Multi-objective planning for integrated energy systems considering both exergy efficiency and economy

Hu, Xiao; Zhang, Heng; Chen, Dongwen; Li, Yong; Wang, Li; Zhang, Feng; Cheng, Haozhong

doi:10.1016/j.energy.2020.117155

Cited by 92 publications

(38 citation statements)

References 36 publications

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“…We choose practical values C prb ∈ [0.8, 1], the default value is one. The constant 60 is a generated point to control w max in range [10,50]. From on the Q t value, we will calculate the value of w max ∈ R (the rate of using surrogate function and the frequency of updating the Kriging model) in the range, a normalize function is defined to adjust valid w max values.…”

Section: An Adaptive Controlmentioning

confidence: 99%

“…The authors in [10] proposed a black-box model to calculate the energy efficiency of an integrated energy system, after defining the energy quality coefficient, which values the quality of various energy forms. A multi-objective planning model that considered energy efficiency and the economy was proposed for the joint planning of energy generators, storage, and networks.…”

Section: Introductionmentioning

confidence: 99%

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A Surrogate Assisted Multi-objective Approach to Social Work Planning

Nguyen¹,

Nguyen²,

Nguyen³

et al. 2021

Preprint

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Planning social tasks are essential jobs of every organization, business, and government. With increasing challenges of society, the organization and effective implementation depend on optimizing the plans of the organization and efficient operations of the professional teams in order, time, and specific requirements. In the context of the impact of the COVID-19 pandemic on social activities, developing strategies for the organization and operation of working teams in implementing disease prevention, control, and elimination are research issues that should be raised. This paper model the plan to organize and operate the social-mission working group problem with a multi-objective approach. The problem includes organizing and planning the health workforce to perform tasks in epidemic prevention and implementing guidelines of the Ministry of Health under the administration of the government. These pose a requirement to balance resources, medical equipment, and ancillary equipment to perform tasks according to different priority levels: disease prevention; vaccination; sterilization, isolation, treatment by different locations, and time to ensure effectiveness. The problem is modeled by approaching the multi-objective optimization with three objectives: makespan, performance efficiency, and rate of human resource usage. We also propose a guidance technique to improve the surrogate-assisted multi-objective optimization algorithms on analyzing the factors that influence finding solutions and maintain a balance between local exploration and global exploitation. The enhanced algorithms confirm the proposed model for social tasks against the COVID-19 pandemic.

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Section: An Adaptive Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Surrogate Assisted Multi-objective Approach to Social Work Planning

Nguyen¹,

Nguyen²,

Nguyen³

et al. 2021

Preprint

View full text Add to dashboard Cite

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“…Improving the utilization rate of energy has always been the core objective of optimization. Hu et al [6] used the energy quality coefficient (which measures the quality of various forms of energy) to evaluate energy. The multi-objective programming model-with energy efficiency and economy as its objectives-was established.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization and Performance Assessments of an Integrated Energy System Based on Fuel, Wind and Solar Energies

Zhao

2021

Entropy

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The integrated energy system (IES) is an efficient method for improving the utilization of renewable energy. This paper proposes an IES based on fuel, wind and solar energies, following an optimization study focused on determining optimal device capacities. The study included gas turbines, wind turbines, solar photovoltaic panels, ground source heat pumps, absorption chillers/heaters, batteries, and thermal storage. Objectives were incorporated into the optimization model for the overall performance of the IES; these included the primary energy saving rate, annual cost-saving rate, and carbon dioxide emission reduction. Then, the nondominated sorting genetic algorithm II was employed to solve the optimization problem for multiple objectives. Ultimately, the verification and sensitivity analyses of the optimization method were achieved by a case study of hospital buildings in Harbin. The optimization results indicated a primary energy saving rate, annual cost saving rate, and carbon dioxide emission reduction rate of 17.3%, 39.8%, and 53.8%, respectively. The total installed capacity for renewable energy generation accounted for 64.5% of performance optimization. Moreover, the price of natural gas affected the economic indicators of the IES–but failed to impact energy consumption indicators.

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“…Some references further consider the uncertainty of the system, and use robust and multi-scenario methods for planning [15]. Additionally, the IES can provide users with multiple energy through energy coupling and cascade utilization [8,9], reduce environmental pollution [8], improve energy efficiency [9], and improve energy supply reliability. The first three effects can be reflected in the planning through the objective function [8,9].…”

Section: Introductionmentioning

confidence: 99%

Optimal device capacity planning and strategy determination in an integrated energy system to promoting IES integration considering reliability value

Xueqian

Liu

2021

IET Generation Trans & Dist

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This paper proposes a novel framework for optimal planning of integrated energy system (IES) that takes into account its reliability value, which aims at promoting the power grid and IES to share the responsibility of the user's energy-supply reliability by market mechanism, thus promoting IES integration. First, an IES grid-connected electricity purchase price estimation model considering reliability is established, based on price theory and reliability theory, to quantify the reliability incremental value of IES. Then, a two-layer collaborative planning model, containing optimal equipment capacity configuration and strategy determination in the upper layer and optimal operation simulation and IES incremental reliability value in the lower layer, is established to coordinate the reliability guarantee capability of distribution network and IES while maximize the profit of IES. Among them, a practical approach of IES probabilistic reliability calculation is studied, considering double uncertainty and time-series matching of generation and demand, aiming at reducing the complexity of electricity price calculation embedded in planning model. Next, the intelligent krill herd algorithm and MILP are implemented to solve the model. Finally, a case is studied to verify the effectiveness of the model, and analyse the impact of load growth rate and user reliability requirements on the planning results.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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Multi-objective planning for integrated energy systems considering both exergy efficiency and economy

Cited by 92 publications

References 36 publications

A Surrogate Assisted Multi-objective Approach to Social Work Planning

A Surrogate Assisted Multi-objective Approach to Social Work Planning

Multi-Objective Optimization and Performance Assessments of an Integrated Energy System Based on Fuel, Wind and Solar Energies

Optimal device capacity planning and strategy determination in an integrated energy system to promoting IES integration considering reliability value

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