Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach

Feng, Wei; Wu, Q. H.; Jing, Zhaoxia; Chen, J.J.; Zhou, Xiaoxin

doi:10.1016/j.energy.2016.05.046

Cited by 61 publications

(27 citation statements)

References 41 publications

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“…Jung et al [20] observed the performance of a DES system with renewable energy. Wei et al [21] analyzed the performance of primary component capacities in DES and optimized the unit size using multiobjective interval optimization and evidential reasoning approaches. Mehleri et al [22] presented an optimal design and operation of DESs, which were applied to a Greek residential sector.…”

Section: Introductionmentioning

confidence: 99%

Performance Comparison of a Distributed Energy System under Different Control Strategies with a Conventional Energy System

2019

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The distributed energy system (DES) has increasingly attracted considerable attention from researchers due to its environmental friendliness and high efficiency. In the hot summer and cold winter areas, DES is an efficient alternative for district cooling and heating. A case study located in Changsha, China, which is a typical hot summer and cold winter area, is analyzed. Four control strategies are proposed in this study. The four cases under different control strategies are compared in terms of energy, economy, environment, solar fraction, and soil annual heat imbalance rate. Results show that the DES can be an energy saving and environmentally friendly alternative. The primary energy saving (PES) is more than 36.70% and can reach up to 48.04%, whereas DES can realize economical operation and reduce the emission of carbon dioxide, sulphur dioxide, and dust. In addition, DES consumes more electricity and less natural gas than the conventional energy system. These features are beneficial to the optimization of China’s energy consumption structure. Moreover, the operation of seasonal thermal storage for the ground soil is effective in maintaining the balance of soil annual heat. The control strategy combining geothermal and solar energies is recommended due to its good performance and high flexibility. This study may provide guidance in the development of DESs in hot summer and cold winter climate zones.

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Section: Introductionmentioning

confidence: 99%

Performance Comparison of a Distributed Energy System under Different Control Strategies with a Conventional Energy System

2019

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“…The concept of ESI is proposed as a new umbrella concept that encompasses activities occurring in the environment of smart grids. Small-scale integrated energy systems are microenergy systems comprising distributed generation units, renewable energy sources, energy coupling technologies, and energy end users, possibly with energy storage devices, which are deployed across a limited geographic area [2]. A microenergy system enables interactions between different energy vectors, such as electric, thermal, and gas [3].…”

Section: Introductionmentioning

confidence: 99%

Modeling the Operation of Small‐Scale Integrated Energy Systems Based on Data‐Driven Robust Optimization

Han

Yang

Sun

et al. 2019

IEEJ Transactions Elec Engng

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To facilitate energy system integration, it is imperative that a multienergy system produce and deliver in a coordinated way the energy in its different component forms. In particular, a small-scale integrated energy system must accommodate renewable energy resources, flexible loads, and energy coupling technologies, which creates new challenges to the interactions between the energy vectors. Hence, an energy management model for a microenergy system in grid-connected mode under uncertainties is proposed to perform the decision-making for shifting energy modes for all energy sources and end-use applications with the aim of optimally scheduling controllable energy resources in the system and minimizing the net management cost under uncertainty. To address the stochastic nature of the price of electricity, a data-driven robust optimization approach is introduced. It uses the available sample data to design the appropriate uncertainty set using statistical hypothesis tests, and a combination of conditional value-at-risk and a worst-case optimization problem is used to formulate the energy management problem under uncertainty. We explore a computationally tractable robust counterpart of the original optimization problem. The optimal energy scheduling solution obtained from the proposed approach is immune against any worst-case realizations. Numerical results demonstrate the effectiveness of the proposed approach and its performance of less conservation.

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“…Fabio et al [1] proposed the use of design optimization techniques to find the ideal truncated full-scale design considering the dynamic effects. Wei et al [2] proposed a comprehensive framework including a multiobjective interval optimization model and evidential reasoning approach to solve the unit-sizing problem of small-scale integrated energy systems. Lei et al [3] built a constrained multiphysics model of a motor wheel for an electric vehicle and then optimized it.…”

Section: Related Workmentioning

confidence: 99%

A Systematic Optimization Design Method for Complex Mechatronic Products Design and Development

Jiang

Ding

Zhang

et al. 2018

Mathematical Problems in Engineering

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Designing a complex mechatronic product involves multiple design variables, objectives, constraints, and evaluation criteria as well as their nonlinearly coupled relationships. The design space can be very big consisting of many functional design parameters, structural design parameters, and behavioral design (or running performances) parameters. Given a big design space and inexplicit relations among them, how to design a product optimally in an optimization design process is a challenging research problem. In this paper, we propose a systematic optimization design method based on design space reduction and surrogate modelling techniques. This method firstly identifies key design parameters from a very big design space to reduce the design space, secondly uses the identified key design parameters to establish a system surrogate model based on data-driven modelling principles for optimization design, and thirdly utilizes the multiobjective optimization techniques to achieve an optimal design of a product in the reduced design space. This method has been tested with a high-speed train design. With comparison to others, the research results show that this method is practical and useful for optimally designing complex mechatronic products.

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Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach

Cited by 61 publications

References 41 publications

Performance Comparison of a Distributed Energy System under Different Control Strategies with a Conventional Energy System

Performance Comparison of a Distributed Energy System under Different Control Strategies with a Conventional Energy System

Modeling the Operation of Small‐Scale Integrated Energy Systems Based on Data‐Driven Robust Optimization

A Systematic Optimization Design Method for Complex Mechatronic Products Design and Development

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