Bie Chaohong et al. from Xi'an Jiaotong University: Research on "Source-Grid-Load" Planning of Energy Internet

China Energy Storage Network: 1. Why do we need to study the planning of energy Internet?

Human production and life activities have a huge demand for energy, but the reserves of fossil energy are limited and insufficient to support the long-term development of society. At the same time, the inefficient use of large-scale fossil energy has caused huge pollution to the environment. Energy crisis and environmental pollution have given rise to people's urgent need for sustainable, clean and efficient energy systems. With the development of energy utilization technology and the advancement of information technology, the deep integration of the two has given rise to a new energy utilization system - Energy Internet. Energy Internet can not only accommodate large-scale renewable energy but also improve energy utilization efficiency by coordinating and optimizing multiple energy systems. Energy Internet is the development direction of future energy systems. Optimizing the planning of Energy Internet is the basis of Energy Internet from theory to engineering practice. Only under the guidance of advanced and reasonable planning theory of Energy Internet can the construction of comprehensive and large-scale Energy Internet be smoothly implemented. At this stage, many demonstration projects of Energy Internet at home and abroad are under construction in full swing. The implementation of these demonstration projects can help gradually improve the planning theory system and lay a theoretical foundation for the subsequent large-scale engineering construction of Energy Internet.

2. Why is the energy Internet structured?

Energy Internet includes multiple energy systems such as electricity, natural gas, and heat. It is large in scale and has many components. It is too difficult to optimize and plan it as a whole. In order to reduce the difficulty of planning and improve the accuracy and feasibility of the planning model, this paper divides the energy Internet into energy production link (source)-energy transmission link (network)-energy consumption link (load) according to different components and tasks. The basic architecture of the energy Internet is shown in Figure 1.

Figure 1 Basic architecture of energy internet

Based on the “source-grid-load” structure of the energy Internet, and taking into account the main tasks, specific constraints, application influencing factors, etc. of each link, a planning model for each link can be established as shown in Table 1.

Table 1 Planning model for each link of energy internet

3. What is the basis for energy internet planning modeling?

The planning of energy internet is to know the physical characteristics and corresponding constraints of the planning object, select a suitable mathematical model to describe the physical characteristics of the planning object, and solve the appropriate planning scheme that meets the requirements of various indicators. Therefore, clarifying the basic constraints and establishing mathematical models that describe the operating characteristics of equipment and coupled energy flows are the basis for energy internet planning modeling. The basic constraints of the planning model are the load requirements of users' electricity, gas, and heat. The mathematical models involved in the planning of energy internet are mainly the coupling and conversion models of multiple energy flows and the flow models of multiple energy flow systems. The coupling and conversion models of multiple energy flows usually adopt the energy hub model proposed by the Swiss Federal Institute of Technology in Zurich; because planning studies long-term problems, the multi-energy flow flow model of the planning model adopts a steady-state flow model, that is, an algebraic equation that satisfies physical characteristics such as node energy balance.

4. What research has been done on the planning of energy production links?

The task of planning the energy production link is to fully consider the coupling of various forms of energy and the complementarity of physical characteristics under the conditions of meeting the various energy needs of users and achieving various technical and economic indicators, and determine when and where to build what type and scale of energy production, conversion, and storage equipment, so that the energy Internet can accept large-scale renewable energy and have good economic benefits during the planning period. In the energy Internet, thermal systems and natural gas systems with large-capacity energy storage equipment are interconnected and coupled with power systems through energy conversion equipment such as combined heat and power (CHP) units and power-to-gas. Compared with the power system, gas and thermal systems have larger inertia and time constants, and have good controllability and adjustability. Large-capacity heat and gas storage equipment enables the power system to smooth the impact of the intermittent and volatile nature of renewable energy on the energy system over a larger time scale and spatial range, thereby improving the system's renewable energy absorption capacity.

Taking the planning of the energy production link of electricity-heat combination as an example, we first analyze the output characteristics of electric boilers and CHP units, and combine the traditional generator model to establish a heat source model and the corresponding equipment output power constraints. Secondly, we fully consider the complementarity of electricity and heat, and establish a reasonable electricity-heat coupling power flow model based on the steady-state power flow of the power system and thermal system. Finally, by setting multiple scenarios and multiple time periods to simulate the system operation status, a mixed integer programming model of the electricity-heat combination system is established.

5. What research has been done on the coordinated planning of energy sources and networks?

The long-distance transmission of energy is mainly based on the power grid and the natural gas grid. The two networks are interconnected and coupled to transmit energy from the source side to the remote load on a large scale. The geographical distribution of renewable energy is relatively scattered. Wind power plants, photovoltaic power plants and power-to-gas plants need to be reasonably sited according to the existing power transmission network to facilitate energy transmission, and gas power plants must also be sited according to the natural gas grid to ensure the supply of natural gas. Therefore, the transmission link of the power-gas combined system cannot be planned alone, and coordinated planning of the source and the network is required. For the coordinated planning of the source and network links, we must first make the multi-energy systems on the source side and the load side equivalent, equate the production of multi-energy to gas source and power source (traditional power source, renewable energy), equate the load to gas load and electric load, and simplify the model to a power-gas combined system.

The planning of the combined electricity-gas system is basically based on the economic optimization of system investment and operation as the objective function, and the most basic constraint is the operation constraint of the combined electricity-gas system. Considering different influencing factors, a hierarchical iterative optimization model can be constructed for the planning model of the combined electricity-gas system. The main problem is set as the investment and construction of energy production, conversion, and storage equipment, site selection, and expansion of power networks and natural gas networks. The sub-problem is the optimal operation of a typical day or a planning year, and sub-problem constraints such as reliability and carbon emissions can be set separately. The main problem transfers the optimized system topology solution to the sub-problem, and the sub-problem transfers the corresponding cut set constraints or penalty functions to the main problem to ensure that the planning solution meets the problem boundaries of reliability, investment cost, etc., and a planning solution that meets the constraints is obtained through multiple coordinated iterations of the main and sub-problems.

6. What research has been done on energy consumption planning?

In the energy consumption link, the user's participation is improved, and the active participation of users can help achieve the flexibility and controllability of the system. The user's participation is mainly reflected in two aspects: 1) demand-side response dominated by price factors; 2) electric vehicle charging services. Energy consumption is mainly concentrated in urban areas. The multi-energy system in the city can be divided into regional multi-energy systems and energy microgrids according to scale. The regional multi-energy system is based on large residential areas, commercial areas or industrial parks, and includes energy conversion equipment such as CHP units, energy storage devices and multi-energy supply networks. The energy microgrid is based on residential buildings and hospitals, and mainly includes a set of combined heating, cooling and power generation devices and small energy storage facilities. Therefore, the planning of the energy consumption side can be divided into the planning of electric vehicle charging stations, the planning of regional multi-energy systems and the planning of energy microgrids as shown in Figure 2.

Figure 2 Division of planning content in energy consumption

For the planning of electric vehicle charging stations, we first need to analyze the impact of electric vehicle access on power development and grid operation, establish mathematical models of various states of electric vehicles, and simulate the behavior of electric vehicles. The constraints that need to be considered in the planning model mainly include road network structure, distribution network structure, charging station capacity constraints, charging waiting time, etc. The objective function can be set to minimize the investment in charging stations and distribution networks, minimize system operating costs, and maximize the traffic flow captured by charging stations. In real life, there are complex interactions between transportation systems and power systems, and current research is still in its infancy.