In order to accurately measure the level of synergy and effectiveness of distributed energy systems, and through the synergy optimization between the subjects to further improve the overall benefits and achieve the goal of sustainable development of distributed energy resources, ensuring that user has access to affordable, reliable and sustainable modern energy, this study uses synergetic entropy to synergetic estimate distributed energy systems. Firstly, the relationship diagram of the distributed energy system is constructed as the research object. Secondly, based on the dissipation theory, the cooperative entropy index of distributed energy system is proposed, and the cooperative entropy calculation formula of distributed energy system is further established to comprehensively evaluate the evolution and the degree of synergy of distributed energy system.
The participating subjects and related relationships of distributed energy systems present different correlation characteristics and associated states at different stages of system development, and there are also hierarchical differences in the extent of driving factors. This study combines the relevant government work reports of power systems, important events of distributed energy power systems, national data and distributed energy power policies over the years to show the relationship, degree of association and type of association between the main components of distributed energy systems in the current stage.
4.1. Division of Distributed Energy Development Stage Based on Policy Analysis and Development Scale Analysis
In the 20 years of distributed energy development, the scale of China’s distributed power generation has been gradually expanded under the support and guidance of relevant national policies. Natural gas distributed generation, solar photovoltaic power generation, biomass power generation, wind power generation and other related support policies have been issued.
Figure 4 shows the key targeted policies for promoting distributed energy generation systems and the scale of distributed energy development represented by distributed photovoltaics and distributed biomass since 2000.
On the basis of comprehensive consideration of the factors affecting the stage of China’s distributed energy development, this paper divides the development time of China’s distributed energy system from 2000 to 2017 according to the promulgation time of key policies and the analysis of development scale. The period from 2000 to 2011 is the initial stage, and from 2012 onwards as a promotion stage.
4.1.1. Initial Stage (2000–2011)
The initial stage is the preliminary period of distributed energy. At this stage, the term distributed energy officially appears in government documents. Most of the policies are macro-enhancement policies, and the scale of distributed energy installation is limited. During this period, a number of cogeneration projects have been initially explored, and distributed energy projects represented by natural gas-fueled distributed energy systems were gradually put into use in large cities. In 2004, the National Development and Reform Commission’s Report of China on Issues Related to Distributed Energy Systems officially defined the concept of distributed energy. The pilot projects of distributed energy in economically developed areas have produced certain economic and social benefits, laying the foundation for the promotion and application of distributed energy systems into more expanded areas. However, the integration of distributed energy at this stage is still difficult, and the scale of distributed energy installation is only expanded to 10 GW, but the speed is relatively slow.
4.1.2. Promotion Stage (2012–Present)
The promotion phase is a period of substantial development of distributed energy. In this stage, policies are more targeted and the development speed of distributed energy is significantly accelerated. The policy intensity in this phase is correspondingly high. Since the “Twelfth Five-Year Plan”, the development of China’s distributed energy system has entered the promotion stage, and support policies have been introduced one after another, mainly involving natural gas distributed energy and distributed photovoltaics. Among them, the promulgation of the Interim Measures for Distributed Generation Management marks that China has begun to promote the development of distributed energy. In 2013, State Grid Corporation of China issued the “Opinions on Doing a Good Job of Distributed Power Grid-Connected Services” to legalize and order the grid. At this stage, there are plenty cases in which a number of individual users self-generated applications for grid connections. This resulted in the scale of installed capacity reaching a maximum of 187%, and there is a tendency to continue to expand at this rate, with a considerable future potential.
Allowing distributed energy grid-connected is the milestone in the development process of distributed energy. However, the supporting measures involved in grid-connected are not perfect, and there are obstacles in the development of distributed energy, so as the economic benefits are not significant.
4.2. Multi-Agent Synergistic Relationship Analysis of Distributed Energy Systems
Based on the characteristics of distributed energy systems and existing research results, this paper extracts the main evolutionary entities. Based on the whole process idea, the key entities are extracted from the aspects of system guarantee level, technical support level and the three process of energy planning, investment construction, operation and maintenance. The relationship between the main body and the main body of the distributed energy system in the initial stage is shown in
Figure 5.
The relationship between the main body and the main body of the distributed energy system in the promotion stage is shown in
Figure 6.
According to the two-stage association diagram and the power-related experts’ review, the study constructs the main energy relationship matrix of the distributed energy system. The degree of association between the participating entities presents different degrees of strength, and the relationship matrix between distributed energy subjects is as listed in
Table 2 and
Table 3. Each column in the table represents the associated behavior accepted by the entity. Each row represents the associated behavior of the synergetic entities. The letters in the matrix indicate the type of association. The numbers in the matrix indicate the strength of the association. Level 1 indicates weak contact, level 2 indicates general contact, 3 indicates strong contact; P indicates policy management, C indicates capital flow, I indicates public opinion impact, E indicates basic attribute, T indicates technical support, and R indicates technology research and development.
In
Table 2 and
Table 3, A = Government, B = Industry Association, D = Distributed energy equipment supplier, F = Distributed energy investor, G = Financial Institutions, H = Engineering construction company, J = Distributed energy supplier, K = Grid company, L = Aggregator, M = User, N = Research institutions, O = International organizations, Q = Energy service company, S = Professional operation and maintenance company.
4.3. Synergistic Entropy Construction
Entropy is one of the parameters that characterize the state of matter in thermodynamics. Its physical significance is to measure the degree of chaos of the system. In this paper, synergy entropy is used to evaluate the multi-agent synergy of distributed energy systems. The aim is to construct an effective index to measure the synergy effect of the complex multi-agent network of the whole distributed energy system. Synergistic entropy is better for dynamic evaluation than traditional methods. The calculation results can show the development trend, find the optimization direction and the sustainable development path.As a quantitative analysis method for dissipative structures, the Brusselator model also provides a theoretical basis and an operational mathematical model for studying the related problems of distributed energy system coordination. In this paper, it is applied to the synergistic analysis of distributed energy systems. Based on the existing research results, the original Brusselator model is transformed, that is, the significance represented by A, B, D, E, X and Y is transformed into the related concept of distributed energy system coevolution.
Let A and B be the components of the cooperative energy entropy of the distributed energy system, that is, A is the positive entropy generated by the synergistic participant, and B is the negative entropy formed by the synergistic participant accepting the related association behavior. D and E are A. Two possible states under the interaction with B: D is the state of non-dissipative structure, that is, the group relationship of each synergistic participant is not clear; E is the state of dissipative structure, that is, the group relationship of each synergistic participant is clear. X, Y are quantifiable indicators that affect the degree of clarity of synergistic participation subject relationships, where X represents a quantifiable positive entropy indicator and Y represents a quantifiable negative entropy indicator. Based on the above definition, this study constructs a Brusselator model of distributed energy system coordination, as shown in Equation (1):
The study uses the synergetic entropy of the distributed energy system to represent that the distributed energy system participates in the synergistic main body and the factors affecting the synergy. In the synergistic process, the effective energy conversion efficiency decreases, and the ineffective energy consumption increases. System status coefficient changes. According to the characteristics of the entropy value, in the synergistic process of distributed energy systems, the larger the synergistic entropy value, the worse the synergistic evolution effect between entities; on the contrary, the better the synergistic evolution between entities.
Claude E. Shannon, one of the originators of information theory, expresses multiple discrete events in system
S as discrete event sets.
, where the probability of each event appearing randomly is
, so information entropy (i.e. total amount of information) can be defined as Equation (2):
Based on the above-mentioned distributed energy system synergistic Brusselator model structure (Equation 1), this study assumes that in the synergistic process of distributed energy systems,
fi is the number of the paths that the
i participating synergistic entity points to the other.
is the number of synergy paths for the
i participants to accept other synergistic participants. Assuming that there are “n” co-participants in the distributed energy system, the total number of co-evolution paths of the distributed energy system is as follows:
In this article, we write
P as
.According to the relationship between probability and Shannon’s entropy function, the evolutionary cooperative entropy expression of distributed energy systems can be obtained:
4.4. Synergetic Entropy Analysis of Distributed Energy Systems
According to the contents of Equations (4) and
Table 2 and
Table 3, the out-degree value and in-degree value of each evolutionary participant and the total number of relationships associated with it in the distributed energy system are calculated. In short, taking participant A as an example, the out-degree value is the number of the relationship lines that the participant participates in the remaining participants. The in-degree value is the number of association lines that the participant accepts from other participants. The number of all associations is the sum of their out-degree and in-degree value. The evolutionary cooperative entropy value of each synergistic participant is determined by the difference between the in-degree and out-degree value and the ratio of overall relationship.
According to the above introduction, the cooperative entropy value of each participating entity in the two stages of the distributed energy system is calculated. The evolutionary cooperative entropy includes positive entropy and negative entropy. Positive entropy will generate system internal friction and increase system evolution burden. Conversely, negative entropy will neutralize the system internal friction and coordinate the evolution of the overall system; The larger the entropy value, the worse the synergy performance of the subject. The larger the negative entropy value, the better the synergy performance of the subject.
Figure 7 shows in detail the changes in entropy values of distributed energy systematization participants (presenting positive entropy or negative entropy). According to the data provided in
Figure 7, the change rule of the entropy value of each participant and the co-evolution effect of each stage are analyzed.Because the weight establishment process of each synergistic participant is complex, there are many driving factorsand the data collection is very difficult, this study only performs the simple addition of the entropy values of the participants in the same level.
Through the statistical analysis of the synergistic entropy values of the synergistic entities of the distributed energy system, this paper concludes the following: Among the 14 participants, engineering construction companies, distributed energy suppliers, distributed energy equipment suppliers, power grid companies, and users all maintain negative entropy values in both phases. Among them, the entropy value of the grid company changed from −0.064 to −0.041, the largest change, indicating that the coordination degree of the grid company is significantly improved during the promotion stage. This change is due to the serious implementation of the national energy development strategy by power grid enterprises under the background of policy promotion and the China’s electricity reform policy. The grid company began to participate in distributed energy operations, and promoted the development of new energy and distributed power as an important political responsibility and social responsibility, and actively served the distributed energy system. The aggregator is a new type of participant between the user and the grid company. It appears for the first time in the promotion stage, with an entropy value of −0.044. As a participant in the power market operation, aggregators can not only buy electricity from the grid or users, but also sell their own stored power to users or power grids, with better synergy. The synergistic entropy of users changed from −0.071 to −0.073, and the synergistic ability fluctuated slightly. This is possibly due to the fact residential users began to install their own small-scale distributed energy at the promotion stage. All aspects of policy conditions are uncertain, leading to the degree of synergy appear a slight decline. The entropy values of engineering construction companies and distributed energy suppliers have not changed much, and the overall coordination situation is good.
The cooperative entropy values of government departments, industry associations, financial institutions, scientific research institutions, international organizations, and energy conservation service companies are all positive entropy values. Among them, the entropy value of international organizations has declined by a large margin, indicating that its influence is gradually increasing. This change is attributed to the increasing emphasis on the coordinated development of distributed energy systems by international organizations, which have enacted global energy policies such as the 2030 Agenda for Sustainable Development, promulgated in 2016. All countries recognize the government plays an important role in supporting power system transformation and energy system integration, and will cooperate to promote technology development and deployment in the fields of energy storage, electric vehicles and modern biomass energy, renewable energy heating, etc.,cooperate in accelerating smart grid deployment and interoperability. These policies not only provide a framework for the development of distributed energy systems in various countries, but also provide external pressure for the coordination of distributed energy systems from the perspective of international supervision. The synergy entropy of the government departments is positive and the change is not sigificant, indicating that the government’s policies on distributed energy systems are not in place. At this stage, there is still a lack of technical standards and management standards at the national level.
4.5. Comprehensive Benefits Improvement Strategy of Distributed Energy System
Combined with the characteristics of distributed energy, the influencing factors of comprehensive benefits and the current synergy between various entities, guided by the sustainable development of distributed energy, this paper proposes a comprehensive benefits and multi-agent synergistic optimization strategy for distributed energy systems.
4.5.1. Synergistic Optimization Strategies of Comprehensive Benefits of Government-Side
The optimization of the government side is based on the system construction of the comprehensive energy system. Through the formulation of relevant policies and laws and regulations, the cooperation with distributed energy system and scientific research institutions should be strengthened to standardize the development of distributed energy. The development level and comprehensive benefits of distributed energy should be further improved by relying on the demonstration and promotion led by the government. Specific synergistic optimization strategies are as follows.
(1) Improve the participation at the national macro level in the multi-agent synergy of distributed energy systems. Government should co-ordinate management andlegally regulate distributed generation and energy utilization models. Meanwhile, establish a national energy comprehensive management function department that adapts to the national conditions, and formulate relevant laws and regulations on distributed power sources, and clearly define distributed energy in law; establish an integrated energy research and development institution, conduct research on major issues in the energy field, and coordinate energy long-term planning to facilitate cooperation, integration and synergetic development in the energy field.
(2) Government should continue to issue clear policy signals, provide a flexible policy environment, further clarify the development orientation of distributed energy in energy transformation, increase financial support and tax support, subsidize project construction, especially the construction of demonstration projects, and consider returning part of the value added tax. At the same time, the power price compensation mechanism shall be improved and price concessions shall be implemented to coordinate the interests of different energy supply participants. In the mean time, further refine the overall objectives and main technical indicators of distributed energy development, and provide favorable grid-connected conditions, focus on the planning of distributed energy projects, and clarify the application conditions and approval procedures. Increase the supervision of key links such as grid connection and transaction after the completion of the project.
(3) Strengthen the coordination of distributed energy market, explore the adapted trading mode of distributed energy, and promote the distributed new energy microgrid in combination with the requirements of the power system, to make the microgrid into a market entity with independent power sales rights, including the distributed energy microgrid carrier as an independent power selling entity, for direct PV supply or interaction with nearby new energy projects. Encourage grid companies to give preferential treatment to internal and external transactions of distributed energy. At the same time, all power and energy companies are encouraged to actively participate in the construction of distributed energy projects, and arouse the enthusiasm of local capital to participate in the project to achieve win-win cooperation and benefits sharing.
(4) Enhance the degree of synergy with scientific research institutions and international organizations. The government should respond positively to the call of international organizations and integrate with the world goals. According to the future development direction, increase investment in scientific research, and propose to set up special funds for research on distributed energy technologies to cultivate professional talents. For instance, to train professional distributed energy planners. These talents must be familiar with relevant policies and regulations, understand various related technologies, and select appropriate distributed technologies according to local climate conditions and resources to achieve the best comprehensive benefits. Leaders in various energy sectors should take the lead in conducting distributed energy knowledge and technical training, enabling professionals to take the decision-making role and correctly guide the direction of distributed energy development.
4.5.2. Synergistic Optimization Strategies of Comprehensive Benefits of Distributed Energy Systems
The synergistic optimization of power side mainly consists of three aspects: energy planning, location valuation, capacity and equipment optimization. The specific optimization strategy is as follows:
(1) Energy service companies and aggregators should continuously build their core competitiveness, effectively integrate the resources of the industry chain, so that the benefits can bring together the entire industry chain and promote the synergetic development of the entire industry. In the early stage of energy planning, the planned system scope and energy load should be carefully considered, the basic types of projects should be clarified, and the development of distributed energy resources should be strengthened. Focusing on existing and future planned gas turbine power plants, the distributed energy project is developed in the controllable area of gas turbine power plants, which take advantage of the power generation and heat supply stability of the gas turbine power plant to ensure the continuous and stable operation of the system and enhance the reliability of the system operation. Actively plan integrated distributed energy supply solutions for natural gas, solar energy, wind energy, geothermal energy, biomass energy and energy storage to create an efficient and integrated energy supply model.
(2) Installing a distributed power source of appropriate capacity at a suitable location can reduce network loss and improve power quality. Methods for determining the optimal capacity and location should be explored to maximize the benefits of loss reduction. The power-side can consider actively investing in distributed energy projects in the demonstration area to strive for optimal policy support. In other areas where there is a high-quality load, a selective development project can be considered.
(3) Optimize the type and quantity of integrated energy system supply and storage equipment. Based on the overall load level of integrated energy in the planning area, the optimal combination scheme of refrigeration, heating, cooling and heat storage devices in the planning area is proposed for a variety of optimal planning objectives and the optimal operation of the whole life cycle. Secondly, the operation scheduling of the integrated energy system equipment should be optimized, and the system operation constraints and supply and demand balance constraints of energy supply and storage equipment are considered under different energy demand periods. Under the guidance of supply-demand relationship and price mechanism, various participants flexibly adjust energy supply, energy consumption and energy storage to achieve flexible interaction of integrated energy and vertical integration of supply-demand and storage, and improve the utilization efficiency of integrated energy.
4.5.3. Synergistic Optimization Strategies of Comprehensive Benefits of Power Grid Company
The optimization strategy of the power grid is based on the synergy enthusiasm of power grid enterprises. Under the condition of upgrading key technologies, coordinated planning and operation are carried out, and the pilot project is built on the premise. The specific optimization strategy is as follows:
(1) Power grid companies should consciously and actively improve the degree of synergy. Under the background of the reform of electric power, power grid enterprises have the right and obligation to actively participate in the investment, construction, operation and management of distributed energy projects, and realize the dual role mechanism transformation of distributed energy stakeholders. On the one hand, in order to avoid conflicts with the provisions of the Electricity Law, grid power companies can be used as stakeholders or project shareholders of distributed energy projects, and members of distributed energy are represented as legal representatives. On the other hand, the distributed energy enterprise thus formed can be used as a member of the power grid enterprise. Under the premise of meeting the terminal demand in the distributed energy region, according to the characteristics of the supply and demand balance of the large power grid and the function of the smart grid, the distributed generation unit’s opening, stopping and load rate are adjusted and optimized to realize the switching between the two modes of operation: grid power or online power sale during peak and low valley periods.
(2) Strengthen coordination with scientific research institutions, study key technologies of distributed energy, increase independent research and development efforts, and reduce dependence on technology in developed countries. In the future, we should further study the protection and control technologies of distributed energy and the new protection principles and methods of distributed power systems to improve the security of the entire social energy supply system. Grid company should analyze the operating characteristics of various distributed power sources and microgrids, the interaction mechanism between distributed power sources, microgrids, and power distribution systems. Developing relevant theories and methods, laying the foundation for energy management and distributed generation economic dispatch. It is necessary to research on distributed power grid-connected technology for the purpose of achieving efficient and user-friendly grid-connected power generation.
(3) Research on coordinated planning methods for distributed power distribution systems. Consider establishing a distribution network design and planning theory system suitable for distributed power supply characteristics, including distribution system structure design methods that contribute to microgrid access, comprehensive performance evaluation index system including distributed energy distribution systems, and new power distribution System optimization planning theory, etc.
4.5.4. Synergistic Optimization Strategies of Comprehensive Benefits of User-Side
The user-side synergistic optimization strategy is optimized through market demand response and user-side construction. The specific strategies are as follows:
(1) Strengthen the synergy among the government, financial institution and the user, liberalize the user-side distributed power supply construction, and promote the operation mode of “spontaneous use, surplus Internet access, and power grid adjustment” to encourage enterprises, institutions, communities, and families to adjust their own conditions. Invest in the construction of various types of distributed power sources such as rooftop solar and wind energy. It can integrate many small-scale energy comprehensive utilization equipment with different forms. In addition to the traditional electric/heat/cold load, it also includes a large number of renewable energy equipment, energy storage equipment, and comprehensive energy supply equipment.
(2) Apply the energy management system on the user side to guide users to avoid the peak of power consumption and cultivate better user habits. Improve the flexibility and reliability of power supply, give priority to the use of local renewable energy or large grid through power, and encouraging new energy sources to access the power demand side management platform in the region. The energy management department should work with relevant departments to study and formulate the demand side management policy of the distributed energy source, and explore the establishment of distributed energy as a market entity to participate in service compensation mechanisms such as interruptible load peak shaving, electric energy storage peak shaving, and black starts.
(3) Increase cooperation with scientific research institutions, use the energy Internet, integrate user-side services, smart grids and distributed generation, and develop smart electricity interactive business models and intelligent power system frameworks. And consider the energy characteristics of equipment for home users and business users, and develop intelligent power technology that integrates information collection, energy efficiency assessment, equipment control, and two-way interaction to realize household energy safety monitoring, electricity consumption information and property management. Function to integrate intelligent microgrid technology with distributed energy. In terms of terminal hardware, a user-oriented intelligent interactive terminal core module shall be developed to realize energy metering and device monitoring for large-scale users.