CN107730032A - A kind of electric cold and hot trilogy supply Optimal Scheduling of pan-energy network and method - Google Patents

Abstract

The present invention relates to the field of energy Internet, and in particular to a system and method for optimal dispatching of electricity, cooling and heating in a ubiquitous energy network. The system includes an input module, an optimal dispatch module and an output module. The input module is used to obtain the demand forecast data of electric cooling and heating, the fixed parameters of each equipment, the current state parameters of each equipment and the preset optimization step size in the pre-divided four links of the ubiquitous energy grid electricity cooling and heating triple supply, and optimize the scheduling The module is used to establish the optimal scheduling model of operating cost and entropy increase respectively, and obtain the optimized scheduling results. The output module is used to output the optimized scheduling results to each device, so as to control the operation of each device. The supply is divided into a four-link structure, introducing energy grades of different energy forms, making full use of various equipment and different energies, and improving energy utilization. At the same time, considering the optimal scheduling model with the optimization goal of minimizing the operating cost and entropy increase, in different requirements Select a different optimization scheduling model under.

Description

A Ubiquitous Energy Network Power Cooling and Heating Triple Supply Optimum Scheduling System and Method

technical field

The invention relates to the field of energy Internet, in particular to a system and method for optimal dispatching of electricity, cooling and heating in a ubiquitous energy grid.

Background technique

Vigorously developing renewable energy and establishing an "Energy Internet" that connects energy networks and information networks is not only a development trend in the world, but also an inevitable choice for establishing a modern energy system, solving my country's national energy security and environmental security, and achieving sustainable development. At present, my country's economic status is still in the extensive development mode, and the energy utilization efficiency is low, only 36.8%, which is lower than the world's average level (50%).

Energy Internet can be understood as the comprehensive use of advanced power electronics technology, information technology and intelligent management technology to interconnect a large number of new power network nodes composed of distributed energy collection devices, distributed energy storage devices and various types of loads to realize An energy peer-to-peer exchange and sharing network with two-way energy flow. The Energy Internet is composed of several energy local area networks connected to each other. The energy local area network is composed of energy routers, power generation equipment, energy storage equipment, and AC and DC loads. It can be connected to the grid or run independently off the grid.

The Energy Internet has distributed characteristics. As a new generation of energy supply mode, distributed energy systems include many energy devices, such as photovoltaic cells, wind power generators, internal combustion engines, gas turbines, gas boilers, absorption waste heat units, etc. Various types of energy loads such as cold and heat demand. Therefore, for the same energy demand, there can be different energy supply methods and scheduling strategies.

In the existing technology, the optimal scheduling for distributed energy systems is mainly to optimize the equipment capacity from an economic point of view. The optimization is relatively simple, and in practice, different energies will have different quality levels. When the system is actually running, the energy Utilization ratio is also very important, but in the prior art, the optimization problem of energy utilization ratio has not been considered.

Contents of the invention

The embodiments of the present invention provide a system and method for optimal dispatching of the ubiquitous energy network, electricity, cooling and heating triple supply, so as to solve the problem that the optimization of the energy system in the prior art is relatively simple and does not consider the energy utilization rate in actual operation.

The specific technical scheme that the embodiment of the present invention provides is as follows:

An optimal dispatching system for combined cooling and heating in a ubiquitous energy network, including:

The input module is used to respectively obtain the demand forecast data of electric cooling and heating, the fixed parameters of each equipment, the current state parameters of each equipment and the preset optimization step size in the pre-divided four links of the ubiquitous energy grid electricity cooling and heating triple supply;

The optimization scheduling module is used to establish the calculation models of the operating cost and entropy increase of each equipment in the four pre-divided links according to the data obtained by the input module and the determined energy grades of different energy forms, and based on the calculation models of each equipment The calculation model of operating cost and entropy increase, with the minimum operating cost and entropy increase as the optimization goal, respectively establishes the optimal scheduling model of the operating cost and entropy increase of the ubiquitous power grid combined cooling and heating, and respectively based on the operating cost and entropy-increased optimal scheduling model, perform optimal scheduling, and obtain optimal scheduling results;

The output module is used to output the optimized scheduling results obtained by the optimized scheduling module to the equipment in the pre-divided four links of the ubiquitous energy network combined cooling and heating, so that each equipment can be based on the optimized scheduling The results are adjusted for the run.

Preferably, the pre-divided four links of the ubiquitous grid, electricity, cooling and heating triple supply are respectively the production link, the storage and transportation link, the recycling link and the user link;

The production link includes at least photovoltaic cells, internal combustion engines, gas boilers and compression chillers, the storage and transportation link includes at least batteries, the recovery link includes at least waste heat boilers and absorption waste heat units, and the user link includes at least At least including electrical equipment, heating equipment and cooling equipment;

The input module is specifically used to: obtain demand forecast data for electricity, cooling and heating, at least including: obtain 24-hour power generation forecast of photovoltaic cells, user's 24-hour electricity/heat demand forecast in winter, and user's 24-hour electricity/cooling in summer demand forecasting;

Obtain the fixed parameters of each device, including at least: obtaining the rated power and minimum start-stop time of the internal combustion engine, the rated power of the gas boiler, the rated power of the compression chiller, and the selling price per unit of electricity in the grid;

Obtain the maximum capacity limit and minimum capacity limit of the storage battery;

Obtain the rated power of the waste heat boiler and the rated power of the absorption waste heat unit;

Obtaining the current state parameters of each device at least includes: obtaining the current power generation power of the internal combustion engine, the current operating power of the gas boiler, the current cooling power of the compression chiller, and the current stored power value of the battery;

Get the preset optimization step size.

Preferably, according to the data obtained by the input module and the determined energy grades of different energy forms, the calculation models of the operating cost and entropy increase of each device in the four pre-divided links are respectively established, and the optimization scheduling module is specifically used for:

Determine the entropy increase function of the combustion gas fuel based on the determined available heat of the combustion gas fuel of the internal combustion engine and the energy grade of the gas fuel, based on the determined entropy increase calculation method;

According to the heat taken away by the waste heat flue gas and the energy grade of the flue gas, based on the calculation method of the determined entropy increase, the entropy increase function of the combustion gas fuel is determined;

According to the heat taken away by the hot water in the jacket and the energy grade of the hot water, the entropy increase function of the hot water in the jacket is determined based on the calculation method of the determined entropy increase;

Determine the operating cost function of the internal combustion engine according to the unit price of the gaseous fuel and the flow rate of the used gaseous fuel;

According to the maximum value and the minimum value of the rated power of the internal combustion engine, a power generation constraint condition of the internal combustion engine is established, and a minimum start-stop time constraint condition of the internal combustion engine is established according to the minimum start-stop time of the internal combustion engine.

Preferably, according to the data obtained by the input module and the determined energy grades of different energy forms, the calculation models of the operating cost and entropy increase of each device in the four pre-divided links are respectively established, and the optimization scheduling module is specifically used for:

According to the heat supply of the gas boiler and the energy grade of the gas fuel, the entropy increase function of the gas boiler is determined based on the calculation method of the determined entropy increase;

Determine the operating cost function of the gas boiler according to the unit price of the gas fuel and the flow rate of the gas fuel used;

According to the maximum value and minimum value of the rated power of the gas boiler, the operating constraints of the gas boiler are established.

Preferably, according to the data obtained by the input module and the determined energy grades of different energy forms, the calculation models of the operating cost and entropy increase of each device in the four pre-divided links are respectively established, and the optimization scheduling module is specifically used for:

Determine the operating cost function of the compression chiller according to the unit electricity price of the power grid and the cooling power consumption of the compression chiller;

According to the maximum and minimum rated power of the compression chiller, the operating constraints of the compression chiller are established.

Preferably, according to the data obtained by the input module and the determined energy grades of different energy forms, the calculation models of the operating cost and entropy increase of each device in the four pre-divided links are respectively established, and the optimization scheduling module is specifically used for:

According to the selling price of electricity per unit in the power grid, and the amount of electricity purchased or sold from the large power grid, the operating cost of purchasing or selling electricity from the large power grid is determined;

When purchasing electricity from the large power grid, the entropy increase function due to thermal power generation is determined based on the calorific value generated by burning coal fuel and the energy grade of coal fuel, based on the determined entropy increase calculation method.

Preferably, the optimized scheduling module is further used for:

According to the maximum capacity limit and the minimum capacity limit of the battery, the power constraint condition of the battery is established;

At least according to the power generation of the internal combustion engine, the power consumption and cooling capacity of the compression chiller, the power generation of photovoltaic cells, the heat supply of gas boilers, the power purchased or sold from the large power grid, and the charging or discharging of batteries Electricity, cold and heat demand forecasting, the amount of cooling/heating by using the waste heat generated by the internal combustion engine, and the amount of cold storage/heat, to establish constraints on the balance between supply and demand of electricity, cooling and heating.

Preferably, based on the calculation model of the operating cost and entropy increase of each device, with the minimum operating cost and entropy increase as the optimization goal, respectively establish the optimization of the operating cost and entropy increase of the ubiquitous power grid combined cooling and heating. Scheduling model, the optimized scheduling module is specifically used for:

According to the operating cost function of the internal combustion engine, the operating cost function of the gas boiler, the operating cost of the compression chiller, and the operating cost of purchasing/selling electricity from the large power grid, the optimization goal is to minimize the operating cost , to establish the operating cost objective function;

According to the entropy increase of the internal combustion engine, the entropy increase of the gas boiler, and the entropy increase caused by thermal power generation when purchasing electricity from the large power grid, the entropy increase minimum is the optimization goal, and an entropy increase objective function is established;

The power generation constraints of the internal combustion engine, the minimum start-stop time constraints of the internal combustion engine, the operation constraints of the gas boiler, the operation constraints of the compression chiller, the battery power constraints, and the The constraint conditions of the supply and demand balance of electric cooling and heating are used as the constraint conditions of the operating cost objective function and the entropy increase objective function.

An optimal scheduling method for combined cooling and heating in a ubiquitous energy network, including:

Respectively obtain the demand forecast data of electric cooling and heating, the fixed parameters of each equipment, the current state parameters of each equipment and the preset optimization step size in the four pre-divided links of the ubiquitous energy grid electricity cooling and heating tri-supply;

According to the data obtained by the input module and the determined energy grades of different energy forms, the calculation models for the operation cost and entropy increase of each equipment in the four pre-divided links are respectively established;

Based on the calculation model of the operation cost and entropy increase of each device, with the minimum operation cost and entropy increase as the optimization goal, respectively establish the optimal dispatching model of the operation cost and entropy increase of the ubiquitous grid, electricity, cooling and heating triple supply, and Optimal scheduling is performed based on the optimal scheduling model of the operating cost and entropy increase respectively, and an optimal scheduling result is obtained;

The optimal scheduling results obtained by the optimal scheduling module are output to each device in the four pre-divided links of the ubiquitous power grid combined cooling and heating, so that each device can adjust and operate based on the optimal scheduling results.

Preferably, the pre-divided four links of the ubiquitous grid, electricity, cooling and heating triple supply are respectively the production link, the storage and transportation link, the recycling link and the user link;

The production link includes at least photovoltaic cells, internal combustion engines, gas boilers and compression chillers, the storage and transportation link includes at least batteries, the recovery link includes at least waste heat boilers and absorption waste heat units, and the user link includes at least At least including electrical equipment, heating equipment and cooling equipment;

Respectively obtain the demand forecast data of electric cooling and heating, the fixed parameters of each equipment, and the current state parameters of each equipment in the pre-divided four links of the ubiquitous energy grid electricity cooling and heating triple supply, specifically including:

Obtaining demand forecast data for electricity, cooling and heating, at least including: obtaining forecasted photovoltaic cell power generation 24 hours a day, users' 24 hours a day's electricity/heat demand forecast in winter, and users' summer 24 hours a day's electricity/cooling demand forecast;

Obtain the fixed parameters of each device, including at least: obtaining the rated power and minimum start-stop time of the internal combustion engine, the rated power of the gas boiler, the rated power of the compression chiller, and the selling price per unit of electricity in the grid;

Obtain the maximum capacity limit and minimum capacity limit of the storage battery;

Obtain the rated power of the waste heat boiler and the rated power of the absorption waste heat unit;

Obtaining the current state parameters of each device at least includes: obtaining the current generating power of the internal combustion engine, the current operating power of the gas boiler, the current cooling power of the compression chiller, and the current stored power value of the battery.

Preferably, according to the data obtained by the input module and the determined energy grades of different energy forms, the calculation models for the operating cost and entropy increase of each device in the four pre-divided links are respectively established, specifically including:

Determine the entropy increase function of the combustion gas fuel based on the determined available heat of the combustion gas fuel of the internal combustion engine and the energy grade of the gas fuel, based on the determined entropy increase calculation method;

According to the heat taken away by the waste heat flue gas and the energy grade of the flue gas, based on the calculation method of the determined entropy increase, the entropy increase function of the combustion gas fuel is determined;

According to the heat taken away by the hot water in the jacket and the energy grade of the hot water, the entropy increase function of the hot water in the jacket is determined based on the calculation method of the determined entropy increase;

Determine the operating cost function of the internal combustion engine according to the unit price of the gaseous fuel and the flow rate of the used gaseous fuel;

According to the maximum value and the minimum value of the rated power of the internal combustion engine, a power generation constraint condition of the internal combustion engine is established, and a minimum start-stop time constraint condition of the internal combustion engine is established according to the minimum start-stop time of the internal combustion engine.

Preferably, according to the data obtained by the input module and the determined energy grades of different energy forms, the calculation models for the operating cost and entropy increase of each device in the four pre-divided links are respectively established, specifically including:

According to the heat supply of the gas boiler and the energy grade of the gas fuel, the entropy increase function of the gas boiler is determined based on the calculation method of the determined entropy increase;

Determine the operating cost function of the gas boiler according to the unit price of the gas fuel and the flow rate of the gas fuel used;

According to the maximum value and minimum value of the rated power of the gas boiler, the operating constraints of the gas boiler are established.

Preferably, according to the data obtained by the input module and the determined energy grades of different energy forms, the calculation models for the operating cost and entropy increase of each device in the four pre-divided links are respectively established, specifically including:

Determine the operating cost function of the compression chiller according to the unit electricity price of the power grid and the cooling power consumption of the compression chiller;

According to the maximum and minimum rated power of the compression chiller, the operating constraints of the compression chiller are established.

Preferably, according to the data obtained by the input module and the determined energy grades of different energy forms, the calculation models for the operating cost and entropy increase of each device in the four pre-divided links are respectively established, specifically including:

According to the selling price of electricity per unit in the power grid, and the amount of electricity purchased or sold from the large power grid, the operating cost of purchasing or selling electricity from the large power grid is determined;

When purchasing electricity from the large power grid, the entropy increase function due to thermal power generation is determined based on the calorific value generated by burning coal fuel and the energy grade of coal fuel, based on the determined entropy increase calculation method.

Preferably, further include:

According to the maximum capacity limit and the minimum capacity limit of the battery, the power constraint condition of the battery is established;

At least according to the power generation of the internal combustion engine, the power consumption and cooling capacity of the compression chiller, the power generation of photovoltaic cells, the heat supply of gas boilers, the power purchased or sold from the large power grid, and the charging or discharging of batteries Electricity, cold and heat demand forecasting, the amount of cooling/heating by using the waste heat generated by the internal combustion engine, and the amount of cold storage/heat, to establish constraints on the balance between supply and demand of electricity, cooling and heating.

Preferably, based on the calculation model of the operating cost and entropy increase of each device, with the minimum operating cost and entropy increase as the optimization goal, respectively establish the optimization of the operating cost and entropy increase of the ubiquitous power grid combined cooling and heating. Scheduling model, specifically including:

According to the operating cost function of the internal combustion engine, the operating cost function of the gas boiler, the operating cost of the compression chiller, and the operating cost of purchasing/selling electricity from the large power grid, the optimization goal is to minimize the operating cost , to establish the operating cost objective function;

According to the entropy increase of the internal combustion engine, the entropy increase of the gas boiler, and the entropy increase caused by thermal power generation when purchasing electricity from the large power grid, the entropy increase minimum is the optimization goal, and an entropy increase objective function is established;

The power generation constraints of the internal combustion engine, the minimum start-stop time constraints of the internal combustion engine, the operation constraints of the gas boiler, the operation constraints of the compression chiller, the battery power constraints, and the The constraint conditions of the supply and demand balance of electric cooling and heating are used as the constraint conditions of the operating cost objective function and the entropy increase objective function.

The beneficial effects of the present invention are as follows: the optimal dispatching system for the combined supply of electricity, cooling and heating in the ubiquitous energy network, including: an input module, which is used to respectively obtain the demand forecast for electricity, cooling and heating in the pre-divided four links of the combined supply of electricity, cooling and heating in the ubiquitous energy network Data, fixed parameters of each device, current state parameters of each device and preset optimization step size; the optimization scheduling module is used to establish pre-divided The calculation model of the operation cost and entropy increase of each equipment in the four links, and based on the calculation model of the operation cost and entropy increase of each equipment, with the minimum operation cost and entropy increase as the optimization goal, respectively establish the said universal energy grid The optimal scheduling model of the operating cost and entropy increase of combined cooling and heating, and the optimal scheduling model based on the operating cost and entropy increase respectively, perform optimal scheduling, and obtain an optimized scheduling result; the output module is used to transfer the optimized scheduling module The obtained optimal scheduling results are respectively output to the equipment in the four pre-divided links of the ubiquitous energy network combined cooling and heating, so that each equipment can be adjusted and operated based on the optimized scheduling results. In this way, the ubiquitous energy grid The triple supply of electricity, cooling and heating is divided into a four-link structure, fully combining the equipment in the four-link structure, introducing energy grades of different energy forms, making full use of the different energies of heating and cooling in the three-link power supply of the ubiquitous energy network, improving energy utilization, and, at the same time Considering the optimal scheduling model with the optimization goal of minimizing the operating cost and entropy increase, different optimal scheduling models can be selected under different requirements to improve the flexibility of optimization.

Description of drawings

Fig. 1 is the basic frame diagram of the triple supply of cooling and heating of the ubiquitous energy network in the embodiment of the present invention;

Fig. 2 is a schematic diagram of the four-link structure of the ubiquitous energy network electricity cooling and heating triple supply in the embodiment of the present invention;

Fig. 3 is an optimized scheduling system for the integrated cooling and heating of the ubiquitous energy network in the embodiment of the present invention;

Fig. 4 is an optimal dispatching method of the combined cooling and heating of the ubiquitous energy network in the embodiment of the present invention.

detailed description

The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

To solve the problem that the optimization of the energy system in the prior art is relatively simple, and the problem of energy utilization rate in actual operation is not considered. In the embodiment of the present invention, for the combined supply of cold and heat of the pan-energy network, all links are fully combined, and energy grades are introduced. , make full use of the energy in the system, model each equipment in the pre-divided four links of the ubiquitous energy grid electricity cooling and heating trigeneration respectively, and then respectively establish the ubiquitous energy grid electricity cooling heating trigeneration model based on operating cost and entropy increase Optimizing the scheduling model, and optimizing the scheduling model based on the operating cost and entropy increase respectively, performing optimal scheduling, and obtaining an optimized scheduling result, so as to achieve optimal control of each device with the minimum operating cost and entropy increase as the optimization goal.

The solution of the present invention will be described in detail below through specific examples. Of course, the present invention is not limited to the following examples.

The embodiment of the present invention is mainly aimed at the triple supply of electricity, cooling and heating of the ubiquitous energy network, and optimizes the scheduling thereof, and then controls the operation of each device. Refer to Figure 1, which is the basic framework diagram of the Ubiquitous Grid, Electricity, Cooling and Heating.

Ubiquitous grid combined cooling and heating is a system that integrates power generation, refrigeration and heating processes, and connects the power grid, heating network and cooling network. Moreover, in the embodiment of the present invention, according to the energy transfer and conversion process, the trigeneration of electricity, cooling and heating in the ubiquitous energy network is divided into a four-link structure, and the flow direction of the three energy forms of electricity, cooling and heat in the four-link structure is clarified.

In the embodiment of the present invention, the optimal scheduling system of the combined supply of cooling and heating of the ubiquitous energy network communicates with the four pre-divided links respectively to realize the optimal scheduling of them.

Among them, the pre-divided four links of the ubiquitous energy network, electricity, cooling and heating are the production link, the storage and transportation link, the recycling link and the user link.

Among them, the production link includes at least photovoltaic cells, internal combustion engines, gas boilers and compression chillers; the storage and transportation link includes at least batteries; the recovery link includes at least waste heat boilers and absorption waste heat units; the user link includes at least electrical equipment, Heat equipment and cold equipment, further, storage and transportation links can also include water heat storage and water storage cold.

Refer to FIG. 2 , which is a schematic diagram of the four-link structure of the ubiquitous grid, electricity, cooling and heating in an embodiment of the present invention. It can be seen that the connection between the four links of the ubiquitous energy network, electricity, cold and heat combined supply and the flow direction of the three energy forms of electricity, cooling and heat in the four-link structure.

The electric energy generated in the production link supplies the user's electric energy demand, and the waste heat discharged from the equipment in the generation link is used to provide heat and cooling to the user through the waste heat recovery and utilization equipment in the recovery link, realizing the cascade utilization of energy and improving the efficiency of the entire system. primary energy efficiency.

As shown in Figure 3, in the embodiment of the present invention, the optimal scheduling system for the combined supply of electricity, cooling and heating in the ubiquitous energy grid includes:

The input module is used to respectively obtain the demand forecast data of electric cooling and heating in the pre-divided four links of the ubiquitous energy grid electricity cooling and heating triple supply, the fixed parameters of each equipment, the current state parameters of each equipment and the preset optimization step size.

The optimization scheduling module is used to establish the calculation models of the operating cost and entropy increase of each equipment in the four pre-divided links according to the data obtained by the input module and the determined energy grades of different energy forms, and based on the calculation models of each equipment The calculation model of operating cost and entropy increase, with the minimum operating cost and entropy increase as the optimization goal, respectively establishes the optimal scheduling model of the operating cost and entropy increase of the ubiquitous power grid combined cooling and heating, and respectively based on the operating cost and entropy-increased optimal scheduling model to perform optimal scheduling and obtain optimal scheduling results.

The output module is used to output the optimized scheduling results obtained by the optimized scheduling module to the equipment in the pre-divided four links of the ubiquitous energy network combined cooling and heating, so that each equipment can be based on the optimized scheduling The results are adjusted for the run.

The following is a detailed introduction to the above-mentioned input module, optimal scheduling module and output module:

1. Input module.

The input modules are respectively connected to the pre-divided four links of the ubiquitous grid, electricity, cooling and heating triple supply, and are specifically used for:

1) Obtaining demand forecast data for electricity, cooling and heating, at least including: obtaining forecasted power generation of photovoltaic cells 24 hours a day, users' 24 hours a day's electricity/heat demand forecast in winter, and users' summer 24 hours a day's electricity/cooling demand forecast;

2) Obtain the fixed parameters of each equipment, including at least: obtaining the rated power and minimum start-stop time of the internal combustion engine, the rated power of the gas boiler, the rated power of the compression chiller, and the selling price per unit of electricity in the power grid;

Obtain the maximum capacity limit and minimum capacity limit of the storage battery;

Obtain the rated power of the waste heat boiler and the rated power of the absorption waste heat unit;

3) Obtain the current state parameters of each device, at least including: the current power generation power of the internal combustion engine, the current operating power of the gas boiler, the current cooling power of the compression chiller, and the current stored power value of the battery.

4) Obtain a preset optimization step size.

That is to say, in the embodiment of the present invention, according to the actual needs, the input module can obtain the relevant data of the required equipment in the four links respectively. Of course, in the embodiment of the present invention, the data obtained by the input module is not limited to the above data parameters, but also Other data can be obtained according to actual needs, and then a model can be established for the optimization scheduling module to provide data for optimal scheduling.

2. Optimize the scheduling module.

The optimal scheduling module is connected to the input module, and based on the data obtained by the input module, a model is established, and optimal scheduling is performed to obtain optimal scheduling results. specifically:

First, according to the data acquired by the input module and the determined energy grades of different energy forms, the calculation models of the operating cost and entropy increase of each equipment in the four pre-divided links are respectively established.

In the embodiment of the present invention, the energy grade is introduced into the calculation of entropy increase, wherein the energy grade represents the quality of different energy forms, and the level of energy quality is reflected in the transfer and conversion process between different energies. Based on the degree of conversion of different energies, different types of energy can be divided into fully convertible energy, partially convertible energy and non-transformable energy.

In order to facilitate subsequent understanding and description, in the embodiment of the present invention, entropy is first defined and given And the calculation method of the energy grade of different energy forms.

In practice, in engineering, the system is usually regarded as a stable flow system. When the system exchanges energy with the environment, the flow rate of the import and export logistics of the system The value can be defined as follows: When the system reversibly changes from an arbitrary state to an equilibrium state, the part of the energy in the system that can be converted into "advanced" energy to the maximum is called

In the analysis of a steady flow system, under the condition of ignoring the stream kinetic energy and potential energy, determine Definition:

E＝ _Eph + _Ech

Among them, E _ph is the physical E _ch for chemistry

In order to simplify the calculation, for the steady flow system, and the physical compared to chemical can be ignored, so from the first law of thermodynamics, the steady flow system It is: E≈E _ph =HH ₀ −T ₀ (SS ₀ ).

Among them, H is the enthalpy of the steady-flow working fluid, S is the entropy of the steady-flow working fluid, H ₀ is the enthalpy of the steady-flow working fluid in the ambient state, S ₀ is the entropy of the steady-flow working fluid in the ambient state, and T ₀ is the standard ambient temperature.

according to The definition of the thermal process before and after The change can be expressed as: ΔE=ΔH-T ₀ ΔS

Therefore, the calculation formulas of energy grade λ and entropy increase ΔS can be determined respectively:

According to the calculation formula for determining the energy grade λ, the energy grades of different energy forms can be calculated respectively: hot water λ _h , electricity λ _e , natural gas λ _g , and flue gas λ _r .

Based on the above analysis and calculation, the calculation models for the operating cost and entropy increase of each equipment in the pre-divided four links are respectively established. Specifically, the objective function and constraint conditions based on the operating cost and entropy increase of each equipment are respectively determined as follows:

1) Internal combustion engine.

a. The entropy increase of the internal combustion engine can be divided into three parts: the entropy increase of the combustion gas fuel, the entropy increase of the waste heat flue gas and the entropy increase of the cylinder jacket hot water. Among them, waste heat flue gas and cylinder liner hot water are the waste heat forms of internal gas power generation. Although internal combustion engines may have various power generation waste heat forms, waste heat flue gas and cylinder liner hot water have relatively large heat, which is the main part that can be used. Therefore , in the embodiment of the present invention, only the entropy increase of these two parts in the form of power generation waste heat is calculated.

(1) The entropy increase of burning gaseous fuel.

According to the determined available heat of the gaseous fuel and the energy grade of the gaseous fuel, and based on the determined calculation method of the entropy increase, the entropy increase function of the gaseous fuel is determined, specifically:

The flow rate M _g,k (Nm ³ /h) of the gaseous fuel in the k period and the heat Q _g',k generated by the combustion in the combustion chamber can be approximated as a linear relationship: Q _g',k =M _g,k ·LHV· η _f .

Then the available heat can be expressed as: Q _g,k =Q _g',k ·η _g =M _g,k ·LHV·η _f ·η _g

Then the entropy increase of burning gaseous fuel can be expressed as:

Among them, LHV is the calorific value of low-level fuel, η _f is the combustion efficiency, η _p is the power generation efficiency, λ _g is the energy grade of the gas fuel, and P _g,k is the electrical output power during the k period.

The power generation efficiency η _p of the internal combustion engine changes with the electrical load α of the unit, and the power generation efficiency of the generator set under different load rates is different.

(2) Entropy increase of waste heat flue gas.

According to the heat taken away by the waste heat flue gas and the energy grade of the flue gas, and based on the determined calculation method of entropy increase, the entropy increase function of burning gaseous fuel is determined.

The heat taken away by waste heat flue gas can be expressed as: Q _h,g,k = Q _g',k η _h,g

Then the entropy increase of waste heat flue gas can be expressed as:

Among them, η _{h, g} is the heat coefficient taken away by waste heat flue gas.

(3) The entropy increase of the hot water in the cylinder jacket.

According to the heat taken away by the hot water in the jacket and the energy grade of the hot water, and based on the calculation method of the determined entropy increase, the entropy increase function of the hot water in the jacket is determined.

The heat taken away by the hot water in the jacket can be expressed as: Q _h,w,k = Q _g',k ·η _h,w

Then the entropy increase of the jacket hot water can be expressed as:

Among them, η _h,w is the heat coefficient taken away by the jacket water.

b. The operating cost of the internal combustion engine, that is, the cost of power generation is mainly reflected in the cost of gas fuel. According to the unit price of gas fuel and the flow rate of the gas fuel used, the operating cost function of the internal combustion engine is determined. For example, the power generation cost of the internal combustion engine can be expressed as C _g M _{g , k} .

Among them, C _g represents the unit price of gas fuel, such as natural gas, M _g,k represents the flow rate of gas fuel in k period,

Then the cost of power generation by the internal combustion engine can be expressed as:

c. Constraints of the internal combustion engine. Internal combustion engine power generation needs to be subject to at least constraints including upper and lower limits of power generation and start-stop time constraints.

(1) In order to ensure the stable and safe operation of the internal combustion engine, the power generation of the internal combustion engine must be constrained by the upper and lower limits of the power generation. According to the maximum and minimum rated power of the internal combustion engine, the power generation constraints of the internal combustion engine are established. For example, the power generation constraints can be expressed as: p _g,min ν _g,t ≤p _g,t ≤p _g,max ν _{g,t t} =k+1,k+2,...,k+T

in, p _g,k is the operating power of the internal combustion engine in the system state quantity collected at the last moment, and the power generation efficiency η _p of the internal combustion engine changes with the change of the electrical load rate α of the unit, then the electric output power of the k period can be expressed as: P _g,k =Q _g,k ·η _p .

ν _g,t is a 0-1 variable, when ν _g,t =1, it means that the internal combustion unit is in the running state, and when ν _g,t =0, it means it is in the off state.

(2) According to the minimum start-stop time of the internal combustion engine, the minimum start-stop time constraints of the internal combustion engine are established, specifically: In order to describe the minimum start-stop time constraints of the unit, the start-stop variable ν _g,k of the internal combustion engine is introduced, which is a 0-1 variable , when ν _g,k =1, it means that the internal combustion unit is in the running state, and when ν _g,k =0, it means that it is in the off state.

When the unit is initially on, using this variable, the internal combustion engine start-stop time constraint can be described as a linear expression of mixed integers:

Among them, NT is the total time, T _on is the shortest power-on time, UT is the time the unit must be in the power-on state at the beginning, and UT=max{0,min[NT,(T _on -X _on )v _g,0 ]}.

When the unit is initially shut down, the internal combustion engine start-stop time constraints can be described as:

Among them, T _off is the shortest shutdown time, DT is the duration that the unit must be in the shutdown state at the beginning, and DT=max{0,min[NT,(T _off -X _off )(1-v _g,0 )]} .

2) Gas boiler.

a. The relationship between heat supply and fuel consumption of gas boilers is: Q _{b, k} = M _{b, k} LHV η _b

Among them, M _b,k is the flow rate of natural gas during k period, Q _b,k is the boiler heat supply during k period, and η _b is the operating efficiency of the gas boiler.

According to the heat supply of the gas boiler and the energy grade of the gas fuel, based on the determined calculation method of the entropy increase, the entropy increase function of the gas boiler is determined. For example, the entropy increase of the gas boiler can be expressed as:

b. According to the unit price of gas fuel and the flow rate of gas fuel used, determine the operating cost function of the gas boiler. The operating cost of the gas boiler can be expressed as:

c. Operating constraints of gas boilers.

In order for the gas boiler to operate safely during heating/cooling, its operating power must be subject to upper and lower limits. According to the maximum and minimum rated power of the gas boiler, the operating constraints of the gas boiler are established. The operating constraints can be expressed as: Q _b,min ν _b,t ≤Q _b,t ≤Q _b,max ν _{b,t t} ＝k+1,k+2,...,k+T

in, Q _{b, k} is the operating power of the gas boiler in the system state quantity collected at the last moment. ν _b,t is a 0-1 variable, when ν _b,t =1, it means that the gas boiler is in the running state, and when ν _b,t =0, it means it is in the off state.

3) Compression chillers.

a. Determine the operating cost function of the compression chiller according to the selling price per unit of electricity in the power grid and the cooling power consumption of the compression chiller, specifically:

The relationship between power consumption and cooling capacity of a compression chiller can be expressed as:

Among them, Q _cc,k is the cooling capacity of the unit during the k period, P _c,k is the power consumption of the unit during the k period, and COP _c is the cooling coefficient of the unit.

Then the refrigeration cost of the compression chiller can be expressed as:

Among them, C _e is the selling price of grid unit electricity.

b. In order to ensure the safe operation of the compression chiller during heating/cooling, its operating power must be subject to upper and lower limits. According to the maximum and minimum rated power of the compression chiller, the operating constraints of the compression chiller are established , for example, this constraint can be expressed as:

Q _cc,min ν _c,t ≤Q _cc,t ≤Q _cc,max ν _c,t t=k+1,k+2,...,k+T

in, Q _cc,k is the operating power of the electric compressor unit in the system state quantity collected at the last moment. ν _c,t is a 0-1 variable, when ν _c,t =1, it means that the electric compressor unit is in the running state, and when ν _c,t =0, it means it is in the off state.

4) Battery.

In order to prevent the battery from being overcharged or overdischarged, the power of the battery needs to be maintained at the maximum storage capacity and the minimum storage capacity. According to the capacity limit of the battery, including the maximum capacity limit and the minimum capacity limit of the battery, the power constraint condition of the battery can be described as:

SOC _min ≤SOC _t ≤SOC _max t＝k+1,k+2,...,k+T

in, p _b,t is the charging (discharging) amount of the battery during k period, when When p b,t <0, it means the battery is charging, and when p _b,t <0, it means the battery is discharging. p _{b, k} is _{Qcc, and k} is the battery power in the system state quantity collected at the last moment.

5) Large power grid

a. According to the selling price of electricity per unit in the power grid and the amount of electricity purchased or sold from the large power grid, determine the operating cost of purchasing or selling electricity from the large power grid. The operating cost can be expressed as: F _m,k = C _e p _m,k

Among them, p _m,k is the amount of power purchased or sold from the large power grid during the k period. When p _{m ,k} > 0, it means purchasing electricity from the large power grid. Electricity.

b. In the embodiment of the present invention, when purchasing electricity from a large power grid, it is necessary to consider the entropy increase caused by it. In practice, the current domestic mainstream power generation method is still thermal power generation. As a fossil fuel, coal is used in the power generation system to convert its chemical energy into physical energy through direct combustion, and then realize the thermal power conversion through the Rankine cycle. Coal combustion produces high-temperature flue gas, and the energy grade value drops greatly.

According to the calorific value generated by burning coal fuel and the energy grade of coal fuel, and based on the determined calculation method of entropy increase, the entropy increase function generated by thermal power generation is determined, specifically:

The power generation and coal consumption of burning coal for power generation can be expressed as: m _k = μ p _m,k

The resulting heat can be expressed as: Q _c,k = m _k ·q _c

Among them, q _c is the calorific value of coal, which is approximately equal to 29307kJ/kg.

Then the entropy increase due to thermal power generation can be expressed as:

6) Determine the supply and demand balance constraints of electric cooling and heating.

The power supply/heating/refrigeration in the production link of the ubiquitous grid power combined cooling and heating needs to meet the needs of users, fully consider the utilization of energy in the ubiquitous grid power combined cooling and heating, at least according to the power generation of the internal combustion engine in the period t, compression The power consumption and cooling capacity of type chillers, the power generation of photovoltaic cells, the heat supply of gas boilers, the power purchased or sold from the large power grid, the power charged or discharged by batteries, and the electricity, cooling and heating needs of users Pre-measure, use the waste heat of internal combustion engine power generation for cooling/heating, cold storage/heating, and establish constraints on the balance between supply and demand of electric cooling and heating. The supply and demand balance constraints of electricity, cooling and heating can be expressed as:

P _g,t +P _pv,t +P _m,t -P _b,t =P _L,t (+P _c,t ) t=k+1,k+2,...,k+T

Q _C,t +Q _cc,k -Q _s,t =Q _CL,t t=k+1,k+2,...,k+T

Q _H,t +Q _b,k -Q _s,t =Q _HL,t t=k+1,k+2,...,k+T

Among them, the formula P _c,t is the power consumption of the electric compressor unit during the period t in summer, P _g,t is the power generation of the internal combustion engine during the period t, P _pv,t is the photovoltaic power generation during the period t, and P _m,t is the increase in the period of t. The grid purchases (sells) electricity, P _b,t is the battery charge (discharge) electricity during the t period, and P _L,t is the user's electricity demand during the t period. Q _C/H,t is the amount of refrigeration/heat supply using the waste heat generated by the internal combustion engine during the t period, Q _cc,t is the cooling capacity of the compression chiller during the t period, Q _b,t is the heat supply of the gas-fired boiler during the _t period, Q _{s, t} is the amount of cold storage (heat) in period t, and Q _CL,t and Q _HL,t are the demand for cold and heat in period t, respectively.

Then, based on the models based on the operation cost and entropy increase of each device, with the minimum operation cost and entropy increase as the optimization goal, respectively establish the optimal dispatching model of the operation cost and entropy increase of the ubiquitous grid, electricity, cooling and heating triple supply .

Specifically, it is divided into the following two optimal scheduling models:

a. Optimal scheduling model based on operating costs.

According to the operating cost of the internal combustion engine, the operating cost of the gas boiler, the operating cost of the compression chiller, and the operating cost of purchasing/selling electricity from the large power grid, the operating cost objective function is established with the minimum operating cost as the optimization goal.

In period k, when considering the optimization step size as T, the running cost objective function is:

Further, in the embodiment of the present invention, the lowest energy efficiency utilization rate is selected, and the power generation efficiency of the internal combustion engine is written into the objective function:

η _p = (8.935+33.157·α-27.081·α ² +17.989·α ³ )≥λ%

Among them, λ is the given minimum energy efficiency utilization rate in the target condition.

The constraints of the operating cost objective function include at least the constraints of power generation of the internal combustion engine, the minimum start-stop time constraints of the internal combustion engine, the operation constraints of the gas boiler, the operation constraints of the compression chiller, the power constraints of the battery, and the Constraints for heating and cooling supply and demand balance.

b. Optimal scheduling model based on entropy increase.

According to the entropy increase of the internal combustion engine, the entropy increase of the gas boiler, and the entropy increase of thermal power generation when purchasing electricity from the large power grid, the entropy increase objective function is established with the minimum entropy increase as the optimization goal.

In period k, when considering the optimization step size as T, the objective function is:

The constraints of the entropy increase objective function include at least the constraints of power generation of the internal combustion engine, the minimum start-stop time constraints of the internal combustion engine, the operation constraints of the gas boiler, the operation constraints of the compression chiller, the power constraints of the battery, and the Constraints for heating and cooling supply and demand balance.

Finally, based on the optimal scheduling models of the operating cost and entropy increase, optimal scheduling is performed to obtain optimal scheduling results.

According to the above two different optimal scheduling models, different optimal scheduling models can be selected according to actual needs, and optimal scheduling can be performed with the minimum operating cost or the minimum entropy increase as the optimization goal.

Specifically:

a. Optimal scheduling model for operating costs.

Based on the optimal scheduling model of operating cost, set the optimization step size, for example, 5, and set the value of λ, the minimum operating cost under different λ values can be obtained, and the rolling optimization is carried out with the optimized step size to obtain the optimal scheduling result.

Among them, the setting of the λ value can be based on the objective function to obtain the relationship between the operating cost and the power generation efficiency, and to select a better working point based on the two factors of economic benefit and energy efficiency utilization. Then at this working point, that is, after the value of λ is selected, a 24-hour optimization problem of combined cooling and power supply in summer and combined heat and power supply in winter is calculated respectively.

b. Optimal scheduling model based on entropy increase.

Based on the optimization scheduling model of entropy increase, set the optimization step size, for example, 5, and perform rolling optimization to obtain the optimal scheduling result.

Specifically, the optimal scheduling of electricity/heat in winter and optimal scheduling of electricity/cooling in summer with economical operation as the optimization goal, and the optimal scheduling of electricity/heat in winter and optimal electricity/cooling in summer with the optimization goal of minimizing entropy increase can be solved respectively. question. For example, take the current moment k as 1, bring it into the optimization model established above, and calculate the value of the optimization variable. Then, update the current time k to be k+1, and repeat this step until the optimal scheduling problem of 24 hours a day is solved.

In this way, in the embodiment of the present invention, when establishing the optimal scheduling model, the equipment in the four links of the pan-energy network, electricity, cooling and heating are fully combined, the power generation is fully combined with the gas-fired unit, and the gas-fired boiler and the compression chiller are used Such as peak-shaving equipment, make full use of distributed renewable clean energy and waste heat generated in the process of internal combustion engine power generation, and improve energy utilization.

Moreover, at the same time, considering the optimization goal of economical operation cost and entropy increase minimum, optimal scheduling is carried out. In different demand situations, different optimal scheduling models can be selected to perform rolling optimization to obtain corresponding optimal scheduling results, and the optimization results are more abundant.

3. Output module.

The output module is connected with the optimal scheduling module, and connected with the generation link, storage and transportation link, and the user link of the combined power cooling and heating supply of the ubiquitous energy grid, and is specifically used for:

The optimal scheduling results obtained by the optimal scheduling module are respectively output to each device in the four pre-divided links of the ubiquitous power grid combined cooling and heating, so that each device can be adjusted and operated based on the optimized scheduling results.

For example, the output module can output the optimal scheduling results to the control units of various devices, such as internal combustion engines, gas boilers, compression chillers, batteries, etc., and the control units control the operation of corresponding devices.

Referring to Fig. 4, in an embodiment of the present invention, an optimal dispatching method for combined cooling and heating in a ubiquitous energy grid includes:

Step 400: Obtain the demand forecast data of electric cooling and heating, the fixed parameters of each equipment, the current state parameters of each equipment and the preset optimization step size in the pre-divided four links of the ubiquitous energy grid electricity cooling and heating tri-supply.

In the embodiment of the present invention, the pre-divided four links of the ubiquitous energy network electricity cooling and heating triple supply are the production link, the storage and transportation link, the recycling link and the user link.

The production link includes at least photovoltaic cells, internal combustion engines, gas boilers and compression chillers, the storage and transportation link includes at least batteries, the recovery link includes at least waste heat boilers and absorption waste heat units, and the user link includes at least Include at least electrical equipment, heating equipment and cooling equipment.

Among them, the demand forecast data for electricity cooling and heating at least include: photovoltaic cell power generation forecast 24 hours a day, user forecast electricity/heat demand 24 hours a day in winter, and user forecast electricity/cooling demand 24 hours a day in summer.

The fixed parameters of each equipment include at least: the rated power and minimum start-stop time of the internal combustion engine, the rated power of the gas boiler, the rated power of the compression chiller, and the selling price per unit of electricity in the grid. Obtain the maximum capacity limit and minimum capacity limit of the battery; obtain the rated power of the waste heat boiler and the rated power of the absorption waste heat unit.

The current state parameters of each device at least include: the current power generation power of the internal combustion engine, the current operating power of the gas boiler, the current cooling power of the compression chiller, and the current stored power value of the battery.

Step 410: According to the data acquired by the input module and the determined energy grades of different energy forms, respectively establish the calculation models of the operating cost and entropy increase of each equipment in the four pre-divided links.

When step 410 is executed, it can be divided into the following situations:

First case: for internal combustion engines. Among them, the entropy increase of the internal combustion engine can be divided into three parts, namely: the entropy increase of the combustion gas fuel, the entropy increase of the waste heat flue gas, and the entropy increase of the cylinder jacket hot water.

1) Determine the entropy increase function of the combustion gas fuel based on the determined available heat of combustion gas fuel of the internal combustion engine and the energy grade of the gas fuel, based on the determined calculation method of entropy increase.

2) According to the heat taken away by the waste heat flue gas and the energy grade of the flue gas, based on the calculation method of the determined entropy increase, the entropy increase function of the combustion gas fuel is determined.

3) According to the heat taken away by the hot water in the jacket and the energy grade of the hot water, based on the calculation method of the determined entropy increase, the entropy increase function of the hot water in the jacket is determined.

4) Determine the operating cost function of the internal combustion engine according to the unit price of the gaseous fuel and the flow rate of the used gaseous fuel.

5) According to the maximum and minimum rated power of the internal combustion engine, the power generation constraints of the internal combustion engine are established, and the minimum start and stop time constraints of the internal combustion engine are established according to the minimum start and stop time of the internal combustion engine.

The second case: for gas boilers.

1) According to the heat supply of the gas boiler and the energy grade of the gas fuel, the entropy increase function of the gas boiler is determined based on the calculation method of the determined entropy increase.

2) Determine the operating cost function of the gas boiler according to the unit price of the gas fuel and the flow rate of the gas fuel used.

3) According to the maximum and minimum rated power of the gas boiler, the operating constraints of the gas boiler are established.

The third case: for compression chillers.

1) Determine the operating cost function of the compression chiller according to the selling price per unit of electricity in the power grid and the cooling power consumption of the compression chiller.

2) According to the maximum and minimum rated power of the compression chiller, the operating constraints of the compression chiller are established.

The fourth case: for the purchase or sale of electricity from large power grids.

1) Determine the operating cost of purchasing or selling electricity from the large grid based on the selling price per unit of electricity in the grid and the amount of electricity purchased or sold from the large grid.

2) When purchasing electricity from the large power grid, the entropy increase function due to thermal power generation is determined based on the calorific value generated by burning coal fuel and the energy grade of coal fuel, based on the determined calculation method of entropy increase.

Further, the following constraints are established:

1) For the battery.

According to the maximum capacity limit and the minimum capacity limit of the battery, the power constraints of the battery are established.

2) Aiming at the balance of cooling and heating supply and demand of the ubiquitous grid power supply and cooling triple power supply.

At least according to the power generation of the internal combustion engine, the power consumption and cooling capacity of the compression chiller, the power generation of photovoltaic cells, the heat supply of gas boilers, the power purchased or sold from the large power grid, and the charging or discharging of batteries Electricity, cold and heat demand forecasting, the amount of cooling/heating by using the waste heat generated by the internal combustion engine, and the amount of cold storage/heat, to establish constraints on the balance between supply and demand of electricity, cooling and heating.

Of course, it is also not limited to establishing the calculation model of the operating cost and entropy increase of the above-mentioned several types of equipment, and can choose other more equipment or arbitrarily choose from the above-mentioned several types of equipment according to actual needs. In the embodiment of the present invention, No limitation is imposed.

Step 420: Based on the calculation model of the operation cost and entropy increase of each device, with the minimum operation cost and entropy increase as the optimization goal, respectively establish the optimal scheduling of the operation cost and entropy increase of the ubiquitous power grid combined cooling and heating model, and an optimal scheduling model based on the operating cost and entropy increase respectively, to perform optimal scheduling and obtain an optimal scheduling result.

When executing step 420, it specifically includes:

1) According to the operating cost function of the internal combustion engine, the operating cost function of the gas boiler, the operating cost of the compression chiller, and the operating cost of purchasing/selling electricity from the large power grid, the operating cost is at least Optimize the objective and establish the operating cost objective function.

2) According to the entropy increase of the internal combustion engine, the entropy increase of the gas boiler, and the entropy increase caused by thermal power generation when purchasing electricity from the large grid, the entropy increase target function is established with the minimum entropy increase as the optimization goal.

3) The power generation constraints of the internal combustion engine, the minimum start-stop time constraints of the internal combustion engine, the operation constraints of the gas boiler, the operation constraints of the compression chiller, the battery power constraints, And the constraint condition of the supply and demand balance of electric cooling and heating is used as the constraint condition of the operating cost objective function and the entropy increase objective function.

Step 430: Output the optimal scheduling results obtained by the optimal scheduling module to each device in the pre-divided four links of the ubiquitous energy network combined cooling and heating, so that each device can perform the optimization based on the optimal scheduling results. Adjust the run.

It is worth noting that the specific execution method is the same as the execution method in the above-mentioned optimal dispatching system for combined cooling and heating of the ubiquitous energy network, and will not be repeated here.

To sum up, in the embodiment of the present invention, the optimal dispatching system for the combined power cooling and heating of the ubiquitous energy network includes: an input module, which is used to respectively obtain the pre-divided power cooling The heat demand forecast data, the fixed parameters of each equipment, the current state parameters of each equipment and the preset optimization step size; the optimization scheduling module is used to obtain the data obtained by the input module and the determined energy grades of different energy forms, respectively Establish the calculation model of the operation cost and entropy increase of each equipment in the four links of pre-division, and based on the calculation model of the operation cost and entropy increase of each equipment, with the minimum operation cost and entropy increase as the optimization goal, respectively establish the described The optimal scheduling model of the operating cost and entropy increase of the combined cooling and heating of the ubiquitous energy network, and the optimal scheduling model based on the operating cost and entropy increase respectively, perform optimal scheduling and obtain optimal scheduling results; the output module is used to convert all The optimized scheduling results obtained by the optimized scheduling module are respectively output to each device in the four pre-divided links of the ubiquitous energy grid power cooling and heating triple supply, so that each device can be adjusted and operated based on the optimized scheduling results. In this way, The ubiquitous energy grid electricity cooling and heating triple supply is divided into four-link structure, fully combines the equipment in the four-link structure, introduces energy grades of different energy forms, makes full use of the different energy of the ubiquitous energy grid triple supply of electricity cooling and heating, and improves energy utilization , and at the same time consider the optimal scheduling model with the optimization goal of minimizing the operating cost and entropy increase, different optimal scheduling models can be selected under different requirements to improve the optimization flexibility.

Those skilled in the art should understand that the embodiments of the present invention may be provided as methods, systems, or computer program products. Accordingly, the present invention can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow chart or blocks of the flowchart and/or the block or blocks of the block diagrams.

While preferred embodiments of the invention have been described, additional changes and modifications to these embodiments can be made by those skilled in the art once the basic inventive concept is appreciated. Therefore, it is intended that the appended claims be construed to cover the preferred embodiment as well as all changes and modifications which fall within the scope of the invention.

Apparently, those skilled in the art can make various changes and modifications to the embodiments of the present invention without departing from the spirit and scope of the embodiments of the present invention. In this way, if the modifications and variations of the embodiments of the present invention fall within the scope of the claims of the present invention and equivalent technologies, the present invention also intends to include these modifications and variations.

Claims (16)

1. The utility model provides an optimal scheduling system that cold and hot trigeminy of smart ability net supplied, its characterized in that includes:

the input module is used for respectively acquiring demand prediction data of electric heating and cooling in a pre-divided four-ring section of the universal energy network electric heating and cooling triple supply, fixed parameters of each device, current state parameters of each device and a preset optimization step length;

the optimization scheduling module is used for respectively establishing a calculation model of the operation cost and the entropy increase of each device in the four pre-divided links according to the data acquired by the input module and the determined energy grades in different energy forms, respectively establishing an optimization scheduling model of the operation cost and the entropy increase of the universal energy network electricity-cooling-heating triple supply by taking the operation cost and the entropy increase as optimization targets based on the calculation model of the operation cost and the entropy increase of each device, and respectively performing optimization scheduling based on the optimization scheduling model of the operation cost and the entropy increase to obtain an optimization scheduling result;

and the output module is used for respectively outputting the optimized scheduling result obtained by the optimized scheduling module to each device in the pre-divided four links of the universal energy network electricity, cooling and heating triple co-generation so as to enable each device to adjust and operate based on the optimized scheduling result.

2. The system of claim 1, wherein the pre-divided four sections for electricity, cold and heat triple supply of the universal energy network are a production section, a storage and transportation section, a recovery section and a user section respectively;

the production link at least comprises a photovoltaic cell, an internal combustion engine, a gas boiler and a compression type water chilling unit, the storage and transportation link at least comprises a storage battery, the recovery link at least comprises a waste heat boiler and an absorption type waste heat unit, and the user link at least comprises electric equipment, heat equipment and cold equipment;

the input module is specifically configured to: acquiring demand forecast data of electric heating and cooling, which at least comprises the following steps: acquiring the electricity generation forecast of a photovoltaic cell 24 hours a day, the electricity/heat demand forecast of a user 24 hours a day in winter and the electricity/cold demand forecast of the user 24 hours a day in summer;

obtaining fixed parameters of each device, at least comprising: acquiring rated power and minimum start-stop time of an internal combustion engine, rated power of a gas boiler, rated power of a compression type water chilling unit and unit electricity selling price of a power grid;

acquiring the maximum capacity limit and the minimum capacity limit of the storage battery;

acquiring rated power of a waste heat boiler and rated power of an absorption type waste heat unit;

acquiring current state parameters of each device, wherein the current state parameters at least comprise: acquiring the current power generation power of the internal combustion engine, the current operating power of the gas boiler, the current refrigeration power of the compression type water chilling unit and the current stored electric quantity value of the storage battery;

and acquiring a preset optimization step length.

3. The system according to claim 2, wherein a calculation model of the operating cost and entropy increase of each device in the four pre-divided links is respectively established according to the data acquired by the input module and the determined energy grades of different energy forms, and the optimization scheduling module is specifically configured to:

determining an entropy-increasing function of the combustion gas fuel based on the determined entropy-increasing calculation mode according to the determined available heat of the combustion gas fuel of the internal combustion engine and the energy grade of the combustion gas fuel;

determining an entropy increasing function of the combustion gas fuel based on a determined entropy increasing calculation mode according to the heat quantity taken away by the waste heat flue gas and the energy grade of the flue gas;

determining an entropy increasing function of the cylinder sleeve hot water based on the determined entropy increasing calculation mode according to the heat quantity taken away by the cylinder sleeve hot water and the energy grade of the hot water;

determining an operating cost function of the internal combustion engine based on the unit price of the gaseous fuel and the flow rate of the gaseous fuel used;

and establishing a power generation constraint condition of the internal combustion engine according to the maximum value and the minimum value of the rated power of the internal combustion engine, and establishing a minimum start-stop time constraint condition of the internal combustion engine according to the minimum start-stop time of the internal combustion engine.

4. The system according to claim 2, wherein a calculation model of the operating cost and entropy increase of each device in the four pre-divided links is respectively established according to the data acquired by the input module and the determined energy grades of different energy forms, and the optimization scheduling module is specifically configured to:

determining an entropy increasing function of the gas boiler based on the determined entropy increasing calculation mode according to the heat supply quantity of the gas boiler and the energy grade of the gas fuel;

determining an operation cost function of the gas boiler according to the unit price of the gas fuel and the flow rate of the used gas fuel;

and establishing an operation constraint condition of the gas boiler according to the maximum value and the minimum value of the rated power of the gas boiler.

5. The system according to claim 2, wherein a calculation model of the operating cost and entropy increase of each device in the four pre-divided links is respectively established according to the data acquired by the input module and the determined energy grades of different energy forms, and the optimization scheduling module is specifically configured to:

determining an operation cost function of the compression type water chilling unit according to the unit electricity selling price of the power grid and the refrigeration power consumption of the compression type water chilling unit;

and establishing an operation constraint condition of the compression type water chilling unit according to the maximum value and the minimum value of the rated power of the compression type water chilling unit.

6. The system according to claim 2, wherein a calculation model of the operating cost and entropy increase of each device in the four pre-divided links is respectively established according to the data acquired by the input module and the determined energy grades of different energy forms, and the optimization scheduling module is specifically configured to:

determining the operation cost generated by purchasing or selling electricity to the large power grid according to the unit electricity selling price of the power grid and the electricity purchasing or selling electricity to the large power grid;

when electricity is purchased to a large power grid, an entropy increasing function generated by thermal power generation is determined based on a determined entropy increasing calculation mode according to a heat value generated by burning coal fuel and the energy grade of the coal fuel.

7. The system of claim 2, wherein the optimized scheduling module is further to:

establishing an electric quantity constraint condition of the storage battery according to the maximum capacity limit and the minimum capacity limit of the storage battery;

and establishing a constraint condition of electric cold and heat supply and demand balance at least according to the generated energy of the internal combustion engine, the power consumption and refrigeration amount of the compression type water chilling unit, the generated energy of the photovoltaic cell, the heat supply amount of the gas boiler, the electric energy for purchasing or selling electricity to a large power grid, the electric energy for charging or discharging the storage battery, the predicted electric, cold and heat demands of a user, the refrigerating/heat supply amount by using the generated waste heat of the internal combustion engine and the cold/heat accumulation amount.

8. The system according to any one of claims 1 to 7, wherein an optimized scheduling model of the operation cost and entropy increase of the electricity-cooling-heating triple co-generation of the smart energy grid is established based on the calculation model of the operation cost and entropy increase of each device with the minimum operation cost and entropy increase as optimization targets, and the optimized scheduling module is specifically configured to:

establishing an operation cost objective function by taking the minimum operation cost as an optimization target according to the operation cost function of the internal combustion engine, the operation cost function of the gas-fired boiler, the operation cost of the compression type water chilling unit and the operation cost of purchasing/selling electricity to a large power grid;

establishing an entropy increase objective function by taking the minimum entropy increase as an optimization objective according to the entropy increase of the internal combustion engine, the entropy increase of the gas boiler and the entropy increase caused by thermal power generation when power is purchased to a large power grid;

and taking the power generation constraint condition of the internal combustion engine, the minimum start-stop time constraint condition of the internal combustion engine, the operation constraint condition of the gas boiler, the operation constraint condition of the compression type water chilling unit, the electric quantity constraint condition of the storage battery and the constraint condition of the electricity-cooling-heat supply-demand balance as the constraint conditions of the operation cost objective function and the entropy increasing objective function.

9. An optimal scheduling method for electricity, cooling and heating triple co-generation of a universal energy network is characterized by comprising the following steps:

respectively acquiring demand prediction data of electric heating and cooling in a pre-divided four-ring section for electricity heating and cooling triple supply of the universal energy network, fixed parameters of each device, current state parameters of each device and a preset optimization step length;

respectively establishing a calculation model of the operation cost and entropy increase of each device in the four pre-divided links according to the data acquired by the input module and the determined energy grades of different energy forms;

on the basis of the calculation models of the operation cost and the entropy increase of each device, respectively establishing an optimization scheduling model of the operation cost and the entropy increase of the electricity-cooling-heating triple co-generation of the smart energy network by taking the operation cost and the entropy increase as optimization targets, and respectively carrying out optimization scheduling on the basis of the optimization scheduling models of the operation cost and the entropy increase to obtain an optimization scheduling result;

and respectively outputting the optimized scheduling result obtained by the optimized scheduling module to each device in the pre-divided four links of the universal energy network electricity, cooling and heating triple supply so as to enable each device to adjust and operate based on the optimized scheduling result.

10. The method of claim 9, wherein the pre-divided four sections for electricity, cooling and heating triple supply of the universal energy network are a production section, a storage and transportation section, a recovery section and a user section respectively;

the production link at least comprises a photovoltaic cell, an internal combustion engine, a gas boiler and a compression type water chilling unit, the storage and transportation link at least comprises a storage battery, the recovery link at least comprises a waste heat boiler and an absorption type waste heat unit, and the user link at least comprises electric equipment, heat equipment and cold equipment;

the method includes the steps of obtaining demand prediction data of electric heating and cooling water, fixed parameters of each device and current state parameters of each device in pre-divided four-ring sections of electricity heating and cooling triple supply of the universal energy grid respectively, and specifically includes the following steps:

acquiring demand forecast data of electric heating and cooling, which at least comprises the following steps: acquiring the electricity generation forecast of a photovoltaic cell 24 hours a day, the electricity/heat demand forecast of a user 24 hours a day in winter and the electricity/cold demand forecast of the user 24 hours a day in summer;

obtaining fixed parameters of each device, at least comprising: acquiring rated power and minimum start-stop time of an internal combustion engine, rated power of a gas boiler, rated power of a compression type water chilling unit and unit electricity selling price of a power grid;

acquiring the maximum capacity limit and the minimum capacity limit of the storage battery;

acquiring rated power of a waste heat boiler and rated power of an absorption type waste heat unit;

acquiring current state parameters of each device, wherein the current state parameters at least comprise: and acquiring the current power generation power of the internal combustion engine, the current operating power of the gas boiler, the current refrigeration power of the compression type water chilling unit and the current stored electric quantity value of the storage battery.

11. The method according to claim 10, wherein the step of respectively establishing a calculation model of the operation cost and entropy increase of each device in the four pre-divided links according to the data acquired by the input module and the determined energy grades of different energy forms comprises:

determining an entropy-increasing function of the combustion gas fuel based on the determined entropy-increasing calculation mode according to the determined available heat of the combustion gas fuel of the internal combustion engine and the energy grade of the combustion gas fuel;

determining an entropy increasing function of the combustion gas fuel based on a determined entropy increasing calculation mode according to the heat quantity taken away by the waste heat flue gas and the energy grade of the flue gas;

determining an entropy increasing function of the cylinder sleeve hot water based on the determined entropy increasing calculation mode according to the heat quantity taken away by the cylinder sleeve hot water and the energy grade of the hot water;

determining an operating cost function of the internal combustion engine based on the unit price of the gaseous fuel and the flow rate of the gaseous fuel used;

and establishing a power generation constraint condition of the internal combustion engine according to the maximum value and the minimum value of the rated power of the internal combustion engine, and establishing a minimum start-stop time constraint condition of the internal combustion engine according to the minimum start-stop time of the internal combustion engine.

12. The method according to claim 10, wherein the step of respectively establishing a calculation model of the operation cost and entropy increase of each device in the four pre-divided links according to the data acquired by the input module and the determined energy grades of different energy forms comprises:

determining an entropy increasing function of the gas boiler based on the determined entropy increasing calculation mode according to the heat supply quantity of the gas boiler and the energy grade of the gas fuel;

determining an operation cost function of the gas boiler according to the unit price of the gas fuel and the flow rate of the used gas fuel;

and establishing an operation constraint condition of the gas boiler according to the maximum value and the minimum value of the rated power of the gas boiler.

13. The method according to claim 10, wherein the step of respectively establishing a calculation model of the operation cost and entropy increase of each device in the four pre-divided links according to the data acquired by the input module and the determined energy grades of different energy forms comprises:

determining an operation cost function of the compression type water chilling unit according to the unit electricity selling price of the power grid and the refrigeration power consumption of the compression type water chilling unit;

and establishing an operation constraint condition of the compression type water chilling unit according to the maximum value and the minimum value of the rated power of the compression type water chilling unit.

14. The method according to claim 10, wherein the step of respectively establishing a calculation model of the operation cost and entropy increase of each device in the four pre-divided links according to the data acquired by the input module and the determined energy grades of different energy forms comprises:

determining the operation cost generated by purchasing or selling electricity to the large power grid according to the unit electricity selling price of the power grid and the electricity purchasing or selling electricity to the large power grid;

when electricity is purchased to a large power grid, an entropy increasing function generated by thermal power generation is determined based on a determined entropy increasing calculation mode according to a heat value generated by burning coal fuel and the energy grade of the coal fuel.

15. The method of claim 10, further comprising:

establishing an electric quantity constraint condition of the storage battery according to the maximum capacity limit and the minimum capacity limit of the storage battery;

and establishing a constraint condition of electric cold and heat supply and demand balance at least according to the generated energy of the internal combustion engine, the power consumption and refrigeration amount of the compression type water chilling unit, the generated energy of the photovoltaic cell, the heat supply amount of the gas boiler, the electric energy for purchasing or selling electricity to a large power grid, the electric energy for charging or discharging the storage battery, the predicted electric, cold and heat demands of a user, the refrigerating/heat supply amount by using the generated waste heat of the internal combustion engine and the cold/heat accumulation amount.

16. The method according to any one of claims 9 to 15, wherein the establishing of the optimal scheduling model of the operation cost and entropy increase of the electricity-cooling-heating triple co-generation of the smart energy grid based on the calculation model of the operation cost and entropy increase of each device with the operation cost and entropy increase minimum as the optimization target respectively comprises:

establishing an operation cost objective function by taking the minimum operation cost as an optimization target according to the operation cost function of the internal combustion engine, the operation cost function of the gas-fired boiler, the operation cost of the compression type water chilling unit and the operation cost of purchasing/selling electricity to a large power grid;

establishing an entropy increase objective function by taking the minimum entropy increase as an optimization objective according to the entropy increase of the internal combustion engine, the entropy increase of the gas boiler and the entropy increase caused by thermal power generation when power is purchased to a large power grid;

and taking the power generation constraint condition of the internal combustion engine, the minimum start-stop time constraint condition of the internal combustion engine, the operation constraint condition of the gas boiler, the operation constraint condition of the compression type water chilling unit, the electric quantity constraint condition of the storage battery and the constraint condition of the electricity-cooling-heat supply-demand balance as the constraint conditions of the operation cost objective function and the entropy increasing objective function.