Abstract:The accurate calculation of the carbon emission indicator on the user side is the key to guiding the usage of low-carbon energy for users. However, the current carbon trajectory tracking methods for integrated energy systems only consider steady states, which cannot accurately calculate the carbon emission indicators of the natural gas and thermal system with significant load variation and long dynamic processes. Therefore, based on the superposition principle, the energy flow tracking and carbon entropy analysis of dynamic natural gas and thermal systems are carried out. Firstly, the dynamic energy flow model based on the superposition characteristics of the natural gas and thermal systems is established. Then, the energy flow is tracked by taking the line pack in the natural gas network and the time delay in the thermal network into consideration, and the source-load energy flow relationship within the system is defined. Secondly, based on the carbon entropy theory, the dynamic carbon entropy analysis methods of natural gas and thermal systems are proposed to clarify the source-load carbon emission relationships, and refined carbon emission indicators on the user side are formed. Finally, an integrated energy system in Jilin Province, China is taken as a case to verify the effectiveness of the model in dynamic energy flow analysis and carbon entropy analysis. The necessity of dynamic carbon trajectory tracking is also verified by comparing the model with the steady-state carbon trajectory tracking method.

Abstract:The utilization of nodal carbon intensity of multipe electric-gas-heat loads to guide demand response (DR) is an effective approach to achieve low-carbon operation in integrated energy systems (IESs). Due to the complex coupling relationships and intertwined dynamic characteristics of multiple energy flows, carbon emission characteristics are difficult to accurately express. The insufficient exploitation of low-carbon operation potential in IES is studied, and an economic dispatching method based on dual response of nodal carbon intensity and energy price is proposed for IES coordination between generation and load to achieve low-carbon operation. On one hand, by analyzing the influence mechanism of gas and heat dynamic characteristics on carbon emission flows, the concept of dynamic characteristic equivalence substitution is introduced to obtain a carbon emission flow model considering dynamic characteristics. Then, the carbon intensity at load nodes is obtained and the allocation of carbon emission responsibility is realized. On the other hand, from the carbon perspective, considering the carbon emission responsibility of multiple loads, the IES source-load low-carbon interaction mechanism based on the dual response of nodal carbon intensity and energy price of multiple loads is designed to fully explore the low-carbon intensity of multiple loads in IES. Through the tracking and measurement of carbon emission generation, transmission, and consumption processes in IES, a control strategy that balances economic and low-carbon factors is formulated. The effectiveness of the proposed model and method is validated using a test system consisting of a 14-bus power grid, a 6-bus heat network, and a 6-bus natural gas network (E14-H6-G6), as well as a system with E57-H12-G12.

Abstract:The entropy state mechanism and analysis method of the integrated energy system (IES) provides a new theoretical basis for the analysis of IES energy quality for renewable energy integration. For different energy system scales and scenarios, how to systematically solve the entropy state distribution of large-scale energy systems is one of the basic problems that need to be solved urgently in subsequent system planning, operation, and energy management and control. On the basis of IES entropy state theory, the calculation system and ideas of the system entropy state distribution are further sorted out. According to the needs of solving the entropy increase flow, some key calculation matrices and calculation column vectors are defined. Then, combined with the definition of IES exergy flow model and entropy state network, considering the entropy increase flow conversion and distribution mechanism of energy hub (energy station), the IES entropy state calculation models based on sequential solution and simultaneous solution are established. The correctness and effectiveness of the two calculation models are verified by cases, and the similarities, differences and applicability of the two calculation methods are discussed.

Abstract:With the promotion of carbon emission reduction in the power industry, the electricity-carbon coupling is becoming tighter, which brings new opportunities and challenges for the optimal operation of integrated energy systems. According to the basic characteristics of the new power system such as multi-energy complementarity, cleanliness and low carbon, safety and controllability, flexibility and efficiency, and openness and interaction, a day-ahead multi-stage market trading method with dynamic demand-side electricity-carbon dual response is proposed. First, based on the carbon emission flow theory, the carbon emission information of the source side is transmitted to each park, and the refined “electricity-carbon” linkage of the source-network-load in the power system in the differential operation mode is realized. Then, a multifaceted demand-side electricity-carbon-green certificate trading market is built to encourage more subjects to participate in the market, and fully tap the value of the demand side in economic, environmental and other aspects. Finally, a two-layer optimal scheduling model for integrated energy system between the main grid and each park is established. The main grid at the upper layer releases dynamic electricity price and dynamic carbon emission factors, and the parks on the lower-layer demand side generate effective emission reduction schemes, so that the two sides of the source and load form effective interaction, and the integrated energy system as a whole realizes low-carbon economic operation. The simulation results show that on the basis of more accurate characterization of carbon emissions, the proposed strategy can deeply tap the carbon emission reduction potential of the park, improve the accommodation rate of renewable energy, and effectively balance the economy, security and low carbon of the system by improving the demand-side multifaceted trading market.

Abstract:Modeling and simulation abstract real systems and their physical properties into the appropriate mathematical forms and use mathematical methods to solve and simulate the behaviors or performances of the real system. Establishing appropriate mathematical models for the physical processes of the integrated energy system (IES) in various time scales and conducting simulation verification are the basis for analyzing the system operation rules, optimizing operation strategies, and assessing operation performance. Focusing on the modeling and simulation of electricity-gas-heat IESs, this paper first introduces the mechanism models of the electricity, gas, and heating subsystems and coupling units. The research progress and technical difficulties of modeling are then summarized. Furthermore, the research progress of simulation techniques for IESs is described from three key aspects: simulation framework, simulation algorithms, and simulation improvement strategies. In particular, the principle, application status and difficulties of numerical method, semi-analytical method and analytical method in simulation algorithms are summarized. Finally, based on the existing technical difficulties, future research is prospected from two aspects: modeling and simulation algorithms.

Abstract:With the goal of carbon emission peak and carbon neutrality, it is of great significance for energy conservation and emission reduction to design a reasonable carbon trading mechanism so that the source, grid and load can participate in the carbon market together. In this context, a distributed collaborative low-carbon economic dispatching strategy of source, grid and load considering the dual-layer carbon trading mechanism with reward and punishment is proposed. First, a collaborative low-carbon dispatching model of integrated energy suppliers and park under the dual-layer carbon trading mechanism with reward and punishment is established. The integrated energy suppliers directly participate in the external ladder-type carbon trading market with reward and punishment, and the parks indirectly participate in the carbon market by paying carbon fees to integrated energy suppliers or obtaining carbon benefit, thus stimulating all entities to actively participate in energy conservation and emission reduction. Secondly, a ladder-type carbon price model with reward and punishment is established, and a carbon cost/benefit allocation method of integrated energy suppliers and multi-parks under the ladder-type carbon price mechanism with reward and punishment is proposed to ensure the effectiveness and rationality of carbon cost/benefit allocation. Thirdly, the low-carbon dispatching models for the integrated energy suppliers and multi-parks are established, respectively, and the cooperation game between parks is described based on Nash bargaining, so as to reduce carbon emissions and improve social benefits through mutual power exchange among parks. Then, a dual-layer distributed solution for nested alternating direction method of multipliers based on adaptive adjustment mechanism is proposed. Finally, the source-grid-load integrated energy system composed of IEEE 14-bus distribution network and 12-line thermal network is taken as a case to verify the effectiveness of the proposed model and method.

Abstract:Considering the subjectivity in multi-objective optimization for existing integrated energy systems, this paper proposes a multi-objective cooperative optimization method of single entity based on the non-cooperative game theory. First, an integrated electricity-gas system model coupling the distribution network, gas distribution network, and energy station is established. To make the optimization dispatch results closer to reality, a compressor model with variable compression ratio is employed in the model of gas distribution network. Its nonlinear consumption characteristic is considered. Then, based on the non-cooperative game theory, the economic objective and environmental objective of the energy station with a single stakeholder are treated as completely equal and rational virtual gamers. The strategy space is composed of the constraints of various devices in the system. Moreover, to ensure the existence of Nash equilibrium solutions in the game model, auxiliary variables and constraints are used to transform the payoff functions (objective functions) into pseudo-convex and differentiable functions. The method of convex relaxation is applied to handle non-convex and nonlinear constraints in the model, and a non-linear iterative strategy is proposed to accelerate the relaxation tightening process. In order to facilitate the solving of Nash equilibrium, the Nikaido-Isoda function is used to reformulate the payoff function, transforming the original model into a global optimization problem. Finally, the validity of the proposed method is verified by cases.

Abstract:In the collaborative operation of building aggregation and integrated community energy system (ICES), buildings with different insulation performances have differential thermal demand response capabilities. In order to fully mobilize their differential demand response potentials, this paper constructs a collaborative optimization framework of building aggregation and ICES considering the difference in insulation performances. First, based on the thermal storage characteristics of the buildings with heating, a resistor-capacitor network is used to model the thermal dynamic process of heat in the building envelope. Secondly, based on the thermal dynamic model of the building, a model of differential heat demand response is constructed for building users containing adjustable radiators. Then, a collaborative optimization framework based on two-layer optimization of building aggregation and ICES is proposed, and a refined heat supply price scheme that realistically responds to the heat consumption of building users is further adopted in the collaborative optimization framework. Finally, the effectiveness of the proposed method is verified by a case

Abstract:Efficient and accurate state estimation (SE) technology is the key to the safe and stable operation of the integrated electricity-gas system (IEGS). The existing IEGS-SE methods often use the finite difference models to describe the dynamic characteristics of the gas network. The models need to introduce redundant space-time microelements, so it is difficult to take into account SE accuracy and computational complexity. Therefore, a distributed robust IEGS-SE method based on the time-domain model is proposed to improve the computational efficiency while ensuring accuracy. First, the state space model of the gas network with the real node pressure as the state variables is derived based on the time-domain model, realizing the simplification and dimension reduction of the gas network model. On this basis, taking the Kalman filter algorithm as a framework, a distributed IEGS-SE strategy with limited boundary information interaction is proposed to solve the problem of information barriers between multiple management agents in different subsystems. Finally, the noise adaptive algorithm is used to accurately track the time-varying noise parameters and improve the robustness of the proposed method. The simulation case demonstrates that the proposed method can effectively improve the SE accuracy and suppress the influence of bad data under the condition of protecting the privacy of each subsystem, and its computational efficiency is much higher than that of traditional finite difference methods.