Energy-Circuit-Based Integrated Energy Management System: Theory, Implementation, and Application

As renewable energy increasingly penetrates into electricity-heat integrated energy system (IES), the severe challenges arise for system reliability under uncertain generations. A two-stage approach consisting of pre-scheduling and re-dispatching coordination is introduced for IES under wind power uncertainty. In pre-scheduling coordination framework, with the forecasted wind power, the robust and economic generations and reserves are optimized. In re-dispatching, the coordination of electric generators and combined heat and power (CHP) unit, constrained by the pre-scheduled results, are implemented to absorb the uncertain wind power prediction error. The dynamics of building and heat network is modeled to characterize their inherent thermal storage capability, being utilized in enhancing the flexibility and improving the economics of IES operation; accordingly, the multi-timescale of heating and electric networks is considered in pre-scheduling and re-dispatching coordination. In simulations, it is shown that the approach could improve the economics and robustness of IES under wind power uncertainty by taking advantage of thermal storage properties of building and heat network, and the reserves of electricity and heat are discussed when generators have different inertia constants and ramping rates.

A novel analytical unified energy flow calculation method for integrated energy systems based on holomorphic embedding

Gas turbine is the core energy equipment of integrated energy system (IES), whose installation scheme not only influences the installed capacity of other energy equipment, but also directly affects the operation strategy of IES. Thus, this paper aims at the existing problems that only focus on the system installed capacity and ignore the gas turbine installation scheme when optimizing the operation strategy of IES, and proposes a planning method for IES based on gas turbine installed capacity optimization as well as establishes the optimization model of IES. The natural gas consumption coefficient and heat generation coefficient are introduced into the model to separate variables and simplify the variable efficiency characteristics of gas turbine. Meanwhile, the matching coefficient is also lead-in to obtain the installation scheme including installed number and installed capacity of gas turbine. Besides, taking the operating load rate of energy equipment as decision variables and under the constrict of energy balance, the optimal operation strategy of IES and the installation scheme of both gas turbine and non-gas turbine equipment can all be obtained with total cost, energy efficiency and carbon emission of IES as objective functions. Meanwhile, an industrial park is selected as a research case in this paper to verify the effectiveness of the method proposed in this paper. It is proved that the proposed method can collaboratively optimize the installation scheme of each energy equipment in IES, and provide theoretical reference for the planning and design of IES and its economic, efficient and low-carbon operation.

The integrated energy system emphasizes the synergy between multiple energy sources compared with the traditional distributed energy subsystem. At present, the research on integrated energy systems is mostly the optimization research of single independent systems, which fails to give full play to the advantages of integrated energy systems. Since the mutual coupling between the electro-gas-thermal networks makes the multi-region integrated energy system optimization operation more complicated, the current research is still immature and needs further research. This paper firstly models the energy storage (storage, heat storage, gas storage) equipment and energy coupling equipment in the integrated energy system. Secondly, it establishes the objective function that considers the minimum system cost and establishes the power of the grid, and give the constraints of power balance equation and line loss equation of power grid, heat network and gas network; Finally, the simulation results show that after the grid, the heat network and the gas network are combined, the original distribution system is converted into a joint supply system through the grid, the heat network and the gas network, which improves the overall economy.

An optimal scheduling model that can integrate the power, heat and gas networks considering the gas linepack and the thermal inertia of heating system is proposed here. By coupling the characteristics of various energy flows, the flexibility and reliability of system operation can be improved without further investment on the storage equipment. First, the storage capacity of the gas pipeline, the process of thermal system transmission and the heat storage capability at the consumer side are analysed and modelled. The associated gas linepack model, heat system thermal inertia model and primary electricity‐gas‐heat model are subsequently combined and simplified through incremental linearization to establish an optimal scheduling model that can be applied for the Integrated Energy System (IES) based on the characteristics of thermal inertia and gas linepack. Case studies are conducted to assess the potential of optimizing the two energy flows using the proposed optimal scheduling method and the results indicate that the IES can significantly enhance the system capability to accommodate excessive renewable energy and maintain reliable operation during peak hours.

Guest Editorial: Situational awareness of integrated energy systems

Energy flow calculation of IES (integrated energy system) aims to calculate the node voltage and pressure, branch current and mass flow rate, working medium temperature and other state parameters according to known information. In the existing researches on energy flow calculation, only the friction head loss is considered and the influence of local head loss is not involved because of the complexity of the pipe structure. The local head loss occurring at abrupt flow boundary changes, such as variable section pipes, pipe inlet and outlet, and pipe connections is inevitable. The output of units and energy flow distribution in the IES will be affected by energy consumption caused by local head loss, so it is necessary to calculate the energy flow with local head loss in mind. In this paper, a local head loss energy model at pipe connection is first established, then a solution model for the energy flow of the electricity-heat IES with local head loss model is established, and the model can be solved by N-R method. Finally, the effectiveness of the model and the influence of local head loss on the whole system are verified through case comparison. The result shows that energy loss caused by local head loss should be avoided although it's a small amount of energy for the whole system.

While proposing dual carbon strategy goals, research on carbon reduction in integrated energy systems (IESs) has become a focus of attention. Traditional IES carbon emission flow is mostly based on energy flow, without considering the differences in energy quality. Exergy can be used as a reasonable measure of energy quality. Combining the theory of exergy flow and carbon emission flow, a modeling and analysis method for IES carbon emission flow considering energy quality is proposed. First, exergy flow models for electric and natural gas systems, equivalent exergy flow models for heat systems, and exergy hub models are introduced. Afterward, the exergy branch losses are allocated to the nodes at both ends. A networked modeling method for the carbon emission flow of energy stations is proposed. A unified matrix calculation model for IES carbon emission flow considering energy quality is established. On this basis, an IES carbon emission flow calculation method considering energy quality is proposed. Finally, this method is applied to the test IES, and the results show that the carbon emission flow calculation results reflect the distribution of carbon emissions borne by the effective energy supplied by the source and consumed by the load in the system, taking into account both the quantity and quality of energy. The reasonable allocation of new energy is conducive to synchronously improving the energy efficiency, exergy efficiency, and cleanliness of the system.

This paper focuses on the joint optimization scheduling of multi-region integrated energy systems (IES) and the influence of regional heating networks on joint scheduling. The IES model is firstly established, including the heating network model and the internal equipment model. Then, in order to ensure the independence of each IES, a bi-level model of multi-region IESs joint scheduling considering regional heating network is established, which is solved by distributed algorithm-analysis target cascading method (ATC). Finally, the simulation results show that the proposed model can effectively optimize the energy scheduling between IESs while ensuring the independence of each IES. The regional heating network can be used as heat storage equipment to participate in the joint scheduling, and absorbs the excess heat energy in IES that cannot be transferred to other IESs.

Integrated energy system (IES) can realize the comprehensive utilization of different energy sources and contribute to energy efficiency and flexibility, which is helpful for reducing environmental pressure. However, the energy flow calculation becomes very complicated due to the coupling relationship of different energy systems in IES. When conducting security assessment, all accident scenarios in a contingency accident set need to be investigated until the accident set is empty. Therefore, the calculation speed of a single accident scenario and the number of accident scenarios in the accident set significantly determine the whole security assessment time. To achieve real-time security assessment, the concept of load cut set is defined based on the graph theory to reduce the accident number in an accident set. Moreover, a method of network equivalence is proposed to reduce the computation time of a single accident scenario.

An evaluation framework for future integrated energy systems: A whole energy systems approach

The emergence of the Integrated energy system (IES) reflects the trend of the energy supply systems, which is conductive to achieving sustainable development. Dynamic simulation can be regarded as a digital twin of the IES, and is applied to generate data and simulate the operations, etc. Thus, it is a significantly meaningful work to implement related studies. In this paper, considering the multi-time scale characteristics of energy categories in the IES, a cooperative dynamic simulation framework based on multiple platforms is proposed, where APROS is applied for the slow-time scale simulation while RT-Lab is for the fast-time one, and the multiple platforms communicate with each other via OPC UA protocol. Under this framework, a dynamic simulation application case of an industrial IES, involving gas, heat and power networks, is studied. Furthermore, an operation strategy optimization is conducted from the aspects of economy, efficiency and environment for a typical winter energy supply scenario for taking the time-of-use energy prices and integrating renewable energy. The experimental results demonstrate that the framework proposed in this study is effective, which can provide technical support for IES researches.

Seismic events can severely damage both electricity and natural gas systems, causing devastating consequences. Ensuring the secure and reliable operation of the integrated energy system (IES) is of high importance to avoid potential damage to the infrastructure and reduce economic losses. This article proposes a new optimal two-stage optimization to enhance the reliability of IES planning and operation against seismic attacks. In the first stage, hardening investment on the IES is conducted, featuring preventive measures for seismic attacks. The second stage minimizes the expected operation cost of emergency response. The random seismic attack is modeled as uncertainty, which is realized after the first stage. An explicit damage assessment model is developed to define the budget set of the uncertain seismic activity. Based on the survivability of transmission lines and gas pipelines of IES, an optimal system investment plan is developed. The problem is formulated as a two-stage distributionally robust optimization (DRO) model, which is tested on an integrated IEEE 30-bus system and 20-node gas network. Case studies demonstrate that the two-stage DRO outperforms robust optimization and a single-stage optimization model in terms of minimizing the investment cost and expected economic loss. This article can help system operators to make economical hardening and operation strategies to improve the reliability of IES under seismic attacks, thus managing a more robust and secure energy system.

Integrated Energy Systems (IES), which leverage the synergistic coordination of electricity, heat, and gas networks, serve as crucial enablers for a low-carbon transition. Current research predominantly treats energy storage as a subordinate resource in dispatch schemes, failing to simultaneously optimise IES economic efficiency and storage operators' profit maximisation, thereby overlooking their potential value as independent market entities. To address these limitations, this study establishes an operator-autonomous management framework incorporating electrical, thermal, and hydrogen storage in IES. We propose a joint optimal dispatch model for hybrid energy storage systems in low-carbon IES operation. The upper-level model minimises total system operation costs for IES operators, while the lower-level model maximises net profits for independent storage operators managing various storage assets. These two levels are interconnected through power, price, and carbon signals. The effectiveness of the proposed model is verified by setting up multiple scenarios for example analysis.

As the coupling and integration of multi-energy flow in the integrated energy system (IES) deepen increasingly, the cascading failure will develop across different energy systems more easily and widely through the energy hub (EH). And it brings great challenges to the security and reliability of IES. The defects of the present cascading failure model of IES have been summarized, and a novel search strategy of fault chains in IES combined heating and power network was proposed in this paper. First, the initial risk assessment index of each energy branch is proposed to form the initial fault sets. Then, combined heat and power control (CHPC) strategies are introduced to deal with the branch overload conditions during the cascading failure. What is more, in order to reduce the workload and overcome the limitation of present methods, we analyzed the relevance of the branches to be predicted by using the kernel fuzzy C-means (KFCM) clustering algorithm and select the branches with the highest value of relevance as the subsequent failure. Based on the predicted fault chain, vulnerability analysis is presented to locate critical component and find out the correlation between cascading outages. The comprehensive evaluation index is also established to effectively evaluate the impact severity of cascading failure. Finally, the case studies are carried out on the combined heating and power systems to demonstrate the effectiveness of the proposed method.