Applied Energy最新文献

{"title":"Risk-averse transactions optimization strategy for building users participating in incentive-based demand response programs","authors":"Cheng Zhen ,&nbsp;Jide Niu ,&nbsp;Zhe Tian ,&nbsp;Yakai Lu ,&nbsp;Chuanzhi Liang","doi":"10.1016/j.apenergy.2024.125009","DOIUrl":"10.1016/j.apenergy.2024.125009","url":null,"abstract":"<div><div>By participating in demand response programs, building users can provide energy flexibility for the power grid while earning economic benefits for themselves. However, the win-win situation described above is often challenged by the presence of ineffective demand response, over-target demand response and under-target demand response, which pose risks to the economic returns of building users and the stable operation of the grid. To this end, this study proposes a risk-averse transaction optimization strategy to offer bidding schemes and operational strategies that effectively balance the effectiveness of demand response with operational economic benefits. First, a novel model for calculating incentive subsidy is developed, which takes into account the power grid's requirements for demand response effectiveness, as well as differentiated subsidy and penalty mechanisms. Then, a risk-averse optimal dispatch model for building integrated energy systems is established. By collaboratively optimizing the declared response quantity and operation strategies, this method reduces the risk of incentive subsidy loss faced by building users and enhances demand response effectiveness. Lastly, the proposed models are applied in the power market of Shenzhen, China, and the effectiveness of the method is assessed based on three key performance indicators: incentive subsidy loss rate, operating cost reduction rate, the actual load response rate. The results indicate that the total incentive subsidy loss rate is reduced from 37.16 % to 17.75 % through the application of the risk-averse optimal dispatch model proposed in this paper, with operating cost savings ranging from 3 % to 8.09 %. More importantly, the effectiveness of demand response is significantly improved, with the proportion of effective response duration increasing from 18.60 % to 65.93 %. The proposed method is further validated by adjusting the penalty coefficient. Findings show that the risk-averse method provides more robust results and provides more reliable bidding schemes for declared response quantity.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 125009"},"PeriodicalIF":10.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142756752","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":"Two-stage planning of integrated energy systems under copula models informed cascading extreme weather uncertainty","authors":"Longxiang Chen ,&nbsp;Ze Luo ,&nbsp;Rui Jing ,&nbsp;Kai Ye ,&nbsp;Meina Xie","doi":"10.1016/j.apenergy.2024.124990","DOIUrl":"10.1016/j.apenergy.2024.124990","url":null,"abstract":"<div><div>Extreme weather events are becoming more intense and frequent globally. It is essential to enhance the resilience of energy system at the planning stage and mitigate negative impacts of these events on system performance by multi-energy integration and design optimization. Therefore, a two-stage integrated energy system planning framework is proposed in this work, which enhances the operational flexibility and resilience under extreme weather conditions. The correlation between floods and storm caused by typhoons is captured by copula models and incorporated into the integrated energy system planning model. The framework is applied to a case study of an industrial park with factory business and residence users. The results indicate that considering cascading extreme weather reduces the total cost and the interruption rate by 2.86 % and 53.71 %, respectively, compared to addressing single extreme weather events. For industrial parks with a high proportion of critical loads, the planning is more conservative, highlighting a reduced need for considering cascading extreme weather.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 124990"},"PeriodicalIF":10.1,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747813","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":"Multi-scale spatio-temporal transformer: A novel model reduction approach for day-ahead security-constrained unit commitment","authors":"Mao Liu ,&nbsp;Xiangyu Kong ,&nbsp;Kaizhi Xiong ,&nbsp;Jimin Wang ,&nbsp;Qingxiang Lin","doi":"10.1016/j.apenergy.2024.124963","DOIUrl":"10.1016/j.apenergy.2024.124963","url":null,"abstract":"<div><div>Security-constrained unit commitment (SCUC) in large-scale power systems faces significant computational challenges, particularly with increasing renewable energy integration. This paper introduces a multi-scale spatio-temporal transformer (MSTT) model for efficient SCUC problem reduction through three key innovations: a multi-scale ST attention mechanism integrating both hierarchical temporal attention and electrical distance-based spatial attention to capture complex system dependencies, a physics-informed position encoding method incorporating power system domain knowledge including electrical distance, power flow sensitivity, and generator stability characteristics, and an adaptive reduction strategy with dynamic threshold adjustment mechanism that automatically balances computational efficiency and solution reliability based on system states and prediction confidence. Experimental results on IEEE test systems demonstrate that the MSTT model achieves up to 69.5 % computational time reduction while maintaining solution optimality (base-normalized cost (BNC) ≤ 0.05 %), significantly outperforming existing approaches.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 124963"},"PeriodicalIF":10.1,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142756751","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":"Graph neural networks for power grid operational risk assessment under evolving unit commitment","authors":"Yadong Zhang,&nbsp;Pranav M. Karve,&nbsp;Sankaran Mahadevan","doi":"10.1016/j.apenergy.2024.124793","DOIUrl":"10.1016/j.apenergy.2024.124793","url":null,"abstract":"<div><div>This article investigates the ability of graph neural networks (GNNs) to identify risky conditions in a power grid over the subsequent few hours, without explicit, high-resolution information regarding future generator on/off status or power dispatch decisions. The GNNs are trained using supervised learning to predict the power grid’s aggregated bus-level (either zonal or system-level) or individual branch-level state under different power supply and demand conditions. The variability of the stochastic grid variables (wind/solar generation and load demand), and their statistical correlations, are considered while generating the inputs for the training data. The outputs in the training data include system-level, zonal and transmission line-level quantities of interest (QoIs). The ground truth of QoIs are obtained by numerically solving deterministic optimization problems (e.g., security-constrained unit commitment) with the same inputs. The GNN predictions are used to conduct hours-ahead, sampling-based reliability and risk assessment w.r.t. zonal and system-level (load shedding) as well as branch-level (overloading) failure events. The proposed methodology is demonstrated for three synthetic grids with sizes ranging from 118 to 2848 buses. Our results demonstrate that GNNs are capable of providing fast and accurate prediction of QoIs and can be good proxies for computationally expensive optimization algorithms. The excellent accuracy of GNN-based reliability and risk assessment suggests that GNN models can substantially improve situational awareness by enabling quick, high-resolution reliability and risk estimation.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 124793"},"PeriodicalIF":10.1,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747809","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":"Thermo-economic analysis of green hydrogen production onboard LNG carriers through solid oxide electrolysis powered by organic Rankine cycles","authors":"Doha Elrhoul ,&nbsp;Manuel Naveiro ,&nbsp;Manuel Romero Gómez ,&nbsp;Thomas A. Adams II","doi":"10.1016/j.apenergy.2024.124996","DOIUrl":"10.1016/j.apenergy.2024.124996","url":null,"abstract":"<div><div>LNG carriers play a crucial role in the shipping industry meeting the global demand for natural gas (NG). However, the energy losses resulting from the propulsion system and the excess boil-off gas (BOG) cannot be overlooked. The present article investigates the H₂ production on board LNG carriers employing both the engine's waste heat (WH) and the excess BOG. Conventional (ORC) and dual-pressure (2P-ORC) organic Rankine cycles coupled separately with a solid oxide electrolysis (SOEC) have been simulated and compared. The hydrogen (H₂) produced is then compressed at 150 bar for subsequent use as required. According to the results, the 2P-ORC generates 14.79 % more power compared to ORC, allowing for an increased energy supply to the SOEC; hence, producing more H₂ (34.47 kg/h compared to 31.14 kg/h). Including the 2P-ORC in the H₂ production plant results in a cheaper H₂ cost by 0.04 $/kg_H2 compared to ORC, a 1.13 %_LHV higher system efficiency when leveraging all the available waste heat. The plant including 2P-ORC exploits more than 86 % of the of the available waste compared to 70 % when using ORC. Excluding the compression system decreases the capital cost by almost the half regardless of the WH recovery system used, yet it plays in favour of the plant with ORC making the cost of H₂ cheaper by 0.29 $/kg_H2 in this case. Onboard H₂ production is a versatile process independent from the propulsion system ensuring the ship's safety and availability throughout a sea journey.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 124996"},"PeriodicalIF":10.1,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747816","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":"Probabilistic geo-referenced grid modeling: A Bayesian approach for integrating available system measurements","authors":"Domenico Tomaselli ,&nbsp;Paul Stursberg ,&nbsp;Michael Metzger ,&nbsp;Florian Steinke","doi":"10.1016/j.apenergy.2024.124913","DOIUrl":"10.1016/j.apenergy.2024.124913","url":null,"abstract":"<div><div>With the ongoing implementation of new climate targets, power distribution grids are increasingly integrating behind-the-meter photovoltaic (PV) systems, electric vehicle (EV) home chargers, and heat pumps (HPs). The integration of these solutions can often result in grid congestion issues, requiring appropriate mitigation measures. Designing these measures can be challenging in the absence of a digital and up-to-date model of the existing infrastructure, which is often the case at the low-voltage (LV) level. In this work, we introduce a novel two-stage Bayesian approach for establishing a probability distribution of geo-referenced power flow (PF)-ready grid models using available system measurements. We demonstrate the proposed approach in a residential region in Schutterwald, Germany. We find that integrating available system measurements can effectively enhance the quality of the distribution, yielding potential grid models that more accurately align with the existing infrastructure. Moreover, we showcase the practical utility of the proposed approach for assessing overvoltage within a specific grid segment subject to high rooftop PV adoption. While state-of-the-art baselines either fail to identify any overvoltage issues or are inconclusive, integrating available system measurements using the proposed approach offers a more reliable assessment.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 124913"},"PeriodicalIF":10.1,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747814","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":"When do different scenarios of projected electricity demand start to meaningfully diverge?","authors":"Casey D. Burleyson ,&nbsp;Zarrar Khan ,&nbsp;Misha Kulshresta ,&nbsp;Nathalie Voisin ,&nbsp;Mengqi Zhao ,&nbsp;Jennie S. Rice","doi":"10.1016/j.apenergy.2024.124948","DOIUrl":"10.1016/j.apenergy.2024.124948","url":null,"abstract":"<div><div>Resource adequacy studies look at balancing electricity supply and demand on 10- to 15-year time horizons while asset investment planning typically evaluates returns on 20- to 40-year time horizons. Projections of electricity demand are factored into the decision-making in both cases. Climate, energy policy, and socioeconomic changes are key uncertainties known to influence electricity demands, but their relative importance for demands over the next 10–40 years is unclear. The power sector would benefit from a better understanding of the need to characterize these uncertainties for resource adequacy and investment planning. In this study, we quantify when projected United States (U.S.) electricity demands start to meaningfully diverge in response to a range of climate, energy policy, and socioeconomic drivers. We use a wide yet plausible range of 21st century scenarios for the U.S. The projections span two population/economic growth scenarios (Shared Socioeconomic Pathways 3 and 5) and two climate/energy policy scenarios, one including climate mitigation policies and one without (Representative Concentration Pathways 4.5 and 8.5). Each climate/energy policy scenario has two warming levels to reflect a range of climate model uncertainty. We show that the socioeconomic scenario matters almost immediately – within the next 10 years, the climate/policy scenario matters within 25–30 years, and the climate model uncertainty matters only after 50+ years. This work can inform the power sector working to integrate climate change uncertainties into their decision-making.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 124948"},"PeriodicalIF":10.1,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747808","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":"An hourly-resolution capacity sharing market for generation-side clustered renewable-storage plants","authors":"Chuan Wang ,&nbsp;Wei Wei ,&nbsp;Laijun Chen ,&nbsp;Yuan Gong ,&nbsp;Shengwei Mei","doi":"10.1016/j.apenergy.2024.124964","DOIUrl":"10.1016/j.apenergy.2024.124964","url":null,"abstract":"<div><div>With the increasing penetration of renewable energy on the generation side, their volatility greatly challenges power balancing in the power grids. Deploying energy storage in wind farms, solar stations, and collection stations allow renewable plants to sell energy guided by the electricity price signal and increase their market revenues. This paper considers a representative scenario on the generation side. Wind farms and solar stations managed by different entities sell energy to a market through a collection station, aiming to maximize individual profits. Each renewable plant is equipped with a local battery in order to store energy and wait for a higher price. They can also rent some capacity from a shared energy storage unit at the collection station for better profitability. This paper designs a day-ahead hourly-resolution capacity rental market for the shared energy storage in the collection station and proposes an online operation policy for individual renewable plants. In the day-ahead market, renewable plants bid their needs of storage capacity in each time period based on the rental price and a batch of renewable power scenarios in the next day, and then the market is cleared at the Stackelberg equilibrium where the shared storage acts as the leader. Given the capacity obtained from the day-ahead market, each renewable plant obtains reference storage level trajectories in the pre-specified scenarios as experiences. In the real-time stage, the dispatch of local and shared storage units is determined from the conditional expectation of experiences, where the conditional distribution is generated by kernel regression using dynamic time warping as the distance measure. This proposed method does not rely on renewable power forecasts and is easy to implement. Numerical results validate the economy of the proposed method. Compared to the autarky mode, the profit of a renewable plant is increased by 40.6% on average. Compared to the ideal optimum, the optimality gap of the proposed method is 1.4% on average.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 124964"},"PeriodicalIF":10.1,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142756750","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":"The future of offshore wind power production: Wake and climate impacts","authors":"Simon C. Warder,&nbsp;Matthew D. Piggott","doi":"10.1016/j.apenergy.2024.124956","DOIUrl":"10.1016/j.apenergy.2024.124956","url":null,"abstract":"<div><div>Rapid deployment of offshore wind is expected within the coming decades to help meet climate goals. With offshore wind turbine lifetimes of 25–30 years, and new offshore leases spanning 60 years, it is vital to consider long-term changes in potential wind power resource at the farm planning stage. Such changes may arise from multiple sources, including climate change, and increasing wake-induced power losses. In this work, we investigate and compare these two sources of long-term change in wind power, for a case study consisting of 21 wind farms within the German Bight. Consistent with previous studies, we find a small but significant reduction in wind resource due to climate change by the end of the 21st century under the high-emission RCP8.5 scenario, compared with a historical period, with a mean power reduction (over an ensemble of seven climate models) of 2.1%. To assess the impact of wake-induced losses due to increasingly dense farm build-out, we model wakes within the German Bight region using an engineering wake model, under various stages of (planned) build-out corresponding to the years 2010–2027. By identifying clusters of wind farms, we decompose wake effects into long-range (inter-cluster), medium-range (intra-cluster) and short-range (intra-farm) effects. Inter-cluster wake-induced losses increase from 0 for the 2010 scenario to 2.5% for the 2027 scenario, with intra-cluster losses also increasing from 0 to 4.3%. Intra-farm losses are relatively constant, at around 13%. While the evolution of wake effects therefore outweighs the climate effect, and impacts over a shorter timescale, both factors are significant. We also find evidence of an interaction between the climate and wake effects. Both climate change and evolving wake effects must therefore be considered within resource assessment and wind farm planning.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 124956"},"PeriodicalIF":10.1,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747815","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":"Determination of trade-offs between 2G bioethanol production yields and pretreatment costs for industrially steam exploded woody biomass","authors":"Edwige Audibert ,&nbsp;Juliette Floret ,&nbsp;Adriana Quintero ,&nbsp;Frédéric Martel ,&nbsp;Caroline Rémond ,&nbsp;Gabriel Paës","doi":"10.1016/j.apenergy.2024.125028","DOIUrl":"10.1016/j.apenergy.2024.125028","url":null,"abstract":"<div><div>Lignocellulosic biomass, including wood, can be transformed into bioethanol using steam explosion as pretreatment to improve saccharification and fermentation steps. Pretreatment is however the most expensive part of the process in terms of CAPEX and OPEX and requires to be optimized. In order to evaluate the link between pretreatment efficiency and cost, three contrasted wood species (oak, poplar and spruce) were pretreated with continuous steam explosion at pilot-scale following full factorial designs. Response surfaces obtained were combined with an economic assessment to determine trade-offs aiming at maximizing both fermentable sugars released during the enzymatic hydrolysis step and bioethanol yield during the fermentation step as well as minimizing costs of pretreatment in an industrial context. Results showed that bioethanol yields were highly dependent on wood species and that high severities of pretreatment were not the most relevant to apply. Optimal conditions of pretreatment corresponding to 70 % and 48 % of bioethanol producible from oak and poplar, respectively, were defined. The desirability function that has been modelled thus helps designing adapted pretreatment conditions regarding bioethanol production and process cost.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"380 ","pages":"Article 125028"},"PeriodicalIF":10.1,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747810","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}