Optimization of Distributed Integrated Multi-energy System Considering Industrial Process Based on Energy Hub

Zhang, Yizhi; Wang, Xiaojun; He, Jinghan; Xu, Yin; Pei, Wei

doi:10.35833/mpce.2020.000260

Cited by 28 publications

(8 citation statements)

References 23 publications

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“…The topologies of the two subsystems are depicted in Figures 3 and 4. Three EHs were connected to electric buses 3,4,5,10,12,16,20,26, and 29 in the electrical system and the natural gas nodes 2, 8, 10, 13, 14, 19, 21, 31, and 40 in the natural gas system. The coupling relationship inside the IES is shown in Figure 5.…”

Section: System Descriptionmentioning

confidence: 99%

“…The modeling of the energy hub (EH) and its internal components is one of the key points in current research on day-ahead optimal energy flow. In [5], taking the industrial production process (IPP) as a control variable of optimal scheduling, a universal extension EH model was proposed. The results demonstrate that such a method reduces the operation cost.…”

Section: Introductionmentioning

confidence: 99%

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Day-Ahead Optimal Scheduling of an Integrated Energy System Based on a Piecewise Self-Adaptive Particle Swarm Optimization Algorithm

et al. 2022

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The interdependency of electric and natural gas systems is becoming stronger. The challenge of how to meet various energy demands in an integrated energy system (IES) with minimal cost has drawn considerable attention. The optimal scheduling of IESs is an ideal method to solve this problem. In this study, a day-ahead optimal scheduling model for IES that included an electrical system, a natural gas system, and an energy hub (EH), was established. The proposed EH contained detailed models of the fuel cell (FC) and power to gas (P2G) system. Considering that the optimal scheduling of an IES is a non-convex complex optimal problem, a piecewise self-adaptive particle swarm optimization (PCAPSO) algorithm based on multistage chaotic mapping was proposed to solve it. The objective was to minimize the operating cost of the IES. Three operation scenarios were designed to analyze the operation characteristics of the system under different coupling conditions. The simulation results showed that the PCAPSO algorithm improved the convergence rate and stability compared to the original PSO. An analysis of the results demonstrated the economics of an IES with the proposed EHs and the advantage of cooperation between the FC and P2G system.

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Section: System Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Day-Ahead Optimal Scheduling of an Integrated Energy System Based on a Piecewise Self-Adaptive Particle Swarm Optimization Algorithm

et al. 2022

View full text Add to dashboard Cite

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“…Industrial parks have complex production constraints, and the types of energy required for different production links are also distinct. There is a corresponding coupling relationship between the industrial production process and the IES [31]. Power plants supply electricity, natural gas and heat energy to various types of loads, and the energy conversion process mostly involves the cascade utilization of heat [32].…”

Section: Necessity Analysis Of Iess Constructionmentioning

confidence: 99%

Architecture and function analysis of integrated energy service stations considering cyber‐physical integration

Liu

Wang

Tang

2021

Energy Conversion and Econom

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With the continuing development of the energy internet (EI), the high complexity of multienergy coupling and the dramatic increase in cyber-physical integration impose stricter requirements on the planning and construction of multi-energy systems. The construction of a new energy hub through the intensive use of existing power substation resources is one of the feasible approaches for satisfying these requirements. Integrated energy service stations (IESSs), which comprise substations, multi-energy conversion stations, data centres, communication base stations, and other functional units, constitute the emerging generation of energy and information control centres. IESSs are capable of all-in-one monitoring and energy optimization, and can effectively manage regional energy services involving various energy requirements. This study initially proposes two feasible schemes to realize IESSs: entity IESSs, which require replanning and construction, and virtual IESSs, which involve transformation through existing substation resources. Thereafter, based on the requirements of three types of users, that is high-energy-consumption users, highreliability users, and high-comfort users, the necessity of IESSs in the construction of the EI is analysed in depth. Furthermore, the feasibility of constructing an IESS based on existing power grid resources and the direction for the future development are discussed.

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“…To put forward a novel optimal scheduling method, an extension energy hub (EH) model considering the industrial production process was formulated in Ref. [7]. The method can improve the energy efficiency and reduce the cost of industrial park DIMS.…”

Section: Introductionmentioning

confidence: 99%

An online dispatch approach for distributed integrated multi‐energy system considering non‐ideal communication conditions

Wang

et al. 2022

IET Energy Syst Integration

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The distributed integrated multi-energy system (DIMS) has many advantages in terms of the utilisation of renewable energy sources and clean energy. Operation strategies for the DIMS based on a real-time profile have been extensively studied. In a DIMS online optimisation problem, besides fluctuations in the renewable energy output and load, inconsistent time scales of the transport dynamics of different energy flows and non-ideal communication (involving communication uncertainty and latency) result in suboptimal operation in dispatch scheduling. An online multi-time-scale optimal operation strategy is proposed for the DIMS to respond to the above challenges, using a hybrid algorithm comprising a model predictive control method and distributed collaborative consensus algorithm (CCA). The approach is based on a hierarchy, comprising rolling optimisation and adjustment. A rolling optimisation is established to schedule operations according to the latest forecast and status information. The rolling dispatch is then adjusted according to the ultrashort-term adjustment using the CCA. Meanwhile, the effect of the information transmission environment on real-time scheduling is considered, and the robust CCA is improved for the implementation of strategies under non-ideal communication conditions. Case studies and results are presented and discussed to show the effectiveness of the proposed approach with the better matching between demand and supply. K E Y W O R D S distributed integrated multi-energy system, model predictive control, multi-time-scale, non-ideal communication, robust collaborative consensus algorithm This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Optimization of Distributed Integrated Multi-energy System Considering Industrial Process Based on Energy Hub

Cited by 28 publications

References 23 publications

Day-Ahead Optimal Scheduling of an Integrated Energy System Based on a Piecewise Self-Adaptive Particle Swarm Optimization Algorithm

Day-Ahead Optimal Scheduling of an Integrated Energy System Based on a Piecewise Self-Adaptive Particle Swarm Optimization Algorithm

Architecture and function analysis of integrated energy service stations considering cyber‐physical integration

An online dispatch approach for distributed integrated multi‐energy system considering non‐ideal communication conditions

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