Energy Network Flow Model and Optimization Based on Energy Hub for Big Harbor Industrial Park

Xia, Tian; Zhao, Rongyong

doi:10.2112/si73-052.1

Cited by 18 publications

(6 citation statements)

References 18 publications

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“…At present, according to the number of research targets, the energy hub optimization operation can be divided into two types: single energy hub optimization operation and coordinated optimization operation of multiple energy hubs [29,30,35,36]. There have been a lot of literatures on the optimization of single energy hub operations.…”

Section: Optimization Operation Of Energy Hubsmentioning

confidence: 99%

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A Real-Time Rolling Horizon Chance Constrained Optimization Model for Energy Hub Scheduling

Hou

Liu

Ма

et al. 2020

Sustainable Cities and Society

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With the increasing consumption of energy, it is of high significance to improve energy efficiency and realize optimal operation of the multi-energy system. Among the many energy system modeling methods, the concept of "energy hub (EH)" is an emerging one. However, the previous EH models only included one or a few of constituting components. The construction of an energy hub model that integrates energy storage systems, photovoltaic (PV) components, a combined cooling heating and power (CCHP) system and electric vehicles (EVs) is explained in this thesis. The inclusion of the CCHP system helps to meet the energy demand and improve the mismatch of heat-to-electric ratio between the energy hub and the load. Additionally, vehicle-to-grid (V2G) technology is applied in this EH; that is, EVs are regarded not only as load demands but also as power suppliers. The energy hub optimization scheduling problem is formulated as a multi-period stochastic problem with the minimum total energy cost as the objective. Compared to 24-hour day-ahead scheduling, rolling horizon optimization is used in the EH scheduling and shows its superiority. In iii real-time rolling horizon scheduling, the optimization principle ensured that the result is optimized each moment, so it avoids energy waste caused by overbuying energy. As part of electricity loads, EVs have certain influence on energy hub scheduling. However, due to the randomness of the driving patterns, it is still very difficult to perfectly predict the driving consumption and the charging availability of the EVs one day in advance. Chance constrained programming can hedge the risk of uncertainty for a big probability and drop the extreme case with a very low probability. By restricting the probability of chance constraints over a specific level, the influence of the uncertainty of electric vehicle charging behavior on energy hub scheduling can be reduced. Simulation results show that the energy hub optimization scheduling with chance constrained programming results in a less energy cost and it can make better use of time-varying PV energy as well as the peak-to-valley electricity price.

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Section: Optimization Operation Of Energy Hubsmentioning

confidence: 99%

“…The energy hub has a high degree of flexibility in modeling the multi-energy system, and the entire system is often modeled and analyzed using multiple energy hubs [35][36]. residential users, commercial buildings, factories [30], and as large to countries.…”

Section: Optimization Operation Of Energy Hubsmentioning

confidence: 99%

A Real-Time Rolling Horizon Chance Constrained Optimization Model for Energy Hub Scheduling

Hou

Liu

Ма

et al. 2020

Sustainable Cities and Society

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“…This model considered the environmental effects of water use, energy consumption, and capital goods within an industrial park in a balanced approach. Tian and Zhao [17] developed an energy network flow model based on the energy hub concept model to model and optimize the energy network flow for the energy conservation and emission reduction in the Big Harbor Industrial Park. Environment-focused models usually provide technical supports for resource saving and environmental friendship.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation of the Performance Optimization of Harbin Yingbin Industrial Park in China

Liu¹,

Wu²,

Liu³

2016

Int. j. simul. model.

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An effective performance optimization of industrial parks is urgently needed because of the importance of these parks. To develop a model to optimize the performance of industrial parks from the comprehensive perspectives of economy, society, and environment, the member assessment model was initially constructed to evaluate the comprehensive performance of enterprises. Then the assembly line balance (ALB) model and the mixed integer linear programming (MILP) method were integrated to construct a model (MILP-ALB) for evaluating the optimized comprehensive performance of an industrial park. This model was applied to Yingbin Industrial Park in Harbin, China. Simulation results indicate that the comprehensive performance of enterprises and their interactions determine the comprehensive performance of the industrial park. Results also demonstrate that the MILP-ALB model is applicable in evaluating the optimized comprehensive performance of the industrial park. Furthermore, the model can reveal the effects of the newly introduced enterprise on the optimized performance. Given these results, the model is a useful tool for performance optimization.

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“…In [9], Setlhaolo et al present a residential energy hub model for a smart home as a modified framework of conventional energy hubs in a smart grid with consideration of heat pump water heater, coordination of sources, and carbon emission. Lingang Industrial Park is an engineering example [12], whose results provide a technical support for the construction of a resource-saving and environmentfriendly harbour. In [13], a residential building and its electrical equipment are modelled as an energy hub system, including washing machine, dryer, HVAC system, refrigerator, and lighting equipment, to minimize energy cost, carbon emission, and peak load for optimal scheduling under the premise of maintaining the comfort of the users.…”

Section: Introductionmentioning

confidence: 99%

An Advanced Multicarrier Residential Energy Hub System Based on Mixed Integer Linear Programming

Yuan

Bayod-Rújula

Chen

et al. 2019

International Journal of Photoenergy

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This work proposes a multicarrier energy hub system with the objective of minimizing the economy cost and the CO2 emissions of a residential building without sacrificing the household comfort and increasing the exploitation of renewable energy in daily life. The energy hub combines the electrical grid and natural gas network, a gas boiler, a heat pump, a photovoltaic plant, and a photovoltaic/thermal (PV/T) system. In addition, to increase the overall performance of the system, a battery-based energy storage system is integrated. To evaluate the optimal capacity of each energy hub component, an optimization scheduling process and the optimization problem have been solved with the YALMIP platform in the MATLAB environment. The result showed that this advanced system not only can decrease the economic cost and CO2 emissions but also reduce the impact to electrical grid.

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Energy Network Flow Model and Optimization Based on Energy Hub for Big Harbor Industrial Park

Cited by 18 publications

References 18 publications

A Real-Time Rolling Horizon Chance Constrained Optimization Model for Energy Hub Scheduling

A Real-Time Rolling Horizon Chance Constrained Optimization Model for Energy Hub Scheduling

Simulation of the Performance Optimization of Harbin Yingbin Industrial Park in China

An Advanced Multicarrier Residential Energy Hub System Based on Mixed Integer Linear Programming

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