4.8 Article

Heat recovery with heat pumps in non-energy intensive industry: A detailed bottom-up model analysis in the French food & drink industry

Journal

APPLIED ENERGY
Volume 111, Issue -, Pages 489-504

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2013.05.035

Keywords

Non-energy intensive industry; Heat recovery; Heat pump; Energy savings; Bottom-up modelling; Food & drink industry

Funding

  1. EDF
  2. ADEME
  3. RENAULT
  4. SCHNEIDER ELECTRIC
  5. TOTAL
  6. MINES ParisTech
  7. Ecole des Ponts ParisTech
  8. AgroParisTech
  9. ParisTech

Ask authors/readers for more resources

Rising energy prices and environmental impacts inevitably encourage industrials to get involved in promoting energy efficiency and emissions reductions. To achieve this goal, we have developed the first detailed bottom-up energy model for Non-Energy Intensive industry (NEI) to study its global energy efficiency and the potential for CO2 emissions reduction at a 4-digit level of NACE classification. The latter, which is generally neglected in energy analyses, is expected to play an important role in reducing industry energy intensity in the long term due to its economic and energy significance and relatively high growth rate. In this paper, the modelling of NEI is done by energy end-use owing to the unsuitability of the end-product/process approach used in the Energy Intensive industry modelling. As an example, we analysed the impact of heat recovery with heat pumps (HP) on industrial processes up to 2020 on energy savings and CO2 emissions reductions in the French food & drink industry (F&D), the biggest NEI sector. The results showed HP could be an excellent and very promising energy recovery technology. For further detailed analysis, the depiction of HP investment cost payments is given per temperature range for each F&D subsector. This model constitutes a useful decision-making tool for assessing potential energy savings from investing in efficient technologies at the highest level of disaggregation, as well as a better subsectoral screening. (C) 2013 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Energy & Fuels

Feasible path toward 40-100% renewable energy shares for power supply in France by 2050: A prospective analysis

Vincent Krakowski, Edi Assoumou, Vincent Mazauric, Nadia Maizi

APPLIED ENERGY (2016)

Article Economics

Energy contribution to Latin American INDCs: Analyzing sub-regional trends with a TIMES model

Sebastien Postic, Sandrine Selosse, Nadia Maizi

ENERGY POLICY (2017)

Article Energy & Fuels

Is GHG mitigation policy enough to develop bioenergy in Asia: a long-term analysis with TIAM-FR

Seungwoo Kang, Sandrine Selosse, Nadia Maizi

INTERNATIONAL JOURNAL OF OIL GAS AND COAL TECHNOLOGY (2017)

Article Energy & Fuels

Exploring sustainable energy future in Reunion Island

Sandrine Selosse, Olivia Ricci, Sabine Garabedian, Nadia Maizi

UTILITIES POLICY (2018)

Article Energy & Fuels

Critical raw materials and transportation sector electrification: A detailed bottom-up analysis in world transport

Emmanuel Hache, Gondia Sokhna Seck, Marine Simoen, Clement Bonnet, Samuel Carcanague

APPLIED ENERGY (2019)

Article Engineering, Environmental

Copper at the crossroads: Assessment of the interactions between low-carbon energy transition and supply limitations

Gondia Sokhna Seck, Emmanuel Hache, Clement Bonnet, Marine Simoen, Samuel Carcanague

RESOURCES CONSERVATION AND RECYCLING (2020)

Article Environmental Studies

Potential bottleneck in the energy transition: The case of cobalt in an accelerating electro-mobility world

Gondia Sokhna Seck, Emmanuel Hache, Charlene Barnet

Summary: The decarbonization of the transport sector is crucial for public policies in the energy transition. Cobalt, used in batteries for electric vehicles, is expected to face increasing demand. To evaluate cobalt availability until 2050, climate and mobility scenarios were considered, with a focus on cobalt content.

RESOURCES POLICY (2022)

Article Green & Sustainable Science & Technology

Hydrogen and the decarbonization of the energy system in europe in 2050: A detailed model-based analysis

Gondia S. Seck, Emmanuel Hache, Jerome Sabathier, Fernanda Guedes, Gunhild A. Reigstad, Julian Straus, Ove Wolfgang, Jabir A. Ouassou, Magnus Askeland, Ida Hjorth, Hans I. Skjelbred, Leif E. Andersson, Sebastien Douguet, Manuel Villavicencio, Johannes Trueby, Johannes Brauer, Clement Cabot

Summary: The paper examines the potential of low-carbon and renewable hydrogen in decarbonizing the European energy system. It presents two policy-relevant scenarios and uses cost optimization modeling to estimate hydrogen production. The results show that hydrogen production will significantly increase in the coming decades and rely on a diverse mix of technologies and imports from neighboring regions.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2022)

Article Multidisciplinary Sciences

The impact of methane leakage on the role of natural gas in the European energy transition

Behrang Shirizadeh, Manuel Villavicencio, Sebastien Douguet, Johannes Truby, Charbel Bou Issa, Gondia Sokhna Seck, Vincent Dherbemont, Emmanuel Hache, Louis-Marie Malbec, Jerome Sabathier, Malavika Venugopal, Fanny Lagrange, Stephanie Saunier, Julian Straus, Gunhild A. Reigstad

Summary: This study examines the cost-optimal European energy transition with CO2 and methane neutrality objectives. The findings show that the adoption of the best available methane abatement technologies can significantly reduce methane leakage and limit the environmental burden to a lower level. Additionally, renewable energy sources are identified as the key drivers for achieving climate neutrality, while natural gas requires high levels of emission reductions.

NATURE COMMUNICATIONS (2023)

Proceedings Paper Energy & Fuels

Time Reconciliation and Space Agregation to Shed Light on the Plausibility of Long-Term Low Carbon Pathways for Power Systems

Nadia Maizi, Vincent Krakowski, Edi Assoumou, Vincent Mazauric, Xiang Li

2016 THE 4TH IEEE INTERNATIONAL CONFERENCE ON SMART ENERGY GRID ENGINEERING (SEGE) (2016)

Article Energy & Fuels

Theoretical and experimental investigation on the advantages of auxetic nonlinear vortex-induced vibration energy harvesting

Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou

Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.

APPLIED ENERGY (2024)

Article Energy & Fuels

Evaluation method for the availability of solar energy resources in road areas before route corridor planning

Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan

Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.

APPLIED ENERGY (2024)

Article Energy & Fuels

Impacts of PTL coating gaps on cell performance for PEM water electrolyzer

Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender

Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.

APPLIED ENERGY (2024)

Article Energy & Fuels

Coordinated pricing mechanism for parking clusters considering interval-guided uncertainty-aware strategies

Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado

Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.

APPLIED ENERGY (2024)

Article Energy & Fuels

The establishment of evaluation systems and an index for energy superpower

Duan Kang

Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.

APPLIED ENERGY (2024)

Article Energy & Fuels

A model-based study of the evolution of gravel layer permeability under the synergistic blockage effect of sand particle transport and secondary hydrate formation

Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang

Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.

APPLIED ENERGY (2024)

Article Energy & Fuels

Energy optimization for HVAC systems in multi-VAV open offices: A deep reinforcement learning approach

Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi

Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.

APPLIED ENERGY (2024)

Article Energy & Fuels

Asymmetry stagger array structure ultra-wideband vibration harvester integrating magnetically coupled nonlinear effects

Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong

Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.

APPLIED ENERGY (2024)

Article Energy & Fuels

Enhancement of hydrogen production via optimizing micro-structures of electrolyzer on a microfluidic platform

Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song

Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.

APPLIED ENERGY (2024)

Article Energy & Fuels

A novel day-ahead scheduling model to unlock hydropower flexibility limited by vibration zones in hydropower-variable renewable energy hybrid system

Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz

Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.

APPLIED ENERGY (2024)

Article Energy & Fuels

Archery-inspired catapult mechanism with controllable energy release for efficient ultralow-frequency energy harvesting

Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He

Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.

APPLIED ENERGY (2024)

Article Energy & Fuels

A novel combined probabilistic load forecasting system integrating hybrid quantile regression and knee improved multi-objective optimization strategy

Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang

Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.

APPLIED ENERGY (2024)

Article Energy & Fuels

Capacity fade prediction for vanadium redox flow batteries during long-term operations

Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung

Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.

APPLIED ENERGY (2024)

Article Energy & Fuels

State-of-charge balancing strategy of battery energy storage units with a voltage balance function for a Bipolar DC mircrogrid

Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu

Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.

APPLIED ENERGY (2024)

Article Energy & Fuels

Deep clustering of reinforcement learning based on the bang-bang principle to optimize the energy in multi-boiler for intelligent buildings

Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen

Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.

APPLIED ENERGY (2024)