Regional integrated energy system energy management in an industrial park considering energy stepped utilization

Energy ◽  
2020 ◽  
Vol 201 ◽  
pp. 117589 ◽  
Author(s):  
Xu Zhu ◽  
Jun Yang ◽  
Xueli Pan ◽  
Gaojunjie Li ◽  
Yingqing Rao
Keyword(s):  
Energy Management ◽  
Energy System ◽  
Industrial Park ◽  
Integrated Energy System ◽  
System Energy

scholarly journals Evaluation and Selection of Integrated Energy System Construction Scheme Equipped with Smart Energy Management and Control Platform Using Single-Valued Neutrosophic Numbers

2021 ◽  
Vol 13 (5) ◽  
pp. 2615
Author(s):  
Junqing Wang ◽  
Wenhui Zhao ◽  
Lu Qiu ◽  
Puyu Yuan
Keyword(s):  
Energy Management ◽  
Evaluation Criteria ◽  
Energy System ◽  
System Construction ◽  
Interval Numbers ◽  
Construction Scheme ◽  
Smart Energy Management ◽  
Integrated Energy System ◽  
And Control ◽  
Selection Of

Since application of integrated energy systems (IESs) has formed a markedly increasing trend recently, selecting an appropriate integrated energy system construction scheme becomes essential to the energy supplier. This paper aims to develop a multi-criteria decision-making model for the evaluation and selection of an IES construction scheme equipped with smart energy management and control platform. Firstly, a comprehensive evaluation criteria system including economy, energy, environment, technology and service is established. The evaluation criteria system is divided into quantitative criteria denoted by interval numbers and qualitative criteria. Secondly, single-valued neutrosophic numbers are adopted to denote the qualitative criteria in the evaluation criteria system. Thirdly, in order to accommodate mixed data types consisting of both interval numbers and single-valued neutrosophic numbers, the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method is extended into a three-stage technique by introducing a fusion coefficient μ. Then, a real case in China is evaluated through applying the proposed method. Furthermore, a comprehensive discussion is made to analyze the evaluation result and verify the reliability and stability of the method. In short, this study provides a useful tool for the energy supplier to evaluate and select a preferred IES construction scheme.

scholarly journals Research on Optimization of Linkage Operation of Integrated Energy System in Industrial Parks based on Chaotic Particle Swarm Algorithm

2021 ◽  
Vol 245 ◽  
pp. 01052
Author(s):  
Yang Yang ◽  
Mengjin Hu ◽  
Mengju Wei ◽  
Yongli Wang ◽  
Minhan Zhou ◽  
...  
Keyword(s):  
Particle Swarm ◽  
Clean Energy ◽  
Energy System ◽  
Utilization Efficiency ◽  
Particle Swarm Algorithm ◽  
Energy Structure ◽  
Industrial Park ◽  
Industrial Parks ◽  
Integrated Energy System ◽  
Swarm Algorithm

Industrial parks cover a variety of production capacities and energy-consuming entities, with large load demand and complex energy-using structure, and common problems such as low energy utilization efficiency and unreasonable energy structure. The construction of an integrated energy system (IES) with a combined cooling, heating and power system as the core unit in the industrial park is of great significance for achieving reliable, efficient and clean energy use in the park. Therefore, this article is based on the integrated energy system of the industrial park, aims at the lowest total cost of park operators, and considers the constraints of grid node balance, equipment output and energy storage equipment, and constructs source-grid-load-storage linkage operation optimization model, and build a chaotic particle swarm algorithm (CPSO) to solve the model. Finally, a typical industrial park in my country is taken as an example to analyze the scientificity of the model.

scholarly journals Holistic Simulation Approach for Optimal Operation of Smart Integrated Energy Systems under Consideration of Resilience, Economics and Sustainability

2021 ◽  
Vol 6 (11) ◽  
pp. 150
Author(s):  
Kai Hoth ◽  
Tom Steffen ◽  
Béla Wiegel ◽  
Amine Youssfi ◽  
Davood Babazadeh ◽  
...  
Keyword(s):  
Energy Management ◽  
Dynamic Models ◽  
Energy Systems ◽  
Energy System ◽  
Optimal Operation ◽  
Distributed Resources ◽  
Holistic Model ◽  
Future System ◽  
Integrated Energy System ◽  
Operational Concept

The intermittent energy supply from distributed resources and the coupling of different energy and application sectors play an important role for future energy systems. Novel operational concepts require the use of widespread and reliable Information and Communication Technology (ICT). This paper presents the approach of a research project that focuses on the development of an innovative operational concept for a Smart Integrated Energy System (SIES), which consists of a physical architecture, ICT and energy management strategies. The cellular approach provides the architecture of the physical system in combination with Transactive Control (TC) as the system’s energy management framework. Independent dynamic models for each component, the physical and digital system, operational management and market are suggested and combined in a newly introduced co-simulation platform to create a holistic model of the integrated energy system. To verify the effectiveness of the operational concept, energy system scenarios are derived and evaluation criteria are suggested which can be employed to evaluate the future system operations.

scholarly journals Electricity, Heat, and Gas Load Forecasting Based on Deep Multitask Learning in Industrial-Park Integrated Energy System

Entropy ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. 1355 ◽  
Author(s):  
Linjuan Zhang ◽  
Jiaqi Shi ◽  
Lili Wang ◽  
Changqing Xu
Keyword(s):  
Energy Demand ◽  
Demand Forecasting ◽  
Energy System ◽  
Multitask Learning ◽  
Effective Characteristics ◽  
Industrial Park ◽  
Energy Forecasting ◽  
Training Stage ◽  
Integrated Energy System ◽  
Term Energy

Different energy systems are closely connected with each other in industrial-park integrated energy system (IES). The energy demand forecasting has important impact on IES dispatching and planning. This paper proposes an approach of short-term energy forecasting for electricity, heat, and gas by employing deep multitask learning whose structure is constructed by deep belief network (DBN) and multitask regression layer. The DBN can extract abstract and effective characteristics in an unsupervised fashion, and the multitask regression layer above the DBN is used for supervised prediction. Then, subject to condition of practical demand and model integrity, the whole energy forecasting model is introduced, including preprocessing, normalization, input properties, training stage, and evaluating indicator. Finally, the validity of the algorithm and the accuracy of the energy forecasts for an industrial-park IES system are verified through the simulations using actual operating data from load system. The positive results turn out that the deep multitask learning has great prospects for load forecast.

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