JournalTOCs

Journal of Renewable and Sustainable Energy
Journal Prestige (SJR): 0.44

Citation Impact (citeScore): 1
Number of Followers: 14

Hybrid journal (It can contain Open Access articles)
ISSN (Online) 1941-7012
Published by AIP

[29 journals]

A procedure set to construct the optimal energy saving retrofit strategy
for old residential buildings in China
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  Authors: Peng Wang, Cheng Ji, Ping Yu, Lei Huang
  Abstract: Journal of Renewable and Sustainable Energy, Volume 15, Issue 2, March 2023.
  A key strategy for lowering emissions and reducing the effects of climate change is to execute energy-saving retrofits in residential buildings. Despite extensive research on different retrofit pathways for building energy efficiency, the current retrofitting of the aged housing stock in China is still constrained by several factors, including occupant willingness, government financial situation, and low energy prices, so retrofitting projects are almost entirely government-led and most of the solutions of existing studies are not applicable. Therefore, a comprehensive optimization framework for low-budget compliance retrofit strategies in the Chinese context is urgently needed. In order to fill this gap, this study established a set of procedures for developing an optimal energy-saving retrofit scheme in old residential buildings in Nanjing city. The results showed that the optimal scheme can reduce 18.52% of residential building energy consumption in five central districts of Nanjing City, and the total energy saving is about 260.43 GW h. The study also showed that improving wall insulation and heating, ventilation, and air conditioning systems were the most efficient retrofit measures but came at a high cost. Setting a reasonable air conditioning target temperature was further identified as the most cost-effective retrofit measure. This study provided a mechanism for district-level retrofit planners to formulate a strategy that may take the performance of retrofitting on the environment and the economy into account while still adhering to code requirements.
  Citation: Journal of Renewable and Sustainable Energy
  PubDate: 2023-03-24T12:00:20Z
  DOI: 10.1063/5.0134055
Profit improvement strategy of electric vehicle charging stations sharing
carbon trading revenue
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  Authors: Hao Qiang, Wenqi Tang, Yanchun Hu, Xiaopeng Sun, Jianfeng Zheng
  Abstract: Journal of Renewable and Sustainable Energy, Volume 15, Issue 2, March 2023.
  With the development of electric vehicles (EVs), a large number of electric vehicle charging stations (CSs) have been rapidly rolled out to meet the charging demand of EVs. However, high construction costs and long payback periods motivate investigations to improve the profits of CSs. Considering the profit improvement of CSs and carbon emission reductions, this paper first proposes a carbon revenue model for CSs to participate in the carbon trading market. A charging price strategy is proposed to share the carbon revenue with EV users to reduce the charging cost of users, increase the charging income of CSs, and reduce carbon emissions. By describing the EV users' response to the charging price based on the fuzzy theory, this paper establishes the charging behavior model of EV users and solves the profit optimization of the dynamic charging price model by particle swarm optimization algorithm. Finally, the results of the simulation case demonstrate the effectiveness of the proposed strategy. A sensitivity analysis of various grid power purchase prices illustrates the difference between the fixed and dynamic charging price methods. The dynamic charging price method is superior, and under the power purchase price of 0.5 yuan/kWh, it can lower EV user charging costs by 16.25%, improve CS profits by 30.09%, and reduce carbon emissions by 74.68%.
  Citation: Journal of Renewable and Sustainable Energy
  PubDate: 2023-03-21T11:22:45Z
  DOI: 10.1063/5.0134546
Optimized allocation of renewable energy quota in Chinese provinces
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  Authors: Fugui Dong, Yuzhu Hou, Wei Zhang
  Abstract: Journal of Renewable and Sustainable Energy, Volume 15, Issue 2, March 2023.
  A fair and efficient renewable energy quota allocation scheme is essential for China to implement the Renewable Portfolio Standards policy. Therefore, based on the principles of fairness and efficiency, this paper comprehensively considers the differences among provinces and then proposes and adopts an improved zero-sum gains data envelopment analysis method to reallocate quotas. Furthermore, for verifying the superiority of the proposed method, this paper establishes a composite index based on the Gini coefficient and the Theil index to compare the rationality of the distribution results. Finally, this paper discusses the relevant advice for the development of renewable energy. The results validate that the proposed method is superior to the traditional method. Additionally, according to the final quota distribution scheme, there are fewer renewable energy quotas in the northern provinces and more in the southern provinces. The quota of most provinces is lower than 50 × 109 kWh, while Guangdong, Sichuan, Yunnan, Jiangsu, and Hunan are the five provinces with the most renewable energy quota of over 100 × 109 kWh. In general, this study provides a more rational renewable energy quota redistribution approach, which will help the government to establish an efficient and fair mechanism of renewable energy quota allocation.
  Citation: Journal of Renewable and Sustainable Energy
  PubDate: 2023-03-20T11:15:13Z
  DOI: 10.1063/5.0129872
Fuzzy logic for renewable energy recommendation and regional consumption
forecast using SARIMA and LSTM
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  Authors: Waldemar Bonventi, Eduardo P Godoy
  Abstract: Journal of Renewable and Sustainable Energy, Volume 15, Issue 2, March 2023.
  The use of renewable energy, notably solar and wind energy, has grown exponentially in Brazil. Consumers can generate their energy using renewable sources, whether interconnected to the distribution system (on-grid) or not (off-grid). In this paper, a fuzzy method is developed for the recommendation of solar and wind sources, for any location in the Brazilian territory. In many aspects, it can be viewed as a representation of human decision-making using sets and inference rules and also can be with vagueness and uncertainty, being very useful to idealize recommendation systems. Georeferenced and historical data were obtained from 2003 to 2019 on solar irradiation and wind speed, and electricity consumption until 2021. With the energy generation data from photovoltaic panels and wind turbines, this method allows us to propose installed areas by each technology and obtain the membership of fuzzy recommendation between solar, wind, both solar and wind, unfeasible or hybrid. In addition, a long short-term memory neural network and the seasonal autoregressive integrated moving average model were used to predict consumption for more than 30 months ahead, allowing the recalculation of fuzzy memberships and updating the installation area by respective technologies. As a result, the recommendation is given as the installed area (m2) of each technology per km2 of consumer units, as a function of the regional consumption density (MWh/km2). It can be concluded that it is possible to plan the viability of the type of renewable energy used, according to regional characteristics for smaller consumer units (farms, cooperatives, industries, consortiums), given the diversity of these factors in the huge Brazilian territory. This methodology is in line with the Brazilian Normative Resolution that authorizes the generation of energy by landowners.
  Citation: Journal of Renewable and Sustainable Energy
  PubDate: 2023-03-17T02:40:53Z
  DOI: 10.1063/5.0127408
Large eddy simulation of atmospheric boundary layer flow over complex
terrain in comparison with RANS simulation and on-site measurements under
neutral stability condition
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  Authors: Yi Han, Michael Karl Stoellinger, Huaiwu Peng, Lihui Zhang, Wei Liu
  Abstract: Journal of Renewable and Sustainable Energy, Volume 15, Issue 2, March 2023.
  Large eddy simulation (LES) of the atmospheric boundary layer (ABL) flow over complex terrain is presented with a validation using meteorological tower (met-tower) data through an improved neutral stability sampling approach. The proposed stability sampling procedure includes a condition based on the most-likely occurrence time-periods of the neutral ABL and reduces the variabilities of the conditional wind statistics calculated at the met-towers in comparison to our previous work. The ABL flow simulations are carried out over a potential wind site with a prominent hill based using the OpenFOAM-based simulator for on/off-shore wind farm applications by applying the Lagrangian-averaged scale-invariant dynamic sub-grid scale turbulence model. A low-dissipative scale-selective discretization scheme for the non-linear convection term in the LES governing equation is adopted implicitly to ensure both the second-order accuracy and bounded solution. The LES inflow is generated through a precursor method with a “tiling” approach based on the flow driving parameters obtained from a corresponding Reynolds-averaged Navier–Stokes (RANS) simulation. Overall, the averaged wind velocity profiles predicted by the LES approach at all met-tower locations show a similar tendency as the RANS results, which are also in reasonable agreement with the met-tower data. An obvious difference in wind speed standard deviation profiles is seen between LES and RANS, especially at regions downstream of the hill edge, where the LES shows under-predicted results at the highest measurement levels in comparison to the tower data. The computational costs of the LES are found to be about 20 times higher than the RANS simulations.
  Citation: Journal of Renewable and Sustainable Energy
  PubDate: 2023-03-13T11:22:58Z
  DOI: 10.1063/5.0133585
Publisher's Note: “Dynamic correlations of renewable-energy companies:
Evidence from a multilayer network model” [J. Renewable Sustainable
Energy 15, 015904 (2023)]
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  Authors: Cuixia Gao, Yu Mao, Juan Li, Mei Sun, Zhangyi Ji
  Abstract: Journal of Renewable and Sustainable Energy, Volume 15, Issue 2, March 2023.
  
  Citation: Journal of Renewable and Sustainable Energy
  PubDate: 2023-03-09T12:24:59Z
  DOI: 10.1063/5.0147931
Multi-timescale operations of nuclear-renewable hybrid energy systems for
reserve and thermal product provision
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  Authors: Jubeyer Rahman, Jie Zhang
  Abstract: Journal of Renewable and Sustainable Energy, Volume 15, Issue 2, March 2023.
  In this paper, an optimal operation strategy of a nuclear-renewable hybrid energy system (N-R HES), in conjunction with a district heating network, is developed within a comprehensive multi-timescale electricity market framework. The grid-connected N-R HES is simulated to explore the capabilities and benefits of N-R HES of providing energy products, different reserve products, and thermal products. An N-R HES optimization and control strategy is formulated to exploit the benefits from the hybrid energy system in terms of both energy and ancillary services. A case study is performed on the customized NREL-118 bus test system with high renewable penetrations, based on a multi-timescale (i.e., three-cycle) production cost model. Both day-ahead and real-time market clearing prices are determined from the market model simulation. The results show that the N-R HES can contribute to the reserve requirements and also meet the thermal load, thereby increasing the economic efficiency of N-R HES (with increased revenue ranging from 1.55% to 35.25% at certain cases) compared to the baseline case where reserve and thermal power exports are not optimized.
  Citation: Journal of Renewable and Sustainable Energy
  PubDate: 2023-03-08T12:07:07Z
  DOI: 10.1063/5.0138648
A comparative study to determine the photovoltaic annual energy generation
in the Brazilian Northeast
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  Authors: M. R. B. Alencar, B. A. Souza
  Abstract: Journal of Renewable and Sustainable Energy, Volume 15, Issue 2, March 2023.
  Renewable energy sources have been growing worldwide and solar energy is a significant part of such sources. An essential step in planning studies, including the problem of optimal location and sizing of photovoltaic (PV) generators, is estimating how much energy the panels will generate over time. For that, two aspects must be considered: the stochastic nature of the input variables and the way to calculate the generator's output power. A brief literature review identified 12 approaches to determine the PV output power. Therefore, this article compares such methods through actual meteorological data and generated energy over 1 year by a solar power plant located in a specific site in the Brazilian Northeast. An analysis is carried out on the influence of correlations between meteorological variables in estimating the generated energy. There is no comparative work in the literature on the analytical models for calculating the PV output power in conjunction with the correlation analysis. As expected, models that consider the influence of ambient temperature on output power performed better than those that do not. How the energy generated by the PV panel is estimated can influence the economic viability of a project since oversizing the PV system entails unnecessary additional costs. Monte Carlo simulations generate data samples used by the studied models for power output calculation. According to our findings, considering the correlation between meteorological variables reduces the error in estimating the generated energy by PV panels.
  Citation: Journal of Renewable and Sustainable Energy
  PubDate: 2023-03-01T01:49:07Z
  DOI: 10.1063/5.0130933