Article
Energy & Fuels
Shuyang Xu, Xingying Chen, Jun Xie, Saifur Rahman, Jixiang Wang, Hongxun Hui, Tao Chen
Summary: This paper proposes a comprehensive market framework where residential customers can provide proactive demand response actions in a day-ahead market, and model and evaluate the interactions between market entities through agent-based modeling and reinforcement learning. Results show that proactive demand response programs and interactions between market entities may yield significant benefits for both the supply and demand sides.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2021)
Article
Construction & Building Technology
Jason Mair, Kiti Suomalainen, David M. Eyers, Michael W. Jack
Summary: The study examines distributed battery energy storage as a potential solution for increasing electricity supply and demand variability. It finds that battery capacity requirements vary significantly based on different operational modes and show seasonal variations. Aggregating households can significantly reduce per-house battery requirements for load smoothing and peak shaving.
ENERGY AND BUILDINGS
(2021)
Article
Chemistry, Physical
Lianlian Liu, Niclas Solin, Olle Inganas
Summary: The increasing use of electricity generated from solar and wind energy has led to a growing demand for energy storage. This demand for materials for storage systems will require considerable energy input, and sustainable electrochemical systems need to be developed to address this issue. Storing electrical energy in bio-based batteries is seen as one option for handling the rapid expansion of renewable energy generated from wind turbines and solar photovoltaic systems.
ADVANCED ENERGY MATERIALS
(2021)
Article
Energy & Fuels
S. A. R. Mir Mohammadi Kooshknow, R. Herber, F. Ruzzenenti
Summary: Electricity storage systems (ESS) are seen as crucial for future electricity systems and the transition to renewables. However, the lack of viable business models has hindered their global implementation. Through simulation and analysis of the Dutch electricity market, it was found that the wholesale arbitrage business model is more profitable than the reserve capacity model for ESS. Additionally, the economic and technical characteristics of ESS have a greater impact on its value than market conditions and carbon pricing.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Economics
J. Isaac Miller, Kyungsik Nam
Summary: The paper proposes a novel method to model daily peak electricity demand using temperature and additional weather covariates. The method allows for flexibility in the impact of different weather factors on temperature's effect on demand, such as humidity and wind speed. Additionally, the study finds that time of day also plays a role in demand response to temperature. Accounting for these weather-related covariates improves the model's ability to explain daily peak demand.
Review
Chemistry, Physical
I. M. Peters, C. Breyer, S. A. Jaffer, S. Kurtz, T. Reindl, R. Sinton, M. Vetter
Summary: Batteries play a crucial role in the transition towards terawatt levels of photovoltaics by reducing fluctuations in electricity generation and enabling higher adoption rates. Technological, economic, and policy innovations are needed to expand the adoption of batteries in solar energy systems.
Article
Engineering, Electrical & Electronic
Seongmun Oh, Junhyuk Kong, Yejin Yang, Jaesung Jung, Chul-Ho Lee
Summary: This study proposes a multi-use energy storage system (ESS) framework that enables industrial customers to participate in demand response programs and earn additional profits through reinforcement learning. The framework uses a Markov decision process model to optimize customer actions in different environments, and experimental results show that it can achieve near-optimal decisions in various scenarios.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Green & Sustainable Science & Technology
Rasool Kalbasi, Mohsen Sharifpur, Mehdi Mortazavi, Nader Karimi, Le Nguyen Nhu Binh, Masoud Afrand
Summary: The installation of a cold water storage tank can effectively address the issue of electricity supply during peak times in hot areas. Through energy analysis and response surface methodology, the optimal tank volume and reduction in electricity demand were determined, resulting in the elimination of cooling-related electricity consumption during peak periods.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Thermodynamics
Shoujun Huang, Oveis Abedinia
Summary: This paper introduces a new planning model based on renewable energy uncertainty and demand response, aiming to minimize the total cost of the electricity market. By incorporating energy storage systems and time-of-use demand response programs, the power flow in the microgrid is effectively managed to ensure essential load support and voltage stability.
Article
Energy & Fuels
Seongmun Oh, Jaesung Jung, Ahmet Onen, Chul-Ho Lee
Summary: This study focuses on the participation strategy of aggregators in the demand response program. By using the reinforcement learning framework, the aggregators and customers interact and make optimal decisions regarding incentives and energy storage system operations to optimize the overall system.
FRONTIERS IN ENERGY RESEARCH
(2022)
Article
Energy & Fuels
Lu Feng, Xinjing Zhang, Chengyuan Li, Xiaoyu Li, Bin Li, Jie Ding, Chao Zhang, Han Qiu, Yujie Xu, Haisheng Chen
Summary: Energy storage is a key factor in promoting renewable energy development. The coupling of battery energy storage systems (BESS) with renewable energy can generate additional revenue through arbitrage and auxiliary services. This study investigates the technical and economic performance of such a coupling system and develops a multi-objective three-level model for the optimal configuration of BESS.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
A. Rezaee Jordehi
Summary: This paper proposes a two-stage stochastic model considering uncertainties in the electricity market, studying how slow and fast demand response can reduce electricity procurement costs and risks, with results showing that fast demand response is more efficient than slow demand response.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Xinjing Zhang, Chao (Chris) Qin, Eric Loth, Yujie Xu, Xuezhi Zhou, Haisheng Chen
Summary: The time-varying mismatch between electricity supply and demand is a growing challenge for the electricity market, exacerbated by the fast-growing renewable energy penetration. Energy storage systems offer a solution and economic benefits through arbitrage.
Article
Construction & Building Technology
Mitchell Curtis, S. T. Smith, Jacopo Torriti
Summary: DSR's slow penetration in electricity markets is mainly due to the difficulty in assessing flexibility potential. A new DSR estimation method using detailed profile information has been developed in this study, showing better error balance compared to previous methods.
ENERGY AND BUILDINGS
(2021)
Article
Green & Sustainable Science & Technology
Ligia da Silva Lima, Mattijs Quartier, Astrid Buchmayr, David Sanjuan-Delmas, Hannes Laget, Dominique Corbisier, Jan Mertens, Jo Dewulf
Summary: This study investigates the environmental impacts of lithium-ion and vanadium flow batteries for renewable energy storage, with a focus on factors such as battery composition and recycled electrolyte. Results show that using recycled electrolyte can significantly reduce the environmental impacts of vanadium-based storage systems, while the new lithium-ion battery cathode chemistry leads to higher overall impacts.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2021)
Article
Engineering, Environmental
Coen van der Giesen, Christoph J. Meinrenken, Rene Kleijn, Benjamin Sprecher, Klaus S. Lackner, Gert Jan Kramer
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2017)
Article
Computer Science, Interdisciplinary Applications
Ali Mehmani, Souma Chowdhury, Christoph Meinrenken, Achille Messac
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2018)
Article
Energy & Fuels
Menglian Zheng, Xinhao Wang, Christoph J. Meinrenken, Yi Ding
Article
Engineering, Electrical & Electronic
Sanjmeet Abrol, Ali Mehmani, Mark Kerman, Christoph J. Meinrenken, Patricia J. Culligan
PROCEEDINGS OF THE IEEE
(2018)
Article
Electrochemistry
Menglian Zhen, Jie Sun, Christoph J. Meinrenken, Tao Wang
JOURNAL OF ELECTROCHEMICAL ENERGY CONVERSION AND STORAGE
(2019)
Article
Energy & Fuels
Christoph J. Meinrenken, Ali Mehmani
Article
Energy & Fuels
Yonghua Song, Yi Ding, Pierluigi Siano, Christoph Meinrenken, Menglian Zheng, Goran Strbac
Article
Environmental Studies
Christoph J. Meinrenken, Zhenyu Shou, Xuan Di
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2020)
Article
Multidisciplinary Sciences
Christoph J. Meinrenken, Daniel Chen, Ricardo A. Esparza, Venkat Iyer, Sally P. Paridis, Aruna Prasad, Erika Whillas
SCIENTIFIC REPORTS
(2020)
Article
Construction & Building Technology
Christoph J. Meinrenken, Sanjmeet Abrol, Gaurav B. Gite, Christopher Hidey, Kathleen McKeown, Ali Mehmani, Vijay Modi, Elsbeth C. Turcan, Wanlin Xie, Patricia J. Culligan
Summary: Research has shown that feedback on electricity usage can reduce demand, with self-comparisons and high variety in feedback messages being the most effective in prompting reductions. Residents tend to conform to their neighbors' average usage, rather than exhibiting anti-conform boomerang behavior.
ENERGY AND BUILDINGS
(2021)
Article
Energy & Fuels
Lechen Li, Christoph J. Meinrenken, Vijay Modi, Patricia J. Culligan
Summary: This study develops a neural network model based on Convolutional Long Short-Term Memory, employing autoregressive features selection, exogenous features selection, and a default state to improve short-term residential electricity load forecasting accuracy. The model demonstrates up to 25% accuracy improvement in forecasting load across three spatial granularities in a multi-family residential building.
Article
Construction & Building Technology
Lechen Li, Christoph J. Meinrenken, Vijay Modi, Patricia J. Culligan
Summary: This study analyzed the impact of COVID-19 pandemic on residential electricity usage in New York City, predicting potential increases in electricity consumption under stay-at-home orders and warm summer weather. The study also highlighted the potential grid management challenges that could arise from the projected increase in peak demand.
ENERGY AND BUILDINGS
(2021)
Article
Multidisciplinary Sciences
Christoph J. Meinrenken, Daniel Chen, Ricardo A. Esparza, Venkat Iyer, Sally P. Paridis, Aruna Prasad, Erika Whillas
Summary: Product carbon footprints (PCFs) are increasingly important for sustainability decisions by companies and consumers. Life cycle assessment (LCA) helps companies achieve greater carbon reductions by improving the product's value chain. The Carbon Catalogue provides detailed information on greenhouse gas emissions and meta data for each product in the dataset.
Article
Multidisciplinary Sciences
Christoph J. Meinrenken, Noah Rauschkolb, Sanjmeet Abrol, Tuhin Chakrabarty, Victor C. Decalf, Christopher Hidey, Kathleen McKeown, Ali Mehmani, Vijay Modi, Patricia J. Culligan
Article
Green & Sustainable Science & Technology
Yash Amonkar, Nafisa Chowdhury, Yiran Song, Jane Siyuan Wu, Parth Vaidya, Christoph J. Meinrenken
JOURNAL OF ENVIRONMENTAL ACCOUNTING AND MANAGEMENT
(2019)
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.
Article
Energy & Fuels
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.