The present study investigates the impact of rotor solidity and blade profile on the self-starting characteristics and performance of H-Darrieus wind rotors (H-rotors) through subsonic wind tunnel experiments. Three symmetrical (NACA 0018) and three unsymmetrical (NREL S823) H-rotors were analyzed to determine the coefficient of static torque (Cts) and coefficient of power (Cp) across three solidities (σ = 0.25, 0.3, and 0.35) and two free stream wind speeds (Uf = 6 and 8 m/s). The findings revealed that the NREL S823-bladed H-rotor outperformed the NACA 0018-bladed H-rotor, displaying 13% and 11% higher Cts values at σ = 0.25 (Uf = 6 and 8 m/s), 9% and 9% at σ = 0.3 (Uf = 6 and 8 m/s), and 13% and 11% at σ = 0.35 (Uf = 6 and 8 m/s). The NREL S823-bladed H-rotor achieved a maximum Cp of 0.197 at σ = 0.3 and Uf = 8 m/s, which is 6% higher than the maximum Cp obtained by the NACA 0018-bladed H-rotor. Furthermore, the trend of maximum Cp values for both H-rotors followed the order of Cp, max σ = 0.25 < Cp, max σ = 0.3 > Cp, max σ = 0.35. Based on the experimental findings, it is inferred that the NREL S823-bladed H-rotor with a solidity of 0.3 is suitable for small-scale wind turbines.
{"title":"Experimental investigation of solidity and blade profile effects on H-Darrieus wind rotor: Performance and self-starting analysis","authors":"Kanthala Uma Reddy, Bachu Deb, B. Roy","doi":"10.1063/5.0159494","DOIUrl":"https://doi.org/10.1063/5.0159494","url":null,"abstract":"The present study investigates the impact of rotor solidity and blade profile on the self-starting characteristics and performance of H-Darrieus wind rotors (H-rotors) through subsonic wind tunnel experiments. Three symmetrical (NACA 0018) and three unsymmetrical (NREL S823) H-rotors were analyzed to determine the coefficient of static torque (Cts) and coefficient of power (Cp) across three solidities (σ = 0.25, 0.3, and 0.35) and two free stream wind speeds (Uf = 6 and 8 m/s). The findings revealed that the NREL S823-bladed H-rotor outperformed the NACA 0018-bladed H-rotor, displaying 13% and 11% higher Cts values at σ = 0.25 (Uf = 6 and 8 m/s), 9% and 9% at σ = 0.3 (Uf = 6 and 8 m/s), and 13% and 11% at σ = 0.35 (Uf = 6 and 8 m/s). The NREL S823-bladed H-rotor achieved a maximum Cp of 0.197 at σ = 0.3 and Uf = 8 m/s, which is 6% higher than the maximum Cp obtained by the NACA 0018-bladed H-rotor. Furthermore, the trend of maximum Cp values for both H-rotors followed the order of Cp, max σ = 0.25 < Cp, max σ = 0.3 > Cp, max σ = 0.35. Based on the experimental findings, it is inferred that the NREL S823-bladed H-rotor with a solidity of 0.3 is suitable for small-scale wind turbines.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41602038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a wind farm participates in automatic generation control (AGC), it should trace the real-time AGC signal from the independent system operator. To achieve a high responding performance, the real-time AGC signal should be rapidly distributed to multiple wind turbines (WTs) via an optimal dispatch. It is essentially a non-linear complex optimization due to the wake effect between different WTs. To solve this problem, a deep learning is employed to rapidly generate the dispatch scheme of AGC in a wind farm. The training data of deep learning is acquired from the optimization results of different anticipated tasks by genetic algorithm. In order to guarantee a reliable on-line decision of deep learning, the error of the regulation power command is corrected via an adjustment method of rotor speed and pitch angle for each WT. The effectiveness of the proposed technique is evaluated by a wind farm compared with multiple optimization methods.
{"title":"Deep learning for optimal dispatch of automatic generation control in a wind farm","authors":"Ruilin Chen, Lei Zhao, Xiaoshun Zhang, Chuan Li, Guiyuan Zhang, Tian Xu","doi":"10.1063/5.0153957","DOIUrl":"https://doi.org/10.1063/5.0153957","url":null,"abstract":"As a wind farm participates in automatic generation control (AGC), it should trace the real-time AGC signal from the independent system operator. To achieve a high responding performance, the real-time AGC signal should be rapidly distributed to multiple wind turbines (WTs) via an optimal dispatch. It is essentially a non-linear complex optimization due to the wake effect between different WTs. To solve this problem, a deep learning is employed to rapidly generate the dispatch scheme of AGC in a wind farm. The training data of deep learning is acquired from the optimization results of different anticipated tasks by genetic algorithm. In order to guarantee a reliable on-line decision of deep learning, the error of the regulation power command is corrected via an adjustment method of rotor speed and pitch angle for each WT. The effectiveness of the proposed technique is evaluated by a wind farm compared with multiple optimization methods.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43514735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Battery technologies offer promising solutions for renewable energy storage. However, selecting the most suitable battery requires proper investigation. This study introduces a multi-criteria decision-making framework for assessing batteries based on various criteria and uncertain data, by using a combined objective weighting method and an uncertainty-preserved complex proportional assessment (UP-COPRAS). The proposed weighting method ensures objectivity and fairness in the weighting result by integrating interval entropy and a gray relational coefficient-supported decision-making trial and evaluation laboratory to capture variation and correlation degrees among the criteria. After incorporating interval numbers with a compensatory ranking method, the UP-COPRAS prioritizes batteries in a simple yet rigorous way using uncertain evaluation data. To test the feasibility of the framework, an illustrative case was employed to assess four battery alternatives using a five-dimensional criteria system. Through results comparison, two mathematical contributions are confirmed. First, the combined objective weighting method uses the variation and correlation features of numerical data to determine criteria weights, which prevents subjective manipulation and eliminates bias in statistical analysis. Second, the UP-COPRAS preserves uncertainties throughout the evaluation, resulting in a rational decision output by eliminating interference in the original data.
{"title":"Evaluating batteries for renewable energy storage: A hybrid MCDM framework based on combined objective weights and uncertainty-preserved COPRAS","authors":"Yongxin Guan, Zhongfang Liu, Yunxi Du, Di Xu","doi":"10.1063/5.0153007","DOIUrl":"https://doi.org/10.1063/5.0153007","url":null,"abstract":"Battery technologies offer promising solutions for renewable energy storage. However, selecting the most suitable battery requires proper investigation. This study introduces a multi-criteria decision-making framework for assessing batteries based on various criteria and uncertain data, by using a combined objective weighting method and an uncertainty-preserved complex proportional assessment (UP-COPRAS). The proposed weighting method ensures objectivity and fairness in the weighting result by integrating interval entropy and a gray relational coefficient-supported decision-making trial and evaluation laboratory to capture variation and correlation degrees among the criteria. After incorporating interval numbers with a compensatory ranking method, the UP-COPRAS prioritizes batteries in a simple yet rigorous way using uncertain evaluation data. To test the feasibility of the framework, an illustrative case was employed to assess four battery alternatives using a five-dimensional criteria system. Through results comparison, two mathematical contributions are confirmed. First, the combined objective weighting method uses the variation and correlation features of numerical data to determine criteria weights, which prevents subjective manipulation and eliminates bias in statistical analysis. Second, the UP-COPRAS preserves uncertainties throughout the evaluation, resulting in a rational decision output by eliminating interference in the original data.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43762381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, solar heat with mid- and high-temperature collected by molten salt parabolic trough solar field was integrated into the boiler sub-system of the double reheat coal-fired power generation system. Three typical integration modes were, respectively, evaluated by energy and exergy perspectives in terms of solar-generated electricity and solar energy conversion efficiency. Integration modes I–III utilized solar heat to preheat the inlet superheated steam, inlet reheated steam and inlet double reheated steam, respectively. Based on the case study through energy evaluation, it indicated that integrating solar energy with lower temperature led to higher solar-generated electricity, higher solar-to-solar heat efficiency, and higher solar-to-electricity efficiency. Integration mode I was unreasonably regarded superior to the other two, because the energy evaluation method ignored the quality of solar energy and mistakenly regarded the efficiency of solar heat to solar-generated electricity as the cycle efficiency. As an update, exergy evaluation takes both energy quantity and energy quality into consideration by regarding the efficiency of solar heat exergy to solar-generated electricity as the cycle exergy efficiency. It indicated that integration mode II was more recommended, with the highest solar-to-solar heat exergy efficiency and solar-to-electricity efficiency being 34.0% and 24.7%, respectively. The corresponding aperture area and solar-generated electricity are 5.7 × 105 m2 and 136.1 MW, respectively.
{"title":"Energy and exergy evaluations of solar-aided double reheat coal-fired power generation system","authors":"Junjie Wu, Jiaming Wu, Yu-Ry Han","doi":"10.1063/5.0160837","DOIUrl":"https://doi.org/10.1063/5.0160837","url":null,"abstract":"In this paper, solar heat with mid- and high-temperature collected by molten salt parabolic trough solar field was integrated into the boiler sub-system of the double reheat coal-fired power generation system. Three typical integration modes were, respectively, evaluated by energy and exergy perspectives in terms of solar-generated electricity and solar energy conversion efficiency. Integration modes I–III utilized solar heat to preheat the inlet superheated steam, inlet reheated steam and inlet double reheated steam, respectively. Based on the case study through energy evaluation, it indicated that integrating solar energy with lower temperature led to higher solar-generated electricity, higher solar-to-solar heat efficiency, and higher solar-to-electricity efficiency. Integration mode I was unreasonably regarded superior to the other two, because the energy evaluation method ignored the quality of solar energy and mistakenly regarded the efficiency of solar heat to solar-generated electricity as the cycle efficiency. As an update, exergy evaluation takes both energy quantity and energy quality into consideration by regarding the efficiency of solar heat exergy to solar-generated electricity as the cycle exergy efficiency. It indicated that integration mode II was more recommended, with the highest solar-to-solar heat exergy efficiency and solar-to-electricity efficiency being 34.0% and 24.7%, respectively. The corresponding aperture area and solar-generated electricity are 5.7 × 105 m2 and 136.1 MW, respectively.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45005691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the increasing dominance of electricity retailers in the electricity market, it has become a new trend for the data center (DC) to participate in sales-side transactions. However, data center electricity retailers (DCERs) and DCs that purchase electricity by DCERs, as different stakeholders, will inevitably face conflicts of interest. To promote the benefit distribution of DCs and DCERs to achieve a win–win situation, our study proposes an optimal scheduling method based on multiple games and establishes a mixed game model by integrating the master–slave game method and the cooperative game method, in which DCERs take profit maximization as the optimization goal, while Internet DCs take the lowest total cost as the optimization goal. The master–slave game is adopted between the DCER and the DC, and the cooperative game is adopted among the members of the DC. The benefits are distributed through Nash bargaining. The model is solved by using the particle swarm optimization algorithm combined with the alternating direction method of multipliers. To demonstrate the effectiveness of our proposed method, we provide an illustrative example that showcases its ability to not only increase DCER revenue by 136.04% but also decrease total DC costs by 9.39%. As a result, our method facilitates a more equitable distribution of cooperation revenues.
{"title":"Optimal scheduling of data centers based on multiple games","authors":"Jiujiu Sun, Y. Che, Zhi-hao Zheng","doi":"10.1063/5.0160474","DOIUrl":"https://doi.org/10.1063/5.0160474","url":null,"abstract":"With the increasing dominance of electricity retailers in the electricity market, it has become a new trend for the data center (DC) to participate in sales-side transactions. However, data center electricity retailers (DCERs) and DCs that purchase electricity by DCERs, as different stakeholders, will inevitably face conflicts of interest. To promote the benefit distribution of DCs and DCERs to achieve a win–win situation, our study proposes an optimal scheduling method based on multiple games and establishes a mixed game model by integrating the master–slave game method and the cooperative game method, in which DCERs take profit maximization as the optimization goal, while Internet DCs take the lowest total cost as the optimization goal. The master–slave game is adopted between the DCER and the DC, and the cooperative game is adopted among the members of the DC. The benefits are distributed through Nash bargaining. The model is solved by using the particle swarm optimization algorithm combined with the alternating direction method of multipliers. To demonstrate the effectiveness of our proposed method, we provide an illustrative example that showcases its ability to not only increase DCER revenue by 136.04% but also decrease total DC costs by 9.39%. As a result, our method facilitates a more equitable distribution of cooperation revenues.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43202148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hang Tan, Shengmao Lin, Xuefang Xu, Peiming Shi, Ruixiong Li, Shuying Wang
Missing data recovery plays a critical role in improving the data quality of wind speed in wind farms, and numerous methods have been proposed to address this issue. However, most of them suffer from the inability to fully use the information of known data, and thus, poor performance of recovery is usually achieved. In this paper, we propose a missing data recovery method based on spatial-temporal tensor decomposition. The proposed method rearranges the whole data based on discrete wavelet transform to construct a four-dimensional tensor of “site × week × scale × hour” for representing the spatial and temporal correlation of wind speed. A completeness tensor is estimated to impute missing data based on Tucker decomposition and the nonlinear conjugate gradient algorithm. The proposed method not only inherits the advantages of imputation methods based on the matrix pattern but also well mines the spatial and temporal inherent correlation of wind speed. Wind speed data of a wind farm are used to verify the effectiveness of the proposed method. The results show that the proposed method recovers missing data with much smaller mean absolute error and root mean square error and requires less effort for recovering missing data of fragmented or continuously, compared with the traditional methods.
{"title":"Missing data recovery of wind speed in wind farms: A spatial-temporal tensor decomposition approach","authors":"Hang Tan, Shengmao Lin, Xuefang Xu, Peiming Shi, Ruixiong Li, Shuying Wang","doi":"10.1063/5.0144648","DOIUrl":"https://doi.org/10.1063/5.0144648","url":null,"abstract":"Missing data recovery plays a critical role in improving the data quality of wind speed in wind farms, and numerous methods have been proposed to address this issue. However, most of them suffer from the inability to fully use the information of known data, and thus, poor performance of recovery is usually achieved. In this paper, we propose a missing data recovery method based on spatial-temporal tensor decomposition. The proposed method rearranges the whole data based on discrete wavelet transform to construct a four-dimensional tensor of “site × week × scale × hour” for representing the spatial and temporal correlation of wind speed. A completeness tensor is estimated to impute missing data based on Tucker decomposition and the nonlinear conjugate gradient algorithm. The proposed method not only inherits the advantages of imputation methods based on the matrix pattern but also well mines the spatial and temporal inherent correlation of wind speed. Wind speed data of a wind farm are used to verify the effectiveness of the proposed method. The results show that the proposed method recovers missing data with much smaller mean absolute error and root mean square error and requires less effort for recovering missing data of fragmented or continuously, compared with the traditional methods.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43856198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaowei Meng, E. Zhai, Cheng-shun Xu, Yilong Sun, Shigang Shi
The offshore wind turbine (OWT) is a high-rise structure that is extremely sensitive to dynamic loads such as wind, waves, and earthquakes. Therefore, in order to avoid resonance, it is extremely important to accurately calculate the natural frequencies of the OWT at the design stage. The integrated finite element model of DTU (Technical University of Denmark) 10 MW OWT is established based on OpenSees finite element software. The correctness of the superstructure simplification method is confirmed by comparing it to the frequencies calculated by the wind turbine dynamic analysis software HAWC2 for the single-blade model and the fixed constraint model at the bottom of the tower. The frequencies and mode shapes calculated by the overall model are compared with those calculated by the fixed model at the mudline and the concentrated mass model at the top of the tower. Then, the parameters of the soil shear modulus G0, void ratio e, pile embedded length L, pile diameter D, water depth, and blade stiffness are analyzed using the lumped mass model and the blade model at the top of the tower, and some regular conclusions about the variation of natural frequency with the parameters are obtained. Finally, based on the blade model, the influence of short-term cyclic loading on the natural frequency for OWT monopiles in dense sand is studied. The results indicate that the pile-soil interaction has a significant impact on the natural frequencies, the blade has a higher influence on the second bending frequency of the OWT, and the front-after direction is more significantly impacted than the side-side direction. The short-term cyclic loading are unlikely to significantly affect natural frequency for OWT monopiles in dense sand.
{"title":"Research on the natural frequencies of an integrated offshore wind turbine model considering blades","authors":"Xiaowei Meng, E. Zhai, Cheng-shun Xu, Yilong Sun, Shigang Shi","doi":"10.1063/5.0147098","DOIUrl":"https://doi.org/10.1063/5.0147098","url":null,"abstract":"The offshore wind turbine (OWT) is a high-rise structure that is extremely sensitive to dynamic loads such as wind, waves, and earthquakes. Therefore, in order to avoid resonance, it is extremely important to accurately calculate the natural frequencies of the OWT at the design stage. The integrated finite element model of DTU (Technical University of Denmark) 10 MW OWT is established based on OpenSees finite element software. The correctness of the superstructure simplification method is confirmed by comparing it to the frequencies calculated by the wind turbine dynamic analysis software HAWC2 for the single-blade model and the fixed constraint model at the bottom of the tower. The frequencies and mode shapes calculated by the overall model are compared with those calculated by the fixed model at the mudline and the concentrated mass model at the top of the tower. Then, the parameters of the soil shear modulus G0, void ratio e, pile embedded length L, pile diameter D, water depth, and blade stiffness are analyzed using the lumped mass model and the blade model at the top of the tower, and some regular conclusions about the variation of natural frequency with the parameters are obtained. Finally, based on the blade model, the influence of short-term cyclic loading on the natural frequency for OWT monopiles in dense sand is studied. The results indicate that the pile-soil interaction has a significant impact on the natural frequencies, the blade has a higher influence on the second bending frequency of the OWT, and the front-after direction is more significantly impacted than the side-side direction. The short-term cyclic loading are unlikely to significantly affect natural frequency for OWT monopiles in dense sand.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44242704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Erren Yao, Like Zhong, Ruixiong Li, Guang Xi, Hansen Zou, Huanran Wang
The advantages of compressed air energy storage (CAES) have been demonstrated by the trigeneration system with the characteristic of high penetration of renewable energy. However, since the irreversible loss of compression heat occurs during the overall operation processes of CAES, the development of CAES with high energy efficiency has been hindered by the conventional conversion pathway of compression heat. Therefore, a trigeneration system integrated with compressed air and chemical energy storage is proposed in this study to improve energy utilization efficiency. The compression heat is converted into H2 and CO via the endothermic methanol decomposition reaction to improve its energy level during the charging process, and then the syngas production can be used for air preheating during the discharging process. The parametric analysis is first performed to investigate the technical and economic feasibility of the system. Subsequently, the multi-objective optimization is conducted to identify the tradeoffs in the thermo-economic performance of the system and acquire the optimal values of operating parameters. Notably, the proposed system with a computed exergy efficiency of 43.31% and levelized cost of energy (LCOE) of 97.53 $/MWh is selected as the most compromise solution by the decision maker of Technique for Order Preference by Similarity to an Ideal Solution among the Pareto optimum fronts, which are 8.47% higher than the exergy efficiency and 7.39 $/MWh lower than the LCOE under the design conditions.
{"title":"Preliminary design and techno-economic assessment of a trigeneration system integrated with compressed air and chemical energy storage","authors":"Erren Yao, Like Zhong, Ruixiong Li, Guang Xi, Hansen Zou, Huanran Wang","doi":"10.1063/5.0144607","DOIUrl":"https://doi.org/10.1063/5.0144607","url":null,"abstract":"The advantages of compressed air energy storage (CAES) have been demonstrated by the trigeneration system with the characteristic of high penetration of renewable energy. However, since the irreversible loss of compression heat occurs during the overall operation processes of CAES, the development of CAES with high energy efficiency has been hindered by the conventional conversion pathway of compression heat. Therefore, a trigeneration system integrated with compressed air and chemical energy storage is proposed in this study to improve energy utilization efficiency. The compression heat is converted into H2 and CO via the endothermic methanol decomposition reaction to improve its energy level during the charging process, and then the syngas production can be used for air preheating during the discharging process. The parametric analysis is first performed to investigate the technical and economic feasibility of the system. Subsequently, the multi-objective optimization is conducted to identify the tradeoffs in the thermo-economic performance of the system and acquire the optimal values of operating parameters. Notably, the proposed system with a computed exergy efficiency of 43.31% and levelized cost of energy (LCOE) of 97.53 $/MWh is selected as the most compromise solution by the decision maker of Technique for Order Preference by Similarity to an Ideal Solution among the Pareto optimum fronts, which are 8.47% higher than the exergy efficiency and 7.39 $/MWh lower than the LCOE under the design conditions.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49659437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The availability of quality power is a foremost need for a nation's sustainable development. The government of Bangladesh has the vision to be a high-income country by 2041. To meet the power challenges in the near future associated with the vision, there should be a well-planned master plan for the power system. Bangladesh has a power system master plan (PSMP) up to 2041. However, it is unclear whether the PSMP is the most adaptable plan considering different power generation scenarios by considering the demand, generation, and emissions. Hence, the long-range energy alternative planning (LEAP) tool is employed for scenario analyses of Bangladesh's electricity sector from 2022 to 2041. On the demand side, the final electricity demand has been projected as 335.25, 314.76, 376.59, and 398.10 TWh in 2041 for business-as-usual (BAU), low growth (LG), medium growth (MG), and high growth (HG) scenarios, respectively. Considering technical and environmental parameters, eight generation scenarios are also analyzed on the supply side. The analysis projected 58,230 MW capacity for BAU and LG under P1 to P8 generation scenarios and 68,830 MW capacity for MG and HG under Q1–Q8 generation scenarios in 2041. In terms of emission in 2041, 167.4 and 165 MMt CO2 equivalent are found for the P8 scenario in the case of BAU and LG. In Q8, for MG and HG, the emissions are found to be 206.5 and 209.4 MMt CO2 equivalent, respectively. The generation scenarios of P8 for BAU and LG and Q8 for MG and HG are found to be suitable ones with respect to energy reliability and reduced emission. A similar analysis could also be performed to identify suitable power generation plans for other developing countries.
{"title":"Analysis of demand, generation, and emission for long-term sustainable power system planning using LEAP: The case of Bangladesh","authors":"M. Sahabuddin, Imran Khan","doi":"10.1063/5.0149307","DOIUrl":"https://doi.org/10.1063/5.0149307","url":null,"abstract":"The availability of quality power is a foremost need for a nation's sustainable development. The government of Bangladesh has the vision to be a high-income country by 2041. To meet the power challenges in the near future associated with the vision, there should be a well-planned master plan for the power system. Bangladesh has a power system master plan (PSMP) up to 2041. However, it is unclear whether the PSMP is the most adaptable plan considering different power generation scenarios by considering the demand, generation, and emissions. Hence, the long-range energy alternative planning (LEAP) tool is employed for scenario analyses of Bangladesh's electricity sector from 2022 to 2041. On the demand side, the final electricity demand has been projected as 335.25, 314.76, 376.59, and 398.10 TWh in 2041 for business-as-usual (BAU), low growth (LG), medium growth (MG), and high growth (HG) scenarios, respectively. Considering technical and environmental parameters, eight generation scenarios are also analyzed on the supply side. The analysis projected 58,230 MW capacity for BAU and LG under P1 to P8 generation scenarios and 68,830 MW capacity for MG and HG under Q1–Q8 generation scenarios in 2041. In terms of emission in 2041, 167.4 and 165 MMt CO2 equivalent are found for the P8 scenario in the case of BAU and LG. In Q8, for MG and HG, the emissions are found to be 206.5 and 209.4 MMt CO2 equivalent, respectively. The generation scenarios of P8 for BAU and LG and Q8 for MG and HG are found to be suitable ones with respect to energy reliability and reduced emission. A similar analysis could also be performed to identify suitable power generation plans for other developing countries.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":"355 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41257198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhao Xin-gang, Lu Wenjie, Wang Wei, Hu Shuran, Zuo Yi
A renewable portfolio standard is implemented to promote the development of renewable energy at a minimum cost through tradable green certificate market mechanism. Formulating a scientific and feasible renewable energy quota allocation scheme helps RPS function smoothly and optimize resource allocation. This paper proposed a bi-level programming model combined with entropy weight method to allocate renewable portfolio standard quotas with provincial heterogeneity and stakeholders' behavior, and an optimized quota allocation scheme among China's 30 provinces in 2020 was obtained. By comparing with the government's issued scheme, the following were the results under the optimized scheme: (1) Quotas in most provinces have increased, and the responsibility for renewable electricity generation is shared with the provinces with developed economy and well-constructed transmission facilities, where electricity producers can meet the quotas by purchasing tradable green certificate. (2) Quota allocation has positive effects on energy, economy, and environment. Specifically, the non-hydro renewable electricity generation increased by 43.8%, the non-hydro renewable electricity producers' profit increased by 18.4%, and the environmental pollution cost reduced by 27.9%. (3) Quota allocation equity measured by the environmental Gini coefficient increased by 14.3%. Based on these findings, some policy implications related to quota allocation and renewable portfolio standard's institutional arrangement have been put forward.
{"title":"How to optimize allocation of renewable portfolio standards for renewable energy development in China?","authors":"Zhao Xin-gang, Lu Wenjie, Wang Wei, Hu Shuran, Zuo Yi","doi":"10.1063/5.0135705","DOIUrl":"https://doi.org/10.1063/5.0135705","url":null,"abstract":"A renewable portfolio standard is implemented to promote the development of renewable energy at a minimum cost through tradable green certificate market mechanism. Formulating a scientific and feasible renewable energy quota allocation scheme helps RPS function smoothly and optimize resource allocation. This paper proposed a bi-level programming model combined with entropy weight method to allocate renewable portfolio standard quotas with provincial heterogeneity and stakeholders' behavior, and an optimized quota allocation scheme among China's 30 provinces in 2020 was obtained. By comparing with the government's issued scheme, the following were the results under the optimized scheme: (1) Quotas in most provinces have increased, and the responsibility for renewable electricity generation is shared with the provinces with developed economy and well-constructed transmission facilities, where electricity producers can meet the quotas by purchasing tradable green certificate. (2) Quota allocation has positive effects on energy, economy, and environment. Specifically, the non-hydro renewable electricity generation increased by 43.8%, the non-hydro renewable electricity producers' profit increased by 18.4%, and the environmental pollution cost reduced by 27.9%. (3) Quota allocation equity measured by the environmental Gini coefficient increased by 14.3%. Based on these findings, some policy implications related to quota allocation and renewable portfolio standard's institutional arrangement have been put forward.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42782485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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