Applied Energy最新文献

{"title":"Control method and system for seawater desalination hydropower symbiosis in coastal steel enterprises","authors":"Liyun Wu ,&nbsp;Sujun Chen ,&nbsp;Yuebo Yu ,&nbsp;Liu Zhang ,&nbsp;Delei Chen ,&nbsp;Zhixin Tang ,&nbsp;Zhong Zheng ,&nbsp;Ke Zhang","doi":"10.1016/j.apenergy.2024.124792","DOIUrl":"10.1016/j.apenergy.2024.124792","url":null,"abstract":"<div><div>In the conventional seawater desalination hydropower cogeneration mode, issues such as condenser cold source loss and energy cascade waste arise. To address these issues, a new process, referred to as hydropower symbiosis, has been developed for seawater desalination. This process utilizes low calorific value exhaust steam from steam turbine power generation as the heat source for desalination. It makes full use of low-calorific-value blast furnace gas from steel mills to improve the efficiency of the power generation system and utilizes previously wasted energy in the form of waste gas steam for seawater desalination. To achieve collaborative control of water and power cogeneration in the new hydropower symbiosis system, this paper presents a control method based on Stair-like Generalized Predictive Control (SGPC). The key coupling parameter of the hydropower symbiosis system, which is the exhaust steam flow, is controlled to ensure synergy in the system. Firstly, the parameters of the hydropower co-generation system are recognized online based on the actual operation data to correct the system parameters under the change of working conditions. Then, the future output of controlled spent steam flow is predicted based on the CARIMA model, which is easy to identify online, providing a reference or the optimization of the control quantity, i.e., the pumping valve opening. Finally, based on the predicted value of spent steam flow, the optimal sequence of pumping valve openings is determined in real-time on a rolling basis to enhance the stability of spent steam flow control under perturbation and variable operating conditions. The stability and effectiveness of the proposed control method are demonstrated through simulation experiments and validated by the application in a seawater desalination project in the steel plant. Production control data from three months of continuous system operation indicate that the method effectively manages variations in blast furnace gas calorific value and steam pipe network pressure fluctuations while maintaining stable control capabilities. It ensures efficient water production under various conditions and meets power generation requirements, ensuring stable and reliable system operation. This method also holds valuable reference significance for similar problem research and engineering applications.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124792"},"PeriodicalIF":10.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating local market operations into transmission investment: A tri-level optimization approach","authors":"Yuxin Xia ,&nbsp;Iacopo Savelli ,&nbsp;Thomas Morstyn","doi":"10.1016/j.apenergy.2024.124721","DOIUrl":"10.1016/j.apenergy.2024.124721","url":null,"abstract":"<div><div>The rise of Local Energy Markets (LEMs) and increasing local flexibility present a key research question: How do local flexibility and LEM operations impact merchant-regulated transmission investments? This paper introduces a novel tri-level framework to integrate local market dynamics into transmission investment decisions. The framework models the sequential operations of the WSM and LEMs, adhering to their respective network constraints, and includes a regulatory mechanism that incentivizes profit-driven Transmission Companies (Transcos) to make social welfare maximizing investments while accounting for local refinement costs. The tri-level optimization problem is asymptotically approximated by a mixed-integer second-order cone programming problem. Our findings from three case studies reveal that the provision of local flexibility substantially reduces reliance on conventional energy generation supplies. Additionally, transmission investment decisions are influenced by the levels of flexible generation and consumers, while adhering to network constraints. Moreover, the tri-level model enhances Transcos’ awareness of the sequential interactions between the WSM and LEMs, enabling them to make investment strategies that are responsive to the changing dynamics of local markets.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124721"},"PeriodicalIF":10.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flexible operation of solar-assisted carbon capture power plants considering interval-enhanced CVaR","authors":"Shuhao Liang ,&nbsp;Suhua Lou ,&nbsp;Ziqing Zhu ,&nbsp;Yongping Sun","doi":"10.1016/j.apenergy.2024.124850","DOIUrl":"10.1016/j.apenergy.2024.124850","url":null,"abstract":"<div><div>Solar-assisted carbon capture power plants (SACCPPs) leverage solar thermal energy to mitigate power output loss and expand the net output range of carbon capture units, enhancing energy economy, reserve capacity, and carbon emission reduction. However, assessing the flexible operation benefits of SACCPPs in power systems with high wind power penetration is challenging due to complex thermodynamic models and limited risk assessment methods. This study addresses these gaps by proposing an innovative modeling approach and benefits evaluation framework. First, a linear flexible operation model is developed, focusing on the technical features of SACCPPs relevant to power system operation and scheduling. This model elucidates the intercoordination in power generation, carbon capture, and thermal storage. The operating ranges of various carbon capture power plants are quantitatively analyzed using a two-dimensional coordinate diagram, highlighting the flexible regulation advantages of SACCPPs. Second, an Interval-Enhanced CVaR method is introduced, which considers random variables with unknown probability distributions, refining the current CVaR-based knowledge. This method is used for a quantified risk assessment to evaluate supply-demand imbalance risks in power systems, providing a foundation for assessing SACCPPs' risk mitigation benefits. Third, a risk-aware operation scheduling model is developed to explore SACCPPs' capability in enhancing the system's energy economic benefits, risk mitigation, and carbon emissions reduction. This model aids energy administration in evaluating system gains from SACCPPs and in developing rational system-wide planning and retrofit projects. Finally, numerical simulation and sensitivity analysis results on the modified IEEE-39 bus system validate the robust adaptability and effectiveness of the proposed models and methods.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124850"},"PeriodicalIF":10.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electro-thermal analysis of inductively coupled power transfer in pavement for electric vehicle charging","authors":"Xiao Chen ,&nbsp;Hao Wang ,&nbsp;Zilong Zheng ,&nbsp;Fei Lu","doi":"10.1016/j.apenergy.2024.124809","DOIUrl":"10.1016/j.apenergy.2024.124809","url":null,"abstract":"<div><div>Inductively coupled power transfer (ICPT) system provides a promising alternative for wireless charging of electric vehicles (EVs). This study aims to develop an integrated electro-thermal analysis approach for analyzing power transmission and heat transfer of ICPT embedded in the pavement. Laboratory experiments were first conducted to evaluate wireless power transfer efficiency of ICPT system with the interference of pavement material. An integrated electro-thermal model was established to analyze transmission efficiency and temperature variation when ICPT system is embedded at various pavement depths of pavement structure subject to different vehicle offsets. The results revealed that traditional cement concrete pavement material with a typical water to cement ratio of 0.48 has negligible impact on power transfer efficiency under standard charging levels. However, the efficiency dropped from 95.4 % to 85.9 % as embedment depth increased from 4 cm to 16 cm, and it further decreased to 84.6 % with a 15 cm one-side offset at a 4 cm installation depth. The power loss results in significant changes of temperature. The maximum temperature variations were found to be impacted by incremental state of charge, charging power, and transmission efficiency, in addition to thermal properties of ICPT components. Under the most unfavorable case, those temperature changes of the ICPT system and pavement can be up to 112 °C and 76 °C, respectively.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124809"},"PeriodicalIF":10.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microgrid energy management system with degradation cost and carbon trading mechanism: A multi-objective artificial hummingbird algorithm","authors":"Ling-Ling Li ,&nbsp;Bing-Xiang Ji ,&nbsp;Zhong-Tao Li ,&nbsp;Ming K. Lim ,&nbsp;Kanchana Sethanan ,&nbsp;Ming-Lang Tseng","doi":"10.1016/j.apenergy.2024.124853","DOIUrl":"10.1016/j.apenergy.2024.124853","url":null,"abstract":"<div><div>Microgrid is an important way to optimize the distributed power generation and its optimal scheduling to ensure reliable and economical operation. This study constructs a multi-objective optimization model for a microgrid energy management system involving degradation cost and carbon trading mechanism. A carbon trading mechanism is to reduce greenhouse gas emissions; meanwhile, a demand response strategy is employed to optimize energy load demand. The energy storage system mathematical model is considered and degradation cost is introduced to change the corresponding control strategy. A hybrid energy storage is used in this model to smooth out the solar power and wind power fluctuations. Hence, a multi-objective artificial hummingbird optimization algorithm is proposed and uses to solve the optimal operation strategy of the microgrid. The final optimal operation strategy is obtained from the Pareto solution set using TOPSIS. The results show that the proposed microgrid system has 20.2 % lower total operating costs, 4.5 % lower carbon emissions, and 32.6 % longer battery life than the conventional microgrid system, which is critical for improving the operation stability, economy, low carbon of the system, and extending the service life of the battery.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124853"},"PeriodicalIF":10.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transactive control for grid-interactive efficient commercial buildings","authors":"Sen Huang ,&nbsp;Jianming Lian ,&nbsp;Srinivas Katipamula ,&nbsp;Robert Lutes","doi":"10.1016/j.apenergy.2024.124675","DOIUrl":"10.1016/j.apenergy.2024.124675","url":null,"abstract":"<div><div>Transactive control (TC) is a type of distributed control strategy that uses market mechanisms to coordinate distinct objectives of individual entities. Through grid-interactive efficient buildings, TC can help achieve power balance in the electrical power grid under high penetration of renewable energy. This paper presents a standard TC approach for commercial heating, ventilation, and air-conditioning (HVAC) systems. This TC approach includes a flexible market structure to accommodate the variances in system configurations of HVAC systems, and an extensible market-based control process to support various demand response (DR) services. In addition, we develop a software workflow for deploying this TC approach. The software workflow is based on VOLTTRON, which is a distributed sensing and control software platform, and encapsulates the process of deploying decentralized control architecture and market-based control on a large scale. Case studies were conducted with both building energy simulations and field tests. The results show that TC is effective at providing real time price, demand limiting, and load following DR services with the studied HVAC systems.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124675"},"PeriodicalIF":10.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental study on dynamic characteristics of a jacket-type offshore wind turbine under coupling action of wind and wave","authors":"Wen-Li Chen ,&nbsp;Ziyang Zhang ,&nbsp;Jiabin Liu ,&nbsp;Donglai Gao","doi":"10.1016/j.apenergy.2024.124876","DOIUrl":"10.1016/j.apenergy.2024.124876","url":null,"abstract":"<div><div>Wind and wave loads are crucial factors affecting the structural safety of offshore wind turbines. With the trend towards larger wind turbines, the DTU 10 MW wind turbines have become mainstream models. The jacket-type foundation has been widely used due to its high rigidity and suitability for a wide range of water depths. Therefore, a scaled experiment was conducted on a DTU 10 MW jacket-type offshore wind turbine to reveal the dynamic characteristics of the structure. The experimental results showed that the wind loads dominated the mean of the structural response. Under the coupling action of wind and wave, the wind load suppresses the response at the structure's first-order frequency and the wave frequency. Both the wind and wave loads influence the amplitude of the structural response. The response amplitudes of the tower top displacement and foundation bending moment were smaller than the square root of the sum of the squares (SRSS) obtained from the separate wind and wave actions. Under extreme wind speed, the tower top displacement's amplitude is 75 % of the SRSS value, and the amplitude of the foundation bending moment is only 67 % of the SRSS value.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124876"},"PeriodicalIF":10.1,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imitation reinforcement learning energy management for electric vehicles with hybrid energy storage system","authors":"Weirong Liu ,&nbsp;Pengfei Yao ,&nbsp;Yue Wu ,&nbsp;Lijun Duan ,&nbsp;Heng Li ,&nbsp;Jun Peng","doi":"10.1016/j.apenergy.2024.124832","DOIUrl":"10.1016/j.apenergy.2024.124832","url":null,"abstract":"<div><div>Deep reinforcement learning has become a promising method for the energy management of electric vehicles. However, deep reinforcement learning relies on a large amount of trial-and-error training to acquire near-optimal performance. An adversarial imitation reinforcement learning energy management strategy is proposed for electric vehicles with hybrid energy storage system to minimize the cost of battery capacity loss. Firstly, the reinforcement learning exploration is guided by expert knowledge, which is generated by dynamic programming under various standard driving conditions. The expert knowledge is represented as the optimal power allocation mapping. Secondly, at the early imitation stage, the action of the reinforcement learning agent approaches the optimal power allocation mapping rapidly by using adversarial networks. Thirdly, a dynamic imitation weight is developed according to the Discriminator of adversarial networks, making the agent transit to self-explore the near-optimal power allocation under online driving conditions. Results demonstrate that the proposed strategy can accelerate the training by 42.60% while enhancing the reward by 15.79% compared with traditional reinforcement learning. Under different test driving cycles, the proposed method can further reduce the battery capacity loss cost by 5.1%–12.4%.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124832"},"PeriodicalIF":10.1,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Divide and conquer: Spectral-splitting and utilization of thermal radiation from waste heat in the steel industry","authors":"Haoming Li ,&nbsp;Shuaibin Wan ,&nbsp;Lu Wang ,&nbsp;Jiyun Zhao ,&nbsp;Dongxu Ji","doi":"10.1016/j.apenergy.2024.124836","DOIUrl":"10.1016/j.apenergy.2024.124836","url":null,"abstract":"<div><div>Approximately 35 % high-temperature waste heat in the steel industry is carried by blast furnace slag and steelmaking slag, and thermal radiation is a primary pathway for this waste heat to dissipate into the ambient environment. Thermophotovoltaic (TPV) systems can convert short-wavelength thermal radiation into electrical energy, but the long-wavelength radiation is still wasted. Here, this work introduces a concept of spectral-splitting (SS) for full-spectrum thermal radiation utilization, allowing simultaneous waste heat recovery by TPV and heat-to-power methods such as Stirling engine (SE). To further demonstrate this concept, an SS TPV-SE system is designed. An optical transmission window of 0–1.7 μm is applied for TPV, and an over 5 μm absorption window is applied for SE. Results show that, with a 0.1 × 1 m molten slag chute, the SS TPV-SE system yields an output power of over 1300 W and achieves an overall efficiency of around 19 %, resulting in an about 58 % improvement compared to the standalone TPV system, and leads to a CO₂ emission reduction of 7516 kg/year. Provided the improved energy efficiency and environmental sustainability, the spectral-splitting concept presented in this work provides a promising approach to enhancing waste heat recovery in the steel industry.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124836"},"PeriodicalIF":10.1,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainable deeply-fused nets electricity demand prediction model: Factoring climate predictors for accuracy and deeper insights with probabilistic confidence interval and point-based forecasts","authors":"Sujan Ghimire ,&nbsp;Mohanad S. AL-Musaylh ,&nbsp;Thong Nguyen-Huy ,&nbsp;Ravinesh C. Deo ,&nbsp;Rajendra Acharya ,&nbsp;David Casillas-Pérez ,&nbsp;Zaher Mundher Yaseen ,&nbsp;Sancho Salcedo-Sanz","doi":"10.1016/j.apenergy.2024.124763","DOIUrl":"10.1016/j.apenergy.2024.124763","url":null,"abstract":"<div><div>Electricity consumption has stochastic variabilities driven by the energy market volatility. The capability to predict electricity demand that captures stochastic variances and uncertainties is significantly important in the planning, operation and regulation of national electricity markets. This study has proposed an explainable deeply-fused nets electricity demand prediction model that factors in the climate-based predictors for enhanced accuracy and energy market insight analysis, generating point-based and confidence interval predictions of daily electricity demand. The proposed hybrid approach is built using Deeply Fused Nets (FNET) that comprises of Convolutional Neural Network (CNN) and Bidirectional Long-Short Term Memory (BILSTM) Network with residual connection. The study then contributes to a new deep fusion model that integrates intermediate representations of the base networks (fused output being the input of the remaining part of each base network) to perform these combinations deeply over several intermediate representations to enhance the demand predictions. The results are evaluated with statistical metrics and graphical representations of predicted and observed electricity demand, benchmarked with standalone models <em><em>i.e.</em></em>, BILSTM, LSTMCNN, deep neural network, multi-layer perceptron, multivariate adaptive regression spline, kernel ridge regression and Gaussian process of regression. The end part of the proposed FNET model applies residual bootstrapping where final residuals are computed from predicted and observed demand to generate the 95% prediction intervals, analysed using probabilistic metrics to quantify the uncertainty associated with FNETS objective model. To enhance the FNET model’s transparency, the SHapley Additive explanation (SHAP) method has been applied to elucidate the relationships between electricity demand and climate-based predictor variables. The suggested model analysis reveals that the preceding hour’s electricity demand and evapotranspiration were the most influential factors that positively impacting current electricity demand. These findings underscore the FNET model’s capacity to yield accurate and insightful predictions, advocating its utility in predicting electricity demand and analysis of energy markets for decision-making.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124763"},"PeriodicalIF":10.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}