CN102426663A - Method for controlling universal-energy network by universal-energy current sequence parameter - Google Patents

Abstract

The invention discloses a method for controlling a ubiquitous energy network by using ubiquitous energy flow sequence parameters. The key sequence parameters of each level are determined from the relationship of the ubiquitous energy flow, among which the key sequence parameters are used to quickly evaluate and optimize the overall system performance; determine the optimization order of the ubiquitous energy network system performance according to the order parameter rules of the levels; optimize each system in turn according to the optimization order The key sequence parameters of the hierarchy; and determine the optimal ratio of the four links according to the optimal link ratio rule, where the optimal ratio of the four links is used to reduce the redundant universal energy flow of the system. The invention realizes the comprehensive optimization of the performance of the ubiquitous energy network system.

Description

A Method of Controlling Ubiquitous Energy Network Using Ubiquitous Energy Flow Sequence Parameters

technical field

The invention relates to the technical field of performance optimization of a ubiquitous energy network, in particular to a method for controlling a ubiquitous energy network by using a ubiquitous energy flow sequence parameter.

Background technique

The applicant proposed the scheme of ubiquitous energy network in Chinese patent applications 201010173519.1 and 201010173433.9, in order to realize the intelligence and informatization of various energy and materials, and multi-energy (multiple types of energy and/or from multiple geographical locations Coupling Utilization, Management and Transaction Services of Energy), the full content of which is incorporated herein by reference.

The ubiquitous energy network is a smart energy network system in which information, energy and matter are integrated through collaborative coupling. Ubiquitous energy network is based on system energy efficiency technology, through the coupling of energy and information in the four links of energy production, storage, application and regeneration cycle, it forms real-time coordination of energy input and output across time domains, and realizes the mutual conversion of multi-category energy horizontally. Supply and demand matching and cascade utilization; vertically realize the optimal allocation of energy throughout the life cycle, fundamentally achieve energy efficiency maximization and emission minimization, and finally output a self-organized, highly ordered, efficient and intelligent energy.

The ubiquitous energy flow is a logical intelligent flow formed by the cooperative coupling of energy flow, material flow and information flow. Among them, the energy flow includes different secondary energy forms such as electricity, gas, and heat, the material flow includes water flow, logistics, etc., and the information flow includes communication, control, data collection and transmission, etc. The ubiquitous energy flow forms a closed-loop ubiquitous energy network system by connecting the energy efficiency gainer, energy efficiency controller, and the four links of the energy life cycle (ie, energy production, energy storage, energy application, and energy regeneration).

As shown in FIG. 1 , FIG. 1 is a schematic diagram of a topology structure of a ubiquitous energy network in the prior art. The topology of the ubiquitous energy network is composed of network relationships of "machine-machine, man-machine, man-man" and "mutual sensing, interaction, and mutual intelligence". At the machine-machine level, the daily operation is controlled by the online optimization of the ubiquitous energy network, the data exchange of the ubiquitous energy network system, and the balance optimization of the ubiquitous energy network. The trigger enables the machine-machine interaction, and the logic optimization achieves machine-machine mutual intelligence. At the human-machine level, after the injection of comprehensive optimization strategies, on-site monitoring personnel make basic adjustments to situations beyond the scope of daily business control to meet the needs of abnormal business changes. Human-machine interaction transmits information through sensors and human senses. Humans send instructions to make machines move, and machine actions also affect human needs. Humans achieve human-machine mutual intelligence through analysis and optimization. At the human-human layer, decision-making meetings are held for disasters, accidents, policies, etc., resource scheduling strategies are determined, and coordinated with corresponding plans, combined with the ubiquitous energy network management system, a comprehensive optimization strategy is formed and sent to the human-machine layer. Human-human interaction transmits information through various carriers, communicates and interacts through various languages, and an intelligent expert system can achieve the purpose of human-human mutual intelligence.

The ubiquitous energy network constitutes a decision-making network through a three-layer decision-making optimization system of mutual induction (machine-machine), interaction (human-machine), and mutual intelligence (human-human), thereby forming the fusion of "intelligence" and "energy". The cross-temporal and spatial coordination of flow from input to output and the multi-scale intelligent interaction in the ubiquitous energy network can realize high-grade absorption of environmental potential energy and efficient utilization of resource energy, and generate nonlinear efficiency enhancement of system energy in the whole life cycle, thereby outputting Smart energy with high quality and high efficiency.

The variables involved in the multi-layer decision-making optimization system are as follows: control variable n, variable state m, time T. Controlling the variable n and the variable state m makes the number of states of each layer increase exponentially at each moment T, and the combination of multi-layer state spaces will increase the state space exponentially, causing the disaster of dimensionality. The disaster of dimensionality means that when the number of variables (dimensions) increases, the complexity of learning increases exponentially, causing the time required for data and the amount of data to be close to incalculable.

If the macro variable P is 0 when the system is in a disordered state, and is not 0 when the system is in an ordered state, then the properties of the macro variable P can be used to indicate the generation and transformation of an ordered structure, and it is called a macro variable P is an order parameter of the system (Order Parameter). The sequence parameter of the ubiquitous energy flow is the driving force that can transform the disordered ubiquitous energy flow of the ubiquitous energy network system into an ordered ubiquitous energy flow, which can be specifically expressed as a control strategy for controlling logical flow and flow direction.

In the prior art, the optimization of the performance of the ubiquitous energy network system generally adopts two methods of integrated optimization and collaborative optimization. Among them, for integration and optimization, the current energy system is dominated by non-renewable energy and supplemented by renewable energy. Using all available resources, a variety of technologies are combined with small and micro thermoelectric cooling (planting) full-energy multi-systems according to local conditions. , Integrate and optimize multiple systems such as electricity, heat, gas, refrigeration, environment, and transportation. For collaborative optimization, energy enterprises have shifted from production to service. The energy system is realized through the automatic management, operation, and scheduling of intelligent computers and Internet communication systems, similar to the Internet of Things; under the optimal operation and scheduling of the Internet and intelligent computers, further Realize collaborative optimization with smart household appliances to achieve optimal scheduling in the smallest range; and use low-valley gas resources and low-valley power resources to store electricity and hydrogen for users' vehicles to achieve a balance between supply and demand of gas, electricity, heating, cooling and domestic hot water , so that each system reaches the optimal benefit state to reduce the cost of each energy system; finally, the waste gas is sent to the plant greenhouse, and the comprehensive utilization of energy and resources is implemented to achieve the environmental and resource goals of zero emissions.

Through the analysis of the above-mentioned integration optimization and collaborative optimization, it can be seen that the current optimization of the performance of the ubiquitous energy grid system still has the following limitations: the optimization of local energy only considers a single energy source, such as the optimization of a single power grid, and does not consider the multi-energy network. Integrated optimization, thus resulting in the lack of corresponding solutions when the complexity of the problem increases.

Contents of the invention

(1) Technical problems to be solved

In view of this, the main purpose of the present invention is to provide a method for controlling the ubiquitous energy grid by utilizing the ubiquitous energy flow sequence parameters, so as to realize the comprehensive optimization of the performance of the ubiquitous energy grid system.

(2) Technical solutions

In order to achieve the above purpose, the present invention provides a method for utilizing the ubiquitous energy flow sequence parameter ubiquitous energy network. The natural order parameter rules determine the key order parameters of each level from the relationship of the ubiquitous energy flow, in which the key order parameters are used to quickly evaluate and optimize the overall system performance; The key sequence parameters of each level are optimized sequentially; and the optimal ratio of the four links is determined according to the optimal link ratio rule, and the optimal ratio of the four links is used to reduce the redundant universal energy flow of the system.

Preferably, before analyzing the ubiquitous energy flow relationship of the four links of production, storage, application and regeneration in the ubiquitous energy network system, the method further includes: configuring the ubiquitous energy network system to indicate the production, storage, and application of the ubiquitous energy flow relationship And the four links of regeneration. The configuration of the ubiquitous energy network system is used to indicate the four links of production, storage, application and regeneration of the ubiquitous energy flow relationship, including: converting fossil energy, biomass energy, solar energy and wind energy into electrical energy, gas energy, and thermal energy that can achieve specific functions Or cold energy, configure this link as energy production link; configure the process of storing electric energy, thermal energy, cold energy or mechanical energy as energy storage link; configure the process of using electric energy, thermal energy, cold energy or mechanical energy as energy application link; configure collection The process of re-providing the surplus energy from the energy system application link, production link or storage link to the system is the energy regeneration link.

Preferably, the analysis of the ubiquitous energy flow relationship in the four links of production, storage, application and regeneration in the ubiquitous energy network system, and the step of determining the key sequence parameters of each level from the ubiquitous energy flow relationship according to the natural order parameter rules, specifically include: comparing The amount of energy consumed by energy units in the four links of production, storage, application, and regeneration in the ubiquitous energy network system determines the energy unit that consumes less energy as the key sequence parameter at each level.

Preferably, the step of determining the optimization order of the performance of the ubiquitous energy network system according to the rules of hierarchical order parameters includes: the ubiquitous energy network system is composed of four layers of four links, wherein the four links at the bottom layer transmit the requirements upward, and the four links at the upper layer go downward Transfer ability, according to the hierarchical order parameter rules, from the perspective of energy consumption, the reduction of the energy consumption of the bottom four links has a significant impact on the entire ubiquitous energy network system, so the bottom layer of the ubiquitous energy network system is determined The four links have the highest priority when optimizing the performance of the ubiquitous energy network system, and the upper four links have the lowest priority when optimizing the performance of the ubiquitous energy network system. The priority is gradually reduced during optimization.

Preferably, the determination of the optimal ratio of the four links according to the optimal link ratio rule includes: due to the dependence of the four links, there must be an optimal ratio, so that the four links maintain the optimum ratio during the entire life cycle operation. The determination of the optimal ratio of the four links is driven by the demand of the application link, and then different parameters of the production link, storage link and regeneration link are selected to calculate the minimum total energy consumption value of the four links and the maximum link satisfaction degree, the best matching ratio of the four links can be obtained.

Preferably, the best performance of the four links in the operation of the whole life cycle includes the minimum energy consumption and the highest link satisfaction, where the link satisfaction is the degree of satisfaction that makes each link operate normally under constraint conditions.

(3) Beneficial effects

It can be seen from the above technical solutions that the present invention specifically considers the integrated optimization of multiple energy sources. When the complexity of the problem increases, a corresponding solution is given to effectively reduce the search space, and the following beneficial effects are obtained:

1. The method for controlling the ubiquitous energy network using the parameters of the ubiquitous energy flow sequence provided by the present invention adopts the optimization rule of the ubiquitous energy flow sequence, and the optimization of the ubiquitous energy flow sequence is optimized at an exponential (t^(1/2)) convergence speed, And through the following parameter optimization rules, the key parameters are quickly found, thereby improving the energy efficiency level of the ubiquitous energy grid, and realizing the comprehensive optimization of the performance of the ubiquitous energy grid system.

2. The method for controlling the ubiquitous energy network by utilizing the sequence parameters of the ubiquitous energy flow provided by the present invention adopts the optimal link ratio rule, and seeks a combination strategy for the sequence parameters of each layer according to the optimal link ratio principle, then the search space will be From n^m to at most max(n, m), then the search time is at least reduced to the original (max(n, m)/n^m). In fact, if n order parameters are associated, the search space is still will decrease.

3. The method for controlling the ubiquitous energy network by utilizing the sequence parameters of the ubiquitous energy flow provided by the present invention adopts the hierarchical sequence parameter rules, optimizes the sequence parameters from the bottom layer, and bidirectionally transmits the input-output relationship through the hierarchical association constraints, which will further reduce the search space and reduce the The search time, the search space will be reduced to ∏max(n _i , m _i ), and the search time will be reduced to the original ∏max(n _i , m _i )/∏(n _i ^m _i ).

4. The method for controlling the ubiquitous energy network by using the ubiquitous energy flow sequence parameters provided by the present invention adopts the natural order parameter rules, and the natural order parameters can significantly reduce the energy consumption of the system. Relevant studies have shown that the introduction of the natural order parameters can reduce the ubiquitous A significant level of 10% of energy grid energy consumption.

Description of drawings

Fig. 1 is a schematic diagram of the topology structure of the ubiquitous energy network in the prior art;

Fig. 2 is the flow chart of the method for optimizing the performance of the ubiquitous energy network system by utilizing the ubiquitous energy flow sequence parameters provided by the present invention;

Fig. 3 is a schematic diagram of optimizing the performance of the ubiquitous energy network system applied to the residence by using the ubiquitous energy flow sequence parameters according to the first embodiment of the present invention;

Fig. 4 is a schematic diagram of optimizing the performance of the ubiquitous energy network system applied to the eco-city by using the ubiquitous energy flow sequence parameters according to the second embodiment of the present invention.

Detailed ways

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

At first, the realization principle of the present invention is as follows:

The ubiquitous energy flow sequence parameter technology is based on the ubiquitous energy flow sequence optimization rule, the optimal link ratio rule, the hierarchical sequence parameter rule, and the natural sequence parameter rule. Rapidly shrinking the policy space has an exponential convergence effect. The selection of sequence parameters is determined by sequence values, and the ubiquitous energy flow sequence parameter technology seeks key indicators hierarchically to quickly evaluate and optimize overall system performance.

The ubiquitous energy flow sequence parameter technology is mainly used to improve the collaborative ability of enterprises. The synergistic ability of an enterprise is an important guarantee for the growth of an enterprise. It affects the integration and utilization of enterprise resources, the coordination and cooperation of various departments of the enterprise, and the adaptability of the enterprise to the environment. Order parameter is the dominant element of enterprise synergy, and its determination will play a vital role in the formation and improvement of enterprise synergy.

The order parameter refers to the change from scratch in the process of system evolution, which affects the collective cooperative behavior of each element of the system from one phase transition state to another phase transition state, and can indicate the parameter of the formation of a new structure. The order parameter has three basic characteristics: 1) The order parameter is a macroscopic parameter. The synergy theory studies the macroscopic behavior of a system composed of a large number of subsystems, and only understands these macroscopic behaviors from the microscopic level; 2) the order parameter is the product of the collective operation of the microscopic subsystems, the representation and brightness of the cooperative effect; 3) the order parameter The parameter is produced through the synergy of various parts, and once it is formed, it becomes the control center of the system, governs the behavior of each subsystem, determines the orderly structure and functional behavior of the entire system, and dominates the overall evolution process of the system.

The sequence parameter of the ubiquitous energy flow is the driving force that can transform the disordered ubiquitous energy flow to the orderly ubiquitous energy flow in the ubiquitous energy network system, which can be specifically expressed as a control strategy to control the logical flow and flow direction. The ubiquitous energy flow sequence parameter technology is based on the ubiquitous energy flow sequence optimization rule, the optimal link ratio rule, the hierarchical sequence parameter rule, and the natural sequence parameter rule. Rapidly shrinking the policy space has an exponential convergence effect. The selection of sequence parameters is determined by sequence values, and the ubiquitous energy flow sequence parameter technology seeks key indicators hierarchically to quickly evaluate and optimize overall system performance.

Ubiquitous Energy Flow Sequence Parameter Optimization Rules: The sequence comparison ratio comparison of universal energy flow can determine the key sequence parameters more efficiently, and achieve the optimal result of the ubiquitous energy network with a high probability. The sequence comparison here includes hierarchical sequence, natural sequence and Comparison of sequences at different levels such as matching sequences.

Universal energy flow order parameter rule 1: natural order parameter rule (priority principle of non-function order parameter)

The so-called non-function sequence parameters refer to the sequence parameters that do not require the input of universal energy flow (such as sunlight, natural ventilation). Because the reactive sequence parameters will reduce the energy consumption of the ubiquitous energy network system relative to the active sequence parameters, the reactive sequence parameters are higher than the sequence values of the active sequence parameters.

Universal energy flow sequence parameter rule 2: hierarchical sequence parameter rule (lower layer sequence parameter priority principle)

Since the ultimate service object of the ubiquitous energy flow is to satisfy the bottom order parameters, the bottom order parameters play a decisive role in the performance of the ubiquitous energy network system, so the order value of the bottom order parameter is greater than the order value of the upper order parameter. The input-output relationship is bidirectionally transmitted between the hierarchical order parameters through hierarchical association constraints.

The third parameter rule of the universal energy flow sequence: the optimal link ratio rule (principle of optimal link ratio priority) The optimal production, storage, application and regeneration links will minimize the redundant universal energy flow of the system, so it can The ordinal value of the order parameter leading to the optimal link ratio is higher than the ordinal value of the suboptimal link ratio.

In the following, the optimization rules of the universal energy flow sequence, the optimal link ratio rules, the hierarchical sequence parameter rules and the natural sequence parameter rules are elaborated respectively.

Ubiquitous energy flow sequence optimization rules: The sequence comparison of the universal energy flow can determine the key sequence parameters more efficiently than the value comparison of the universal energy flow and achieve the optimal result of the universal energy network with a high probability. The sequence comparison here includes the hierarchical sequence, Comparison of different levels of order, such as natural order and matching order. Ubiquitous energy flow sequence optimization is optimized at an exponential (t^-(1/2)) convergence speed, and the key parameters are quickly discovered through the following sequence parameter optimization rules, thereby improving the energy efficiency level of the ubiquitous energy network.

The optimal link ratio rule: the optimal production, storage, application, and regeneration links will minimize the redundant universal energy flow of the system, which can lead to the order value of the order parameter of the optimal link ratio being higher than that of the suboptimal The ordinal value of the order parameter of the link ratio. For the order parameters of each layer, according to the principle of optimal link ratio to seek a combination strategy, then the search space will change from n^m to at most max(n, m), and the search time will be reduced to at least the original (max(n, m)/n^m), in fact, if the n order parameters are associated, the search space will be reduced. Here, the search space is usually used in the field of optimization, and refers to the combination of all possible solutions of the problem in the process of seeking the optimal solution of the problem.

Hierarchical order parameter rule: Since the ultimate service object of the ubiquitous energy flow is to satisfy the underlying order parameter, the underlying order parameter plays a decisive role in the performance of the ubiquitous energy network system, so the order value of the underlying order parameter is greater than the order value of the upper order parameter. The input-output relationship is bidirectionally transmitted between the hierarchical order parameters through hierarchical association constraints. The order parameter is optimized from the bottom layer, and the input-output relationship is transmitted bidirectionally through hierarchical association constraints, which will further reduce the search space and thus reduce the search time. The search space will be reduced to ∏max(n _i , m _i ), and the search time will also be Reduced to the original ∏max(n _i , m _i )/∏(n _i ^m _i ).

Natural sequence parameter rule: The so-called non-function sequence parameter refers to the sequence parameter that does not require the input of universal energy flow (such as sunlight, natural ventilation). Because the reactive sequence parameters will reduce the energy consumption of the ubiquitous energy network system compared with the functional sequence parameters, the sequence value of the reactive sequence parameters is higher than that of the functional sequence parameters. The natural order parameter can significantly reduce the energy consumption of the system. Related research (UTC-Tsinghua Institute) shows that the introduction of the natural order parameter can achieve a significant level of reducing the energy consumption of the ubiquitous energy network by 10%.

In the optimization process, the above three criteria are applied to the identification of key sequence parameters. First, the key sequence parameters of each layer are judged according to the natural (reactive) sequence parameter rules, and then the bottom layer is optimized first, and gradually optimized through the hierarchical dynamic correlation constraints. To the high level, and finally through the link matching rules, the system can have the function of self-organization and self-evolution.

Based on the above realization principle, Fig. 2 shows a flowchart of a method for optimizing the performance of the ubiquitous energy network system provided by the present invention using the ubiquitous energy flow sequence parameters, the method includes the following steps:

Step 201: Analyze the ubiquitous energy flow relationship of the four links of production, storage, application and regeneration in the ubiquitous energy network system, and determine the key sequence parameters of each level from the ubiquitous energy flow relationship according to the natural sequence parameter rules, where the key sequence parameters are used for Quickly evaluate and optimize overall system performance;

Step 202: Determine the optimization order of the performance of the ubiquitous energy network system according to the hierarchical order parameter rules;

Step 203: sequentially optimize the key sequence parameters of each level according to the optimization sequence;

Step 204: Determine the optimal ratio of the four links according to the optimal link ratio rule, where the optimal ratio of the four links is used to reduce the redundant universal energy flow of the system.

In the above optimization methods, sequential optimization runs through the entire optimization process. Firstly, the ubiquitous energy flow is optimized using the equal-interval discrete optimization method. Due to the increase in the number of samples, the optimization combination will increase exponentially. Using the sequential optimization method can solve this problem well: (1) soften the optimization target, and A good enough solution is used as the optimization goal; (2) Fast optimization is achieved through the comparison of the order of the universal energy flow instead of the comparison of the value. Practice has proved that using the sequential optimization method can reduce the strategy space exponentially, and seek key indicators to quickly evaluate and optimize the overall system performance. The above method is called the universal energy flow sequence parameter optimization method.

Example 1

Fig. 3 is a schematic diagram of optimizing the performance of a ubiquitous energy grid system applied to a residence by utilizing ubiquitous energy flow sequence parameters according to the first embodiment of the present invention.

Production (Generation), storage (Storage), application (Utilization), regeneration (Regeneration) four links (Four Stages) expressed as FS = (G, S, U, R).

在此公式中，由于四环节FS中包含G(生产)，S(储存)，U(应用)，R(再生)四个参数，但有的能量单元可能缺少某个或某几个环节，例如，亮度系统只有生产环节、应用环节，没有储存环节、再生环节，空格表示该能量单元不存在于该环节。下文公式中出现的空格同此处，均表示该能量单元不存在于该环节。For the bottom layer of the ubiquitous energy flow, the brightness system has four links, input electricity, attach natural light source, meet the brightness requirements, and output heat, that is

In this formula, since the four-link FS includes four parameters of G (production), S (storage), U (application), and R (regeneration), some energy units may lack one or several links, such as , the brightness system only has the production link and the application link, without the storage link and the regeneration link, and the empty space means that the energy unit does not exist in this link. The blanks in the following formulas are the same as here, which means that the energy unit does not exist in this link.

The temperature system has four links, input electricity and heat, and the heat generated by the brightness system is attached to meet the requirements of output heat, that is, $\mathrm{FS}=({\mathrm{E.}}_{\mathrm{1,1}}^{e,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{1,1}}^{h,u}\left(t\right)+o_{\mathrm{2,1}}^{h,g}\left(t\right),,{\mathrm{<figure-callout\; id="1"\; label="o"\; filenames="HSA00000503789700021.png,HSA00000503789700022.png"\; state="\{\{state\}\}">o</figure-callout>}}_{\mathrm{1,1}}^{h,g}\left(t\right),).$

For the second layer of the ubiquitous energy network, the electricity delivered by photovoltaics to the residence, together with electricity storage and heat storage, meets the needs of the temperature system and brightness system, that is $\mathrm{FS}=({\mathrm{E.}}_{\mathrm{4,2}}^{h,u}\left(t\right)+{\mathrm{<figure-callout\; id="1"\; label="o"\; filenames="HSA00000503789700021.png,HSA00000503789700022.png"\; state="\{\{state\}\}">o</figure-callout>}}_{\mathrm{1,2}}^{e,g}\left(t\right)+{\mathrm{<figure-callout\; id="1"\; label="o"\; filenames="HSA00000503789700021.png,HSA00000503789700022.png"\; state="\{\{state\}\}">o</figure-callout>}}_{\mathrm{1,2}}^{h,g}\left(t\right),,$ ${\mathrm{E.}}_{\mathrm{1,1}}^{e,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{2,1}}^{e,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{1,1}}^{h,u}\left(t\right),).$

For the third layer of the ubiquitous energy network, the electricity generated by photovoltaics meets the needs of electricity storage, heat storage, and residential electricity and heat, that is, $\mathrm{FS}=(\mathrm{Solar}\left(t\right),{\mathrm{E.}}_{\mathrm{4,2}}^{e,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{3,2}}^{h,u}\left(t\right),{\mathrm{E.}}_{\mathrm{4,2}}^{h,u}\left(t\right),).$

By analyzing the above general energy flow relationship, the present invention can find key sequence parameters. For example, in the first layer, natural light sources can be considered as key sequence parameters by comparing with electric energy because they consume less energy. In the same principle, both the second and third layers can find out the key sequence parameters, which is the first criterion of the key sequence parameters: the natural (reactive) sequence parameter rule. Practice has shown that by using the natural order parameter rules, the energy consumption of the ubiquitous energy grid can be reduced by more than 10%.

Secondly, because different levels have different effects on the entire energy application, for example, if the energy application of the first layer is optimized, the effect is more obvious than that of the upper layers, such as the second and third layers. Therefore, the optimization order of the present invention is from low to high in the hierarchy, and the priority is from high to low. This is the second criterion of the key sequence parameter: the hierarchy sequence parameter rule. The actual effect also shows that the energy saving at the user end has a very obvious effect on reducing the load at the production end of the entire ubiquitous energy network system.

Thirdly, the four links of the ubiquitous energy network, the flow of ubiquitous energy flow of production, storage, application, and regeneration, should maintain a certain ratio under certain conditions. When the optimal ratio is reached, the operation of the ubiquitous energy network in its entire life cycle The effect is the best, so when the present invention optimizes the flow of the ubiquitous energy flow in each link, if the flow of the ubiquitous energy flow in the four links can be optimized according to the optimal ratio of the four links, this will greatly improve the self-organization and self-evolution of the ubiquitous energy network. has a certain meaning. This is the third criterion of the sequence parameters of the universal energy flow: the link ratio rule.

In the optimization process of the present invention, the above three criteria are applied to the discrimination of key sequence parameters. First, the key sequence parameters of each layer are judged according to the natural (reactive) sequence parameter rules, and then the bottom layer is first optimized. Constraints are gradually optimized to high-level, and finally through link matching rules, the system can have the function of self-organization and self-evolution. In the optimization process, the sequential optimization method will be used throughout. Firstly, the equal-interval discrete optimization method is used to optimize the ubiquitous energy flow. Due to the increase in the number of samples, the optimization combination will increase exponentially, so the sequential optimization method can be used very well. To solve this problem: (1) Soften the optimization goal, and take a good enough solution as the optimization goal; (2) Quickly find the optimization through the comparison of the order of the universal energy flow instead of the comparison of the value. Practice has proved that using the sequential optimization method can reduce the strategy space exponentially, and seek key indicators to quickly evaluate and optimize the overall system performance. The above method is called the universal energy flow sequence parameter optimization method.

Fig. 4 is a partial schematic diagram of optimizing the performance of the ubiquitous energy network system applied to the eco-city by using the ubiquitous energy flow sequence parameters according to the second embodiment of the present invention.

Production (Generation), storage (Storage), application (Utilization), regeneration (Regeneration) four links (Four Stags) are expressed as: FS = (G, S, U, R).

For the bottom layer of the ubiquitous energy flow, there are four links in the brightness system, input electricity, attached with natural light source, to meet the brightness requirements, that is $\mathrm{FS}=({\mathrm{E.}}_{\mathrm{2,1}}^{e,u}\left(t\right)+\mathrm{Solar}\left(t\right),,o_{\mathrm{2,1}}^{h,g}\left(t\right),).$

The temperature system has four links, input electricity and heat, and the heat generated by the brightness system is attached to meet the requirements of output heat, that is, $\mathrm{FS}=({\mathrm{E.}}_{\mathrm{1,1}}^{e,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{1,1}}^{h,u}\left(t\right)+o_{\mathrm{2,1}}^{h,g}\left(t\right),,{\mathrm{<figure-callout\; id="1"\; label="o"\; filenames="HSA00000503789700021.png,HSA00000503789700022.png"\; state="\{\{state\}\}">o</figure-callout>}}_{\mathrm{1,1}}^{h,g}\left(t\right),).$

For the second layer of the ubiquitous energy network, the multi-generation, photovoltaic power transmission to the smart building, plus power storage and heat storage, meet the temperature system and brightness system requirements, that is $\mathrm{FS}=$ $({\mathrm{E.}}_{\mathrm{3,2}}^{e,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{2,2}}^{h,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{4,2}}^{h,u}\left(t\right)+{\mathrm{<figure-callout\; id="1"\; label="o"\; filenames="HSA00000503789700021.png,HSA00000503789700022.png"\; state="\{\{state\}\}">o</figure-callout>}}_{\mathrm{1,2}}^{e,g}\left(t\right)+{\mathrm{<figure-callout\; id="1"\; label="o"\; filenames="HSA00000503789700021.png,HSA00000503789700022.png"\; state="\{\{state\}\}">o</figure-callout>}}_{\mathrm{1,2}}^{h,g}\left(t\right),,{\mathrm{E.}}_{\mathrm{1,1}}^{e,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{2,1}}^{e,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{1,2}}^{h,u}\left(t\right),).$

For the third layer of the ubiquitous energy network, the multi-supply required electricity and gas, and solar energy is attached to meet the electricity and heat storage needs of smart buildings, that is, $\mathrm{FS}=({\mathrm{E.}}_{\mathrm{1,3}}^{m,g}\left(t\right)+{\mathrm{E.}}_{\mathrm{1,3}}^{e,g}\left(t\right)+\mathrm{Solar}\left(t\right),$ ${\mathrm{E.}}_{\mathrm{1,2}}^{e,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{2,2}}^{e,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{4,2}}^{e,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{1,2}}^{h,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{3,2}}^{h,u}\left(t\right),{\mathrm{E.}}_{\mathrm{3,2}}^{e,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{2,2}}^{h,u}\left(t\right)+{\mathrm{E.}}_{\mathrm{4,2}}^{h,u}\left(t\right),).$

Similar to the above example, at first, the present invention can analyze the above universal energy flow relationship through the natural (reactive) order parameter rule, and can find the key order parameter, such as in the third layer, according to the natural (reactive) order parameter rule, Energy consumption selection for multi-generation input, including electricity input, gas input, or electricity and gas input according to a certain ratio. The first layer and the second layer can seek key order parameters according to the same principle. Secondly, according to the hierarchy order parameter rules, different levels have different effects on the entire energy application. Optimizing the energy application of the first layer is more effective than optimizing the second and third layers. Therefore, the order of optimization should be from low to high, and the priority should be from high to low. Thirdly, according to the link ratio rules, the flow of the ubiquitous energy flow in the four links of ubiquitous energy network production, regeneration, application and storage should maintain a certain ratio under certain conditions. When the optimal ratio is reached, the ubiquitous energy network will Cycle runs at its best. Finally, the parameter optimization method of universal energy flow sequence is comprehensively used to soften the optimization objective and reduce the strategy space exponentially, so as to finally seek key indicators to quickly evaluate and optimize the overall system performance.

The specific embodiments described above have further described the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above descriptions are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims (7)

1. A method for controlling the ubiquitous energy network utilizing the ubiquitous energy flow sequence parameter, is characterized in that the method comprises: Analyze the ubiquitous energy flow relationship of the four links of production, storage, application, and regeneration in the ubiquitous energy network system, and determine the key sequence parameters of each level from the ubiquitous energy flow relationship according to the natural sequence parameter rules. The key sequence parameters are used for rapid evaluation and Optimize overall system performance; Determine the optimization order of the performance of the ubiquitous energy grid system according to the hierarchical order parameter rules; optimize the key sequence parameters of each level sequentially according to the optimization sequence; and According to the optimal link ratio rules, the optimal ratio of four links is determined, and the optimal ratio of four links is used to reduce the redundant universal energy flow of the system. 2. the method for utilizing the ubiquitous energy flow sequence parameter to control the ubiquitous energy network according to claim 1, characterized in that, the method analyzes the ubiquitous energy flow relationship of the four links of production, storage, application and regeneration in the ubiquitous energy network system Previously, also included: The configuration of the ubiquitous energy network system is used to indicate the four links of production, storage, application and regeneration of the ubiquitous energy flow relationship. 3. The method for controlling the ubiquitous energy network utilizing the ubiquitous energy flow sequence parameters according to claim 2, characterized in that, the configuration ubiquitous energy network system is used to indicate the four links of production, storage, application and regeneration of the ubiquitous energy flow relationship ,include: Transform fossil energy, biomass energy, solar energy and wind energy into electric energy, gas energy, thermal energy or cold energy that can achieve specific functions, and configure this link as an energy production link; The process of configuring the storage of electric energy, heat energy, cold energy or mechanical energy is the energy storage link; Configure the process of using electric energy, heat energy, cold energy or mechanical energy as the energy application link; The process of configuring and collecting the surplus energy in the application link, production link or storage link of the energy system and providing it to the system again is the energy regeneration link. 4. the method for controlling the ubiquitous energy network utilizing the ubiquitous energy flow sequence parameter according to claim 1, characterized in that, the analysis of the ubiquitous energy flow relationship of the four links of production, storage, application and regeneration in the ubiquitous energy network system, The steps of determining the key order parameters of each level from the universal energy flow relationship according to the natural order parameter rules include: Compare the energy consumption of energy units in the four links of production, storage, application and regeneration in the ubiquitous energy network system, and determine the energy units that consume less energy as the key sequence parameters at each level. 5. the method for utilizing the ubiquitous energy flow order parameter to control the ubiquitous energy network according to claim 1, is characterized in that, the described step of determining the optimization order of the ubiquitous energy network system performance according to the hierarchical order parameter rule includes: The ubiquitous energy network system is composed of four layers of four links, among which the bottom four links transmit the demand upward, and the upper four links transmit the capacity downward. According to the order parameter rules of the hierarchy, from the perspective of energy consumption, the energy consumption of the bottom four links is lower than that of the upper layer. The reduction of the energy consumption of the four links has a significant impact on the entire ubiquitous energy network system, so it is determined that the bottom four links of the ubiquitous energy network system have the highest priority in the performance optimization of the ubiquitous energy network system, and the upper four links have the highest priority in the ubiquitous energy network system. The system performance optimization has the lowest priority, and the priority of the ubiquitous energy network system performance optimization is gradually reduced from the bottom four links to the upper four links. 6. the method for utilizing the ubiquitous energy flow sequence parameter to control the ubiquitous energy network according to claim 1, is characterized in that, described according to optimal link proportioning rule to determine four link optimum ratios, comprising: Due to the dependence of the four links, there must be an optimal ratio that enables the four links to maintain the best performance during the entire life cycle operation. The determination of the optimal ratio of the four links is driven by the demand of the application link, and then Select different parameters of the production link, storage link and regeneration link, and calculate the minimum total energy consumption value of the four links and the maximum satisfaction degree of the link, and then obtain the optimal ratio of the four links. 7. The method for controlling the ubiquitous energy network by utilizing the ubiquitous energy flow sequence parameters according to claim 6, characterized in that, the best performance of the four links in the operation of the whole life cycle, including minimum energy consumption and satisfactory links The degree of satisfaction is the highest, and the link satisfaction is the degree of satisfaction that makes each link operate normally under the constraint conditions.

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