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This paper presents an advanced operational framework for large-scale combined heat and power (CHP)-based multi-carrier energy (MCE) networks integrating both electrical and gas energy storage systems (EESS and GESS). A novel coordinated controller is developed to regulate energy flows by managing charging and discharging cycles of storage units while stabilizing electricity and gas supply to CHP units. The operational optimization problem is solved using a parameter-free Teaching-Learning-Based Optimization (TLBO) algorithm, which efficiently minimizes total costs and enhances system flexibility. The proposed approach is validated on a comprehensive testbed comprising the IEEE 14-bus power system, the Belgian natural gas network, and district heating subsystems. Results showed that the presence of EESS reduced the total operation cost of the network by about 0.075%, while the use of GESS increased the operation cost by about 0.024%. Overall, the framework significantly improves operational cost efficiency, energy flow stability, and network resilience compared to existing methods. This work provides valuable insights into the integration and coordinated control of multi-energy storage in CHP-based MCE networks, contributing to the development of more sustainable and flexible energy systems.

The modeling and multi-energy flow calculation of an integrated energy system (IES) are the bases of its operation and planning. This paper establishes the models of various energy sub-systems and the coupling equipment for an electricity-gas-thermal IES, and an integrated multi-energy flow calculation model of the IES is constructed. A simplified calculation method for the compressor model in a natural gas network, one which is not included in a loop and works in constant compression ratio mode, is also proposed based on the concept of model reduction. In addition, a numerical conversion method for dealing with the conflict between nominal value and per unit value in the multi-energy flow calculation of IES is described. A case study is given to verify the correctness and speed of the proposed method, and the electricity-gas-thermal coupling interaction characteristics among sub-systems are studied.

Energy flow in molecules, like the dynamics of other many-dimensional finite systems, involves quantum transport across a dense network of near-resonant states. For molecules in their electronic ground state, the network is ordinarily provided by anharmonic vibrational Fermi resonances. Surface crossing between different electronic states provides another route to chaotic motion and energy redistribution. We show that nonadiabatic coupling between electronic energy surfaces facilitates vibrational energy flow and, conversely, anharmonic vibrational couplings facilitate nonadiabatic electronic state mixing. A generalization of the Logan–Wolynes theory of quantum energy flow in many-dimensional Fermi resonance systems to the two-surface case gives a phase diagram describing the boundary between localized quantum dynamics and global energy flow. We explore these predictions and test them using a model inspired by the problem of electronic excitation energy transfer in the photosynthetic reaction center. Using an explicit numerical solution of the time-dependent Schrödinger equation for this ten-dimensional model, we find quite good agreement with the expectations from the approximate analytical theory.

Cavitation significantly impacts the performance and stability of axial flow pumps, yet the underlying mechanisms driving head rise in the cavitation curve remain inadequately understood. This study provides a novel exploration of internal flow dynamics and energy dissipation in the turning region of the cavitation curve, where head rises. By integrating vortex dynamics and entropy production theory, the intricate interplay between cavitation-induced flow separation and energy loss is revealed. Numerical simulations, validated by experimental data, are employed to analyze energy flow density fluctuations caused by pressure pulsations across different pump regions. The results uncover a critical link between abrupt energy flow density variations and localised high-energy dissipation, which originate from flow separation on the suction side of the impeller blades. Specifically, at the cavitation coefficient where head rise begins, flow separation emerges around the mid-tip region due to cavitation effects at the blade tip and suction surface. As cavitation intensifies and head reaches its peak, the separation zone progressively expands from tip to hub, further amplifying energy dissipation. Beyond this point, excessive cavitation triggers a rapid head drop, shifting the separation zone toward the trailing edge and enhancing the development of the tip separation leakage vortex. This study not only elucidates the physical mechanisms governing head rise under cavitation but also establishes a deeper connection between energy loss and cavitation dynamics, offering valuable insights for optimising axial flow pump performance in cavitating conditions.

With the increase in the proportion of renewable energy and the integration of multiple loads, the uncertainty of the integrated heat and electricity systems (IHESs) has become increasingly prominent. Therefore, it is important to calculate the optimal energy flow while taking into account the uncertainty of IHES. This study proposes an interval optimal electric–heat energy flow solution algorithm based on the holomorphic embedding method (HEM). First, the electric and heat load demands, along with the variable outputs from wind and solar power, are represented in interval forms. Based on HEM, the electric, heat, and coupled unit interval energy flow models are reconstituted into holomorphic series. Second, the analytical expression of the IHES interval energy flow is obtained through recursive solution, resolving the issue of error accumulation and interval expansion. By employing the improved simulated annealing–particle swarm optimization algorithm (SA‐PSO), the optimal set of power series coefficients for the analytical expression of the IHES energy flow is determined. This algorithm combines the global optimization capability of SA with the fast convergence property of PSO, thereby effectively avoiding local optima and enhancing optimization efficiency. Finally, the standard examples of a 51‐node heat network and 14‐node power network are coupled to form an IHES for analysis and calculation. The simulation results show that the proposed method has perfect calculation accuracy and efficiency.

As power to gas (P2G) technology gradually matures, the coupling between electricity networks and natural gas networks should ideally evolve synergistically. With the intent of characterizing market behaviors of integrated electric power and natural gas networks (IPGNs) with P2G facilities, this paper establishes a steady-state model of P2G and constructs optimal dispatch models of an electricity network and a natural gas network separately. In addition, a concept of slack energy flow (SEF) is proposed as a tool for coordinated optimal dispatch between the two networks. To study how the market pricing mechanism affects coordinated optimal dispatch in an IPGN, a market equilibrium-solving model for an IPGN is constructed according to game theory, with a solution based on the Nikaido-Isoda function. Case studies are conducted on a joint model that combines the modified IEEE 118-node electricity network and the Belgian 20-node gas network. The results show that if the game between an electric power company and a natural gas company reaches market equilibrium, not only can both companies maximize their profits, but also the coordinated operation of the coupling units, i.e., gas turbines and P2G facilities, will contribute more to renewable energy utilization and carbon emission reduction.

Local damage (mainly burning, heating, and mechanical wounding) induces propagation of electrical signals, namely, variation potentials, which are important signals during the life of plants that regulate different physiological processes, including photosynthesis. It is known that the variation potential decreases the rate of CO2 assimilation by the Calvin–Benson cycle; however, its influence on light reactions has been poorly investigated. The aim of our work was to investigate the influence of the variation potential on the light energy flow that is absorbed, trapped and dissipated per active reaction centre in photosystem II and on the flow of electrons through the chloroplast electron transport chain. We analysed chlorophyll fluorescence in pea leaves using JIP-test and PAM-fluorometry; we also investigated delayed fluorescence. The electrical signals were registered using extracellular electrodes. We showed that the burning-induced variation potential stimulated a nonphotochemical loss of energy in photosystem II under dark conditions. It was also shown that the variation potential gradually increased the flow of light energy absorbed, trapped and dissipated by photosystem II. These changes were likely caused by an increase in the fraction of absorbed light distributed to photosystem II. In addition, the variation potential induced a transient increase in electron flow through the photosynthetic electron transport chain. Some probable mechanisms for the influence of the variation potential on the light reactions of photosynthesis (including the potential role of intracellular pH decrease) are discussed in the work.

INTRODUCTION: The development of integrated energy systems (IES) is of paramount significance in addressing climate change and other challenges. Ensuring the rapid and accurate calculation of energy flow states is crucial for their efficient operation. However, the difference in response time of various heterogeneous energy flows in IES will lead to the inaccuracy of the steady-state model. OBJECTIVES: This paper proposes a model for multi-stage multi-energy flow IES of electricity, gas, and heat based on heterogeneous energy flow characteristics. Methods: IES was divided into fast variable networks and slow variable networks, and a multi-energy flow multi-stage model was established.  Suitable models were matched for different subnets at different stages to improve the calculation accuracy. RESULTS: Selected a practical Electrical-Gas-Heat IES as a case study for simulation. Through case studies, the effectiveness and accuracy of the proposed method are demonstrated. CONCLUSION: The multi-stage model proposed in this paper can improve the accuracy of multi-energy flow in IES.

The smart grid technology permits the revolution of the electrical system from a conventional power grid to an intelligent power network which has led the improvements in electrical system in terms of energy efficiency and sustainable energy integration. This study presents the energy management/coordination scheme for domestic demand using the key strategy of smart grid energy efficiency modelling. The structure consists of combining renewable energy resources, photovoltaic (PV) and wind power generation connected to the utility grid with energy storage system (ESS) in an optimal control manner to coordinate the power flow of a residential home. Based on the demand response schemes in the framework of real-time electricity pricing, this work designs a closed-loop optimal control strategy that is created by the dynamic model of the ESS to compute the system performance index, which is formulated by the cost of the energy flows. A dynamic distributed energy storage strategy (DDESS) is implemented to optimally coordinate the energy system, which reduces the total energy consumption from the main grid of more than 100% of the load demand. The designed model introduces a payback scheme while robustly optimising the energy flows and minimising the utility grid's energy consumption cost.

China plays a critical role in global carbon reduction in the context of mitigating climate change as the essence of climate change and the associated environmental issues is energy consumption, especially the combustion of fossil fuels. This paper provides a clear picture of China’s energy consumption in the past, present and future to facilitate the understanding of what has happened, the main cause and what is likely coming. First, an extended energy flow chart is presented based on the adjusted energy balance table for China, and the detailed energy chains of final services, subsectors and the corresponding technologies are linked to the chart. This work enriches the information about sources of energy demand and contributes to the identification of key areas that should be given priority for energy transitions and technological innovations. Second, three development modes describing the relationship between energy consumption and GDP per capita are proposed based on the experiences of developed countries, and it is noted that China’s trajectory is more likely to follow the medium or low energy consumption modes. Finally, the future energy demand of China is projected in a more comprehensive and precise manner by summarizing and comparing the results of outlook reports published by well-known international organizations. The overall trend is that China’s energy consumption will continue to grow, while the growth rate will gradually slow.