power generation and load within the park microgrid are unbalanced, electricity can be purchased or sold to the external network through the interconnection line, and the electricity price adopts the time-of-use electricity price of the large power grid.

Based on the integrated information set stored in the blockchain network, the constructed constraints include: power balance constraints, wind turbine operation constraints, photovoltaic unit operation constraints, micro gas turbine unit operation constraints, battery energy storage unit constraints or at least one of the interconnection line exchange power constraints. The park microgrid selects appropriate constraints based on the equipment it has. In this embodiment, the park microgrid has all the constraints.

The power balance constraint is the balance between load and output power, as follows:

表示风力发电的功率，

表示光伏发电的功率，

表示微型燃气轮机发电的功率，

表示购电功率，

表示购电状态，

表示切负荷功率，

表示切负荷状态，

表示储能充电功率，

表示储能充电状态，

表示购电功率，

表示购电状态，

表示储能放电状态，

表示储能放电功率，

表示t小时时段内预测的总负荷值；in,

is the power of wind power generation,

Represents the power of photovoltaic power generation,

represents the power generated by the micro gas turbine,

Indicates the purchased power,

Indicates the power purchase status.

Indicates load shedding power,

Indicates load shedding state.

Indicates the energy storage charging power,

Indicates the energy storage charging status,

Indicates the purchased power,

Indicates the power purchase status.

Indicates the energy storage discharge state,

represents the energy storage discharge power,

It represents the total load value predicted in the t-hour period;

Wind turbine operation constraints:

Among them, P _wtmax represents the upper limit of wind power output;

PV unit operation constraints:

Among them, P _pvmax represents the upper limit of photovoltaic power generation output;

Micro gas turbine unit operation constraints:

Among them, _Pmtmax and _Pmtmin represent the upper and lower limits of the micro gas turbine output; and the climbing rate will also constrain the micro gas turbine output:

Among them, P _mt,down represents the downward climbing power of the micro gas turbine, and P _mt,up represents the upward climbing power of the micro gas turbine;

Battery energy storage unit constraints:

In order to ensure periodic scheduling, the initial remaining capacity of the battery every day should be equal to the remaining capacity at 24h time:

At time t, the battery is not in the charging and discharging state at the same time:

There are power constraints when charging and discharging batteries:

Wherein, P _dis,min represents the lower limit of one-time discharge of the battery, P _dis,max represents the upper limit of one-time discharge of the battery, P _cha,min represents the lower limit of one-time charge of the battery, and P _cha,max represents the upper limit of one-time charge of the battery;

Tie line switching power constraints:

At time t, the working state constraints of the connection lines of the park microgrid are:

Constraints on power exchange between the campus microgrid and the grid:

P _buy,min represents the lower power limit of electricity purchased from the large power grid, P _buy,max represents the upper power limit of electricity purchased from the large power grid, P _sell,min represents the lower power limit of electricity sold to the large power grid, and P _sell,max represents the upper power limit of electricity sold to the large power grid.

In step S4,

又包含离散变量

的非线性函数优化问题，需要将园区微电网调度优化模型中的目标函数和约束条件线性化；采用混合整数线性规划生成线性化模型，并使用大规模求解优化器进行求解，其中，线性化模型的表达式如下：The optimization problem of campus microgrid dispatch can be described as a problem that includes both continuous variables

Contains discrete variables

The nonlinear function optimization problem requires linearization of the objective function and constraints in the park microgrid dispatch optimization model. The linearized model is generated by mixed integer linear programming and solved by a large-scale solver optimizer. The expression of the linearized model is as follows:

Wherein, f ^T x is the objective function, and x is the column vector that needs to be solved in the end. According to the vectors f, lb and ub, the matrices A and Aeq, and the corresponding vectors b and beq, x can be solved. The large-scale solver optimizer used in this embodiment is Gurobi, which is a large-scale solver optimizer with leading performance worldwide and can be used to solve mixed integer linear programming problems. Its performance is significantly better than that of traditional mainstream optimization tools.

Based on smart contracts and blockchain networks, nodes in the campus microgrid can obtain real-time and historical data to improve prediction accuracy and data transparency; the generated scheduling plans and data can be stored in the blockchain to better ensure data security.

In step S5, the optimized scheduling plan is sent to each node of the blockchain network with a preset time interval T as a period, where T is a positive integer ≥ 1; within the period of time interval T, the park microgrid operates according to the scheduling plan. In this embodiment, the day-ahead scheduling of the park microgrid is set with a period of 24 hours, and the scheduling time interval is 1 hour. The trigger time is set before 00:00 that night to ensure that the day-ahead scheduling plan can be generated and issued.

In addition, after step S5, when each node operates according to the optimized scheduling plan, if the power generation information obtained is different from the power generation information of the optimized scheduling plan, for example, due to the influence of the external environment, the wind turbine generator set cannot generate electricity, the photovoltaic generator set cannot generate electricity, etc., it is necessary to reallocate the plan and repeat the above steps S3 to S5. At this time, the information provided by the generator set is real-time information and forecast information. The scheduling time interval is still 1 hour. The energy management system re-acquires a new scheduling plan and can only re-issue the scheduling plan and re-adapt to the environment to obtain the minimum park operation cost.

In the method provided in this embodiment, based on the blockchain network, a smart contract is designed to realize information interaction. Each node in the blockchain network can obtain data and historical data in real time to improve the accuracy of prediction and the transparency of data. Based on the integrated information set, an economic dispatch model of the park microgrid is established under the constraints of cost and other conditions. The integrated information set is optimized using the economic dispatch model to obtain an optimized dispatch plan; the optimized dispatch plan is sent to each node of the blockchain network to realize the dispatch optimization of the park microgrid. The optimized dispatch plan and data information are stored in the blockchain to ensure data security. Timely acquired data can reduce the dispatch decision time and improve timeliness.

The method provided in this embodiment comprehensively considers the distributed nature of each unit of the park microgrid and the structural characteristics of blockchain technology as a distributed ledger, as well as the problems of data opacity and low prediction accuracy in traditional scheduling, and proposes an optimized scheduling architecture for the park microgrid based on blockchain technology; an energy blockchain network is established to make it a data storage and information exchange center for the scheduling of the park microgrid. Compared with the traditional scheduling mode, each node in the park microgrid can obtain historical data and scheduling plans through smart contracts, which improves the transparency of data information and the accuracy of predicted data; under the economic scheduling model of the park microgrid provided in this embodiment, the renewable distributed energy in the park microgrid is output at maximum power, and the controllable power generation unit and the battery adjust the output according to different electricity price periods, avoiding the purchase of electricity at peak electricity prices, reducing the operating cost of the park microgrid, and improving the economic effect and output flexibility.

The embodiment of the present invention also relates to a campus microgrid dispatching system based on blockchain technology, including: a blockchain network module, each node in the blockchain network module includes each unit of the campus microgrid, and the unit includes a power generation unit, a power consumption unit, a battery unit, and a unit interacting with the power grid; an information acquisition module, the information acquisition module can obtain an information group, and integrate the information group through a smart contract module to obtain an integrated information set, and the smart contract module uploads the integrated information set to the blockchain network module, wherein the information group includes power generation forecast information of the power generation unit, power consumption forecast information of the power consumption unit, the battery unit's own parameters and status information, and the interconnection line constraint information and power grid electricity price information of the unit interacting with the power grid; a construction module, the construction module takes the minimum total operating cost of the campus microgrid as the goal, and at the same time constructs constraints to establish an economic dispatching model for the campus microgrid; an optimization module, the optimization module uses the economic dispatching model to optimize the integrated information set to obtain an optimized dispatching plan; and an allocation module, the allocation module sends the optimized dispatching plan to each node of the blockchain network module.

The embodiment of the present invention also relates to a storage medium, in which a computer program is stored. When the computer program runs in an electronic device, the processor of the electronic device loads and executes any one of the park microgrid scheduling methods based on blockchain technology in this embodiment; the storage medium can be used to store the computer program and/or module, and the processor loads and executes any one of the park microgrid scheduling methods based on blockchain technology in this embodiment by running or executing the computer program and/or module stored in the memory, and calling the data stored in the memory. The storage medium can mainly include a storage program area and a storage data area, wherein the storage program area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.); the storage data area can store data created according to the use of a mobile phone (such as audio data, a phone book, etc.). In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Caed, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

The following content is a specific application scenario of a campus microgrid scheduling method based on blockchain technology in this embodiment. In the campus microgrid of this application scenario, there are wind turbines, photovoltaic power generation systems, micro gas turbines, battery energy storage systems, and interconnection lines with the large power grid. The maximum output forecast value of the wind turbine and photovoltaic power generation system for each hour in the next 24 hours, as well as the forecast value of the load for each hour in the next 24 hours can be obtained. This application uses the IDE-Remix platform to design smart contracts, and uses MATLAB software to write the optimization scheduling program for the campus microgrid; the performance parameters of each distributed power source and energy storage unit in the campus microgrid are shown in Table 3.

Table 3 Parameters of each unit of the park microgrid

When the park microgrid interacts with the large grid to purchase or sell electricity, the large grid's time-of-use electricity price is used, as shown in Figure 4.

Each power generation unit and load unit in the park microgrid calls the smart contract to read the historical data and current status information in the blockchain, and then conducts a comprehensive analysis based on weather information, electricity price market conditions and production capacity information. The maximum output or load value of wind turbines, photovoltaic generators and loads in each hour in the next 24 hours is analyzed, and the day-ahead forecast is obtained as shown in Figure 5.

After obtaining the output forecast value and load forecast value, the smart contract of the blockchain network will issue the day-ahead dispatch plan, as shown in Figure 6.

Combined with the real-time electricity price chart 4, it can be seen that the time period from 0:00 to 6:00 in the early morning is the valley electricity price period of the large power grid. At this time, the photovoltaic generator set has no output due to the influence of time, but discharges through wind turbines and batteries. At this time, it still cannot meet the load. Considering the economic benefits, it is necessary to purchase electricity from the large power grid. At this time, the battery can also be charged by purchasing electricity from the large power grid. The time period from 6:00 to 12:00 is the peak electricity price period of the large power grid. Combined with the load forecast chart, it can be seen that the load demand increases at this time, and the output of wind power and photovoltaic power also increases due to the influence of weather. Since the power price of the power grid is high at this time, the micro gas turbine unit in the park microgrid generates electricity instead of purchasing electricity from the large power grid. For economic benefits, if there is any excess electricity at this time, it can be sold to the large power grid. The period from 12:00 to 18:00 is the flat electricity price period. Due to the reduction of the output of the photovoltaic unit, the park microgrid mainly relies on wind power generation, photovoltaic power generation and purchasing electricity from the large power grid to provide the load demand electricity. The electricity price from 18:00 to 24:00 is the peak electricity price, the gas turbine output increases, and the photovoltaic generator set has zero output due to the lack of sunlight. At this time, wind power, purchased electricity, and gas turbines are used to provide the load demand electricity, and the excess electricity can be used to charge the battery.

As can be seen from Figure 7, the load and power supply power are always balanced during operation, maintaining the operational reliability of the park microgrid and ensuring the quality of power. In addition, renewable energy accounts for a high proportion of all outputs. As can be seen from Figures 8 and 9, both wind turbines and photovoltaic units use the maximum power as the output power. Since renewable energy does not consume fuel and has low cost, it greatly reduces the operating costs of the park microgrid and has good economic benefits.

The battery energy changes are shown in Figure 10. The battery was discharged at 6:00 to meet the load, and then remained stable. It was charged at 21:00 to keep the total battery power unchanged. There was no deep charge and discharge during this process, and the loss was small, which extended its service life.

In general, there is no load shedding in this solution, and the reliability is high. When the power grid is at peak price, the gas turbine will increase its output to reduce the operating cost of the park microgrid, avoid high electricity prices, and improve the economic benefits and output flexibility of the park microgrid.

In the case of a large number of renewable distributed energy grid-connected, the traditional one-way energy flow mode gradually changes to a two-way energy flow mode. This embodiment combines the structural characteristics of the distributed power generation and load units of the park microgrid, and the structural characteristics of the blockchain as a distributed ledger, and studies the economic dispatch model of the park microgrid based on blockchain technology. This embodiment first analyzes the similarities between blockchain technology and the park microgrid, and theoretically explains the compatibility of blockchain and park microgrid and the feasibility of applying blockchain technology to the park microgrid. In view of the existing problems of low prediction accuracy and insufficient information transparency in the park microgrid dispatch, a park microgrid dispatch model based on blockchain technology is studied, and energy storage units are added to the model. Finally, the model was built using MATLAB, and simulation experiments were carried out to verify the economy and feasibility of the park microgrid dispatch model. The application of blockchain technology in the park microgrid greatly improves the decentralization of the park microgrid and the prediction accuracy of the data. In the absence of a third-party authority, a consensus can be achieved across the entire network to ensure that the dispatch plan of the park microgrid can be automatically and strictly implemented. In addition, the dispatching plan of the park microgrid and the information of each node can be stored in the blockchain network, which improves the traceability and transparency of the data and ensures the security of the dispatching information.

Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or storage media. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

The present application is described with reference to the flowchart and/or block diagram of the method, device (system) and computer program product according to the embodiment of the present application. It should be understood that each process and/or box in the flowchart and/or block diagram, and the combination of the process and/or box in the flowchart and/or block diagram can be realized 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 produce a device for realizing the function specified in one process or multiple processes in the flowchart and/or one box or multiple boxes in the block diagram.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

A person of ordinary skill in the art can understand that all or part of the steps in realizing the above-mentioned facts and methods can be completed by instructing the relevant hardware through a program, and the program involved or the program can be stored in a computer-readable storage medium. When the program is executed, it includes the following steps: At this time, the corresponding method steps are derived, and the storage medium can be ROM/RAM, a disk, an optical disk, etc.

The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims (10)

1. The park micro-grid scheduling method based on the block chain technology is characterized by comprising the following steps of:

s1: constructing a blockchain network, wherein each node of the blockchain network represents each unit of a campus micro-grid, and each unit comprises a power generation unit, a power utilization unit, a storage battery unit and a power grid interaction unit;

s2: acquiring an information group, integrating all information in the information group through an intelligent contract to obtain an integrated information set, and storing the integrated information set into a blockchain network through the intelligent contract, wherein the information group comprises power generation prediction information of a power generation unit, power consumption prediction information of a power consumption unit, self parameters and state information of a storage battery unit, contact line constraint information of an interaction unit with a power grid and power grid price information;

S3: taking the minimum total cost of operation of the park micro-grid as a target, constructing constraint conditions at the same time, and establishing an economic dispatch model of the park micro-grid;

s4: optimizing the integrated information set by using the economic dispatch model to obtain an optimized dispatch scheme;

s5: and issuing the optimized scheduling scheme to each node of the blockchain network.

2. The method for campus microgrid scheduling based on blockchain technology of claim 1, wherein,

in step S2, the step of acquiring the information set further includes the following steps:

and confirming the validity of each information in the information group, and taking the valid information as the information to be integrated.

3. The method for campus microgrid scheduling based on the blockchain technique of claim 2, wherein,

the validity means that each information in the information group meets a preset range.

4. The method for campus microgrid scheduling based on blockchain technology of claim 1, wherein,

in step S3, the constraint condition includes: at least one of a power balance constraint, a wind turbine generator system operation constraint, a photovoltaic turbine generator system operation constraint, a micro gas turbine generator system operation constraint, a battery energy storage unit constraint, or a tie-line exchange power constraint.

5. The method for campus microgrid scheduling based on blockchain technology of claim 4, wherein,

the power balance constraint is load and output power balance, and the power balance constraint is specifically as follows:

wherein ,

representing the power of wind power generation +.>

Represents the power of photovoltaic power generation, +.>

Representing the power generated by the micro gas turbine, +.>

Representing the purchase power, < >>

Indicating the electricity purchasing state->

Representing load shedding power, < >>

Indicating load shedding status, < >>

Representing the stored charge power>

Indicating the state of charge of the stored energy>

Representing the purchase power, < >>

Indicating the electricity purchasing state->

Indicating the state of energy storage discharge->

Representing the energy storage discharge power>

Representing a predicted total load value over a t-hour period;

wind turbine generator operation constraint:

wherein ,P_wtmax Representing an upper limit of the output of the wind power generation;

photovoltaic unit operation constraint:

wherein ,P_pvmax Representing the upper output limit of photovoltaic power generation;

micro gas turbine unit operation constraints:

wherein ,P_mtmax 、P _mtmin Indicating the upper and lower limits of the micro gas turbine output; and the climbing rate also constrains the micro gas turbine output:

wherein ,P_mt,down Representing downhill power P of micro gas turbine _mt,up Representing the upward hill climbing power of the micro gas turbine;

and (3) restraining a storage battery energy storage unit:

In order to ensure periodic scheduling, the initial residual capacity of the storage battery per day should be equal to the residual capacity at 24 h:

at time t, the storage battery is not in a charging and discharging state at the same time:

the storage battery has power constraint when being charged and discharged:

wherein ,P_dis,min Indicating the lower limit of one-time discharge of the storage battery, P _dis,max Indicating the upper limit of the one-time discharge of the battery,P _cha,min indicating the disposable lower limit of charge of the battery, P _cha,max Indicating a disposable upper limit of charge of the battery;

tie-line switching power constraints:

in the time t, the working state constraint of the connection line of the campus micro-grid:

constraint of power exchange between campus microgrid and grid:

P _buy,min representing the lower power limit of purchasing electricity from a large power grid, P _buy,max Representing the upper power limit of purchasing electricity from a large power grid, P _sell,min Representing a lower power limit, P, for selling electricity to a large grid _sell,max Indicating the upper power limit for selling electricity to a large grid.

6. The method for campus microgrid scheduling based on blockchain technology according to claim 5, wherein optimizing the integrated information set based on the economic scheduling model comprises the steps of: and generating a linearization model by adopting mixed integer linear programming pairs, and solving by using a large-scale solving optimizer, wherein the expression of the linearization model is as follows:

7. The method for scheduling a micro-grid in a park based on the blockchain technology according to claim 6, wherein in step S5, the optimal scheduling scheme is issued to each node of the blockchain network with a preset time interval T as a period, wherein T is a positive integer greater than or equal to 1.

8. The method for campus microgrid scheduling based on blockchain technology of claim 1, wherein,

after step S5, when each node operates according to the optimal scheduling scheme, if the obtained power generation information is different from the power generation information of the optimal scheduling scheme, repeating steps S3 to S5.

9. A campus microgrid scheduling system based on a blockchain technique, comprising:

the system comprises a block chain network module, wherein each node in the block chain network module comprises each unit of a campus micro-grid, and each unit comprises a power generation unit, a power utilization unit, a storage battery unit and a power grid interaction unit;

the information acquisition module can acquire an information group, integrates the information group through the intelligent contract module to acquire an integrated information set, and uploads the integrated information set to the blockchain network module, wherein the information group comprises power generation prediction information of a power generation unit, power utilization prediction information of a power utilization unit, self parameters and state information of a storage battery unit, tie line constraint information of an interaction unit with a power grid and power grid price information;

The construction module aims at the minimum total running cost of the park micro-grid, and constructs constraint conditions at the same time, so as to establish an economic dispatch model of the park micro-grid;

the optimization module optimizes the integrated information set by utilizing the economic dispatch model to obtain an optimized dispatch scheme;

and the distribution module is used for transmitting the optimal scheduling scheme to each node of the block chain network module.

10. A storage medium having stored therein a computer program which, when run in an electronic device, is loaded by a processor of the electronic device and performs the method of the block chain technology based campus microgrid scheduling of any one of claims 1-8.

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