Use Of Clean Energy Research Articles

A PVAR dynamic correlation appraisal of China’s carbon emissions in conjunction with economic growth and clean energy use

This study aims to explore the dynamic relationship among economic growth, clean energy, and carbon dioxide (CO2) emissions in China. The indicators of economic growth, clean energy, CO2 emissions, fixed assets investment, and research and development intensity of 30 provinces and municipalities for the period of 2005–2019 in China have been investigated by Panel Vector Autoregression model (PVAR). To further explore regional differences, three types of regions were classified by K-means cluster analysis. The results show that clean energy has a positive impact on economic growth in China; Clean energy reduces CO2 emissions in Region II while others do not; Both fixed assets investment and research and development promote clean energy development; The dynamic relationship between the 5 indicators varies across regions. Various regions in China should combine their development characteristics and location advantages, increase capital investment and research and development input in clean energy, strengthen environmental regulations, and improve the energy consumption structure.

Feasibility Study for the Implementation of Photovoltaic Panels in Public Transportation in Barranquilla

The conservation of the environment and the use of clean energy is one of the main concerns of international governments. In this sense, encouraging the use of clean energy, both locally, nationally, and internationally, contributes to the development of countries. In this order of ideas, this work was motivated with the purpose of contributing to the scope of the SDGs at the national level, specifically, in the city of Barranquilla (Colombia). The thermal sensation inside the public transport in Barranquilla limits the quality of the service and, consequently, the satisfaction of the users due to the high temperatures (T > 30 °C). To address this problem, it is necessary to implement air conditioning systems that improve comfort conditions and are friendly to the environment. In this study, the feasibility of implementing photovoltaic panels as an alternative energy source for air conditioning units in public transport was examined. The study began with the dimensioning of the photovoltaic system and the accumulation of energy. A stress analysis was then performed on the chassis and bodywork of a selected bus. Finally, the work was evaluated based on the results obtained from the dimensioning of the mentioned systems. The results confirmed that a photovoltaic generator with a power of 35.88 kW and an energy storage capacity of 481,204 Ah is required. Additionally, the results also confirmed that the chassis and bodywork are structurally sound. The economic analysis carried out confirmed a Net Present Value and an Internal Rate of Return of 22,936 USD and 11.05%, respectively. The energy alternative proposed for the transport sector, based on the application of photovoltaic energy, constitutes an advance to meet international objectives in relation to the use of clean energy.

3D FE modeling of a real-world energy piled foundation

3D FE modeling of a real-world energy piled foundation

Does technological innovation bring better air quality?

This paper analyses the interrelation between technological innovation (TI) and air quality (AQ) using the bootstrap rolling-window subsample Granger test for China. We find that TI has a twofold impact on AQ. On the one hand, TI brings better AQ. This result proves the technique effect, indicating that TI can improve AQ by directly reducing air pollutants emissions and facilitating clean energy use. On the other hand, TI can make AQ worse when TI mainly focuses on utilising fossil fuels to expand production, which proves the scale effect. In turn, AQ can also influence TI; the direction of the influence is dependent on the severity of air pollution and the government’s response. This study provides important policy implications for coordinating innovation and environmental conservation to achieve sustainable development.

The impacts of clean energy policies on air pollutants and CO2 emission reduction in Shaanxi, China

In response to environmental problems, China has implemented many policies to control its emission of air pollutants and CO2. As a significant source of pollutant emissions, energy use has received special attention. Shaanxi Province is a region of China with major thermal power generation, which consumes a large amount of fossil fuel and causes severe deterioration in ambient air quality. However, it is rich in natural resources that could support the development of solar energy, wind energy, and other renewable clean energies, making it a typical example of a region suitable for energy structure transformation. On the basis of environmental statistical data, field surveys, and data from the Shaanxi Provincial Bureau of Statistics, this study developed an inventory of anthropogenic source emissions of seven pollutants in 2017 in Shaanxi Province. In accordance with the established inventory, various scenarios were considered to analyze the impact of energy structure transformation on air pollutant emissions. In comparison with the Business-as-Usual scenario, the comprehensive clean energy use scenario reduced SO2, NOx, CO, PM10, PM2.5, VOCs, NH3 and CO2 emissions by 32.50%, 33.10%, 14.56%, 26.64%, 16.72%, 2.88%, 4.36% and 36.85%, respectively. Ambitious development of clean energy, such as wind and solar, could greatly reduce the emission of air pollutants, especially CO2, SO2 and NOx, that are derived mainly from fossil fuel combustion, showing that strict control of the energy structure could reduce pollutant emissions. This work is important for quantifying the impact of energy restructuring on regional air quality and providing pollution control policies for environmental managers.

Indoor exposure to polycyclic aromatic hydrocarbons associated with solid fuel use in rural China.

Polycyclic aromatic hydrocarbons (PAHs) are widespread environmental contaminants associated with various health risks including lung cancer. Indoor exposure to PAHs, particularly from the indoor burning of fuels, is significant; however, long-term large-scale assessments of indoor PAHs are hampered by high costs and time-consuming in field sampling and laboratory experiments. A simple fuel-based approach and statistical regression models were developed as a trial to predict indoor BaP, as a typical PAH, in China, and consequently spatiotemporal variations in indoor BaP and indoor exposure contributions were discussed. The results show that the national population-weighted indoor BaP concentration has decreased substantially from 46.1ng/m3 in 1992 to 6.60ng/m3 in 2017, primarily due to the increased use of clean energies for cooking and heating. Indoor BaP exposure contributed to > 70% of the total inhalation exposure in most cities, particularly in regions where solid fuels are widely utilized. With limited experimental observation data in building statistical models, quantitative results of the study are associated with high uncertainties; however, the study undoubtedly supports effective countermeasures on indoor PAHs from solid fuel use and the importance of promoting clean household energy usage to improve household air quality.

SUMMER：A small modular lead-bismuth-cooled fast reactor for mobile energy supply

The pursuit of small modular reactors (SMRs) has become a trend in this century due to their potential to expand the use of clean and reliable nuclear energy to a broader range of customers and applications. One promising candidate is the lead-based fast reactor. A mobile energy supply unit based on a lead-bismuth-cooled, pool-type, small modular fast reactor named SUstainable Modular Mobile Enhanced Reactor (SUMMER) is being developed by the University of Science and Technology of China (USTC) and China Nuclear Power Technology Research Institute. SUMMER is intended to provide stable energy supply in the field or remote regions, which are potential application scenarios for SMRs. Key features of SUMMER include a long lifetime of over a decade, mobility (transportable by truck or train), and inherent safety. In this paper, the reactor design is completed under the constraints of fulfilling these features, such as the limitation of size and lifetime. Neutronic and thermal-hydraulic analyses are implemented, as well as safety analyses of the reactor under several typical accidents. The results show that the design meets all these criteria and that the reactor has an adequate safety margin under both steady-state and transient conditions.

How military spending, economic growth, and renewable energy impacts ecological footprints in Next Eleven nations.

The objective of this study is to investigate the association between military spending and environmental sustainability within the N-11 countries. There exists a strong correlation between sustainable economic expansion and energy consumption, which in turn results in the generation of elevated levels of carbon emissions. Moreover, it is plausible that a correlation exists between military spending and the degradation of the environment. The primary objective of this study is to examine the emissions of carbon and emissions of greenhouse gases in the N-11 countries, as these nations exhibit comparatively elevated levels of such emissions. Therefore, this study examines the correlation among economic growth, militarization, renewable energy, and environment in the Next Eleven nations from 1990 to 2022. The cross-section autoregressive distributed lag (CS-ARDL) model is employed to analyze the enduring and immediate connections between variables. Empirical evidence indicates that a country's environment is positively influenced by GDP and militarization. The escalation of military capital intensity has exacerbated the environmental damage. Increasing the adoption of renewable energy sources can mitigate negative environmental impacts over time. This study proposes policy recommendations for sustainable development, including reducing militarization and improving the use of clean energy.

Lead-free and highly-stable double perovskite Cs2SnClXI6-X microcrystals for efficient photocatalytic degradation

In order to protect water bodies and prevent water pollution, the direct use of clean solar energy to degrade the organic dyes in industrial wastewater into innoxious products is a potential strategy and a trending topic. Recently, the lead halide perovskites have been intensively investigated as photocatalysts on account of their unique photoelectric properties. Unsatisfactorily, the lead toxicity and instability of these materials cause irreversible harm to the ecology and low long-term degradation efficiency, limiting their practical applications. For the first time, lead-free double perovskite Cs2SnClXI6-X microcrystals were prepared by solution supersaturation recrystallization method for the photocatalytic degradation of Sudan Red III. The optical band gaps of the Cs2SnClXI6-X microcrystals were adjustable from 4.48 to 1.34 eV upon halogen regulation, while the photodegradation performance of Cs2SnCl4.1I1.9 was even much higher than the recently reported composite photocatalysts under similar conditions. Furthermore, the recycling and storage experiments demonstrated the reusability and excellent environmental stability of the as prepared Cs2SnClXI6-X microcrystals. Based on the results of the free radical trapping tests and electron paramagnetic resonance measurements, the mechanism for the photocatalytic degradation process were discussed in details.

Clean energy use and subjective and objective health outcomes in rural China

This study analyses the impact of clean energy use on rural residents' subjective health outcomes (self-reported health status, health change, and discomfort) and objective health outcomes (bronchitis, asthma, medical expenditure, and fitness expenditure). Using an inverse probability-weighted regression adjustment estimator and the 2018 China Family Panel Studies data, we address the selection bias associated with clean energy use and estimate the treatment effects. The empirical results show that farmers using clean energy (liquid gas, natural gas, methane, solar energy, or electricity) as the primary cooking fuel report improved health, a lower probability of physical discomfort, and higher fitness expenditures than non-users. Clean energy use does not significantly affect self-reported health, the probability of having bronchitis and asthma, or medical expenditures. The health effects of clean energy use on men differ from those on women; they also vary across different economic strata. We also find that farmers’ decisions to use clean energy are positively associated with their educational level, household income, whether they rent farmland, and their happiness levels but are negatively related to their age, family size, whether they own real estate, and the ratio of elders in their household.

Greenhouse gas emissions along the value chain in palm oil producing systems: A case study of Cameroon

The agricultural sector is the second most emitting sector globally, contributing about 18% of total global greenhouse gas (GHG) emissions. Multipurpose high in-demand commodities like palm oil contribute significantly to these emissions. The Roundtable on Sustainable Palm Oil (RSPO) with an objective to make the palm oil sector sustainable, developed a new tool to quantify carbon emissions from palm oil mills. The PalmGHG tool has been used in Southeast Asia to measure carbon emissions from palm oil production and for palm oil certification. However, no studies have used the tool to evaluate GHG emissions from palm oil mills in sub-Saharan Africa, which contributes about 24% of global palm oil production and is home to one of the last remaining primary forests in the world. In this study, we quantify GHG emissions along the crude palm oil (CPO) life cycle in a growing palm oil producing region in Cameroon. We use the RSPO PalmGHG accounting tool, to identify sources of CO2 emissions and quantify them in tons of CO2 equivalent. Six mills across the South West and Center regions of Cameroon were sampled. We found that the sources of carbon emissions from our sampled mills in decreasing order of magnitude are land conversion (78%), palm oil mill effluent (21%), fertilizer use (0.9%), mill fuel combustion (0.1%) and grid electricity utilization (0.04%). The average GHG emissions per ton of crude palm oil produced were exceptionally high at 22.3 tCO2e compared to other palm oil producing regions in the world such as Indonesia with only 1.6 tCO2e/ton of CPO. In addition, we found that planting oil palm on previously logged land instead of primary forest conversion could prevent field emissions by up to about 89% and by up to about 69% for replanting old oil palm stands. Intensification measures like improving palm oil mill extraction rates and improving yields would drastically reduce emissions per ton of crude palm oil produced. Although land conversion associated with deforestation remains the major source of palm oil GHG emissions, farm and mill practices such as reduction in fertilizer use, biogas capture and use of clean energy could help reduce emissions in the long run.

Dynamic disparities in clean energy use across rural-urban, regional, and ethnic boundaries in China.

The consequences of relying on solid fuels are disproportionately borne by minorities, the marginalized, and rural communities. However, the social disparities in transitioning from polluting energy to clean energy are not well understood. We track changes in the main energy source used for cooking among Chinese households between 2010 and 2018. We find that the proportion of households who rely on clean energy increased from 53.7% in 2010 to 80.1% in 2018. We detect substantial disparities in clean energy use between rural and urban areas, across regions, and between ethnic minorities and the Han majority. Urban status, regional variations, and household characteristics entirely accounted for the observed ethnic differences in clean energy use. Over time, disparities across rural-urban, regional, and ethnic boundaries declined, and household characteristics became irrelevant to the ethnic differences. Therefore, China's efforts to mitigate the imbalance in socioeconomic development also reduced ethnic inequalities in clean energy use.

Distributed low-carbon operational optimization model of an integrated energy system based on ladder carbon trading and integrated demand response

ABSTRACT Integrated energy system (IES) has become significant in the global energy revolution because of its unique advantage of promoting clean energy use and improving energy efficiency. However, its low-carbon operational optimization and capacity allocation challenges have sharply increased because, as its scale continuously grows, its inherent strongly coupled multi energy flow and high nonlinearity characteristics have become more prominent. This study proposes a distributed low-carbon operational optimization mechanism for an IES using integrated demand response (IDR) and ladder carbon trading (LCT). First, a low-carbon IES was modeled as a coupled model between energy operators (EO) that contain combined cooling, heating, and power systems (CCHP) and flexible users (FU) based on the Stackelberg game. Second, the operational optimization model was formulated as a source-load synergistic operation scheduling mechanism based on IDR and the LCT. Finally, the strategy of each stakeholder was obtained using a modified distributed algorithm of genetic algorithm nested quadratic programming (GA-QP). The effectiveness of the proposed model was verified through a case study. The economic benefits for each stakeholder improved, as confirmed through the experimental results. The energy cost of the FU decreased by 4.42%, and the revenue from energy sales of the EO increased by 11.9%; renewable energy was prioritized for consumption, with a consumption rate of 100%; the total output of the core devices for energy cascade utilization increased by 15.6%, significantly improving energy supply efficiency; the total carbon emissions decreased by 8.64%; and power and heat loss rates were 0% and 0.00059%, respectively. Highlights With the rapid development of renewable energy, The integrated energy system relies on its inherent operational advantages of high flexibility, high toughness, and multi energy coupling cascade utilization, demonstrates unique advantages in serving as a clean and renewable energy carrier and adapting to the development of distributed energy The energy cost of flexible users has decreased by 4.42%, and the revenue from energy sales of energy operators has increased by 11.9%; Renewable energy is prioritized for consumption, with a consumption rate of 100%; The total output of the core devices for energy cascade utilization has increased by 15.6%, significantly improving energy supply efficiency; The total carbon emissions decreased by 8.64%, both power and heat loss rates are 0%, the error rate of energy supply is 0.00059% Based on the above research, this paper is established a distributed low-carbon operation optimization model for Integrated energy system coupled the EO that contain CCHP and the FU based on Stackelberg game In view of the gradual deepening of the coupling degree of the IES, the increasingly obvious characteristics of multi-agent, the difficulty of centralized scheduling to protect the interests of each independent entity, and the inadequacy of the system’s energy cascade utilization advantages, this paper establishes a bilateral distributed operation optimization model based on Game theory In response to the insufficient utilization of the advantages of multi energy coupling in existing research on IES, insufficient attention paid to the interaction between supply and demand on both sides of the system, and insufficient enthusiasm of users as independent entities to participate in system operation scheduling, this article adopts a integrated demand response as the load side operation scheduling strategy

Low-carbon Economic Scheduling of Combined Cooling, Heating and Power Microgrid Considering Demand Response and Shared Energy Storage

In order to further promote the new energy consumption of combined cooling, heating, and power (CCHP) microgrid, reduce carbon emissions, and optimize the total operating cost of the microgrid, a low-carbon optimal scheduling model of CCHP microgrid was proposed. It considered demand response (DR) and shared energy storage (SES). Firstly, the concept of SES and its operation mode are applied to the microgrid. Secondly, in order to take advantage of the flexible nature of multiple loads, an integrated demand response (IDR) model with a ladder subsidy mechanism was established. Then, the optimal scheduling model introduces a reward and punishment ladder carbon trading mechanism (RPL-CTM). Finally, taking energy purchase cost, load reduction subsidy cost, interaction cost with energy storage station, carbon trading cost, and wind abandoning penalty cost as optimization objectives, a multi-energy coupling, and multi-objective collaborative optimization scheduling model was established. Numerical analysis indicates that the model can efficiently lower the microgrid’s operating cost and encourage the use of clean energy and carbon emission reduction.

Solar Panel Study in the Desert Climate of Abu Dhabi, United Arab Emirates

The negative effects of climate change and global warming are no longer a futuristic issue to deal with. This is the result of the continued and extensive use of fossil fuels and subsequent greenhouse gasses emissions such as CO2. Earth has been warming at an alarmingly fast pace the last 40 years due to greenhouse gas emission and the trapping of heat in the atmosphere. To slow down and eliminate this unnatural warming rate a reduction in greenhouse gas emissions is essential. This is accomplished by an increase in the deployment and use of clean renewable energy. Solar energy continues to play a significant role in the clean energy shift due to the abundance and unlimited supply of energy provided by the sun. The use of solar energy is on an exponential rise thanks to recent government policies to reduce emissions. For example, solar energy production in the United Arab Emirates (UAE) from 2009-2019 shows an exponential rise starting in 2016 reaching almost 3500 GWh of production in 2019 [1]. The UAE is also home to the Mohammed Bin Rashid Al Maktoum solar park. The largest single site solar park the world. This project will help reduce more than 6.5 million tons of emissions and will have capacity of 5000 megawatts [2].The United Arab Emirates is an ideal region for solar due the amount of sunshine and with very few cloudy/rainy days. However, desert climates have their own unique challenges, such as extreme heat and soling. Temperatures can reach above 40 in summer months in the UAE with high humidity and effect of soiling from dust is not very well understood [3]. Also, what is important is finding the optimal angle and direction of roof top solar panels to maximize the power and limit these negative effects.In this work, we studied a real solar panel on the rooftop in Abu Dhabi. The solar panel was bought from a local vendor in the UAE. The solar panel is polysilicon with specs: 10W, Vmp 18V, Imp 0.56A, Voc 24.4V and ISC 0.69A under AM1.5G at 25°C. We placed the panel on a roof top in Abu Dhabi at Khalifa University. To find the optimal angle and location we tested the panels at 12noon to maximum sun power. We first fixed the angle around 22° based on literature, and then modified the direction from north, south, west and east to find which direction gave the peak. We found that south gave the highest power from the rest (10.32W). Then we changed from angle from this data from 0°-90° in steps of 10°. The data showed the maximum power is when panel is facing south with angle between 25°-30°. The optimum placement of solar panels is key in helping to mitigate the negative desert effects such at heat and soiling. In addition, to this study, we also studied the panel for a continuous period to see effects of soling and longer-term heat exposure. More on this data will be added to in the poster to be presented.In summary, the use for solar panels is key to help prevent the negative effect of climate change. In desert like conditions, while there is plenty of sunshine, the negative effects of soling and temperature is not fully studied yet. Finding the optimum, angle and direction is key it get the peak performance of the panel and helping to mitigate some of these negative effects. Also studying the long-term effects of the temperature and soiling is important. Finally, knowing the negative effects can help researchers find new materials and solutions for solar cells for desert like environments.[1] E. Agency, "Renewables Information," July 2021. [Online].[2] T. National, "Road to Net Zero," 09 May 2019. [Online][3] O. Albadwawi et al., "Quantification of spectral losses of Natural soiling and detailed microstructural analysis of Dust collected from Different locations in Dubai, UAE," 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC), 2019, pp. 3115-3118, doi: 10.1109/PVSC40753.2019.8980937. Figure 1

Impact of Digital Inclusive Finance on Urban Carbon Emission Intensity: From the Perspective of Green and Low-Carbon Travel and Clean Energy

This paper uses the non-balanced panel data of 285 prefecture-level cities in China from 2011 to 2017 and the Peking University Digital Inclusive Finance Index to examine the impact of the development of digital inclusive finance on urban carbon emission intensity. The results show that the development of digital inclusive finance has a significantly negative impact on urban carbon emission intensity. By using the spherical distance between various cities and Hangzhou as an instrumental variable to deal with the potential endogeneity problem, the results still hold. Mechanism analysis shows that digital inclusive finance can reduce urban carbon emission intensity by promoting green and low-carbon travel modes of public transport and the use of clean energy. Compared with other regions, the effect of digital inclusive finance in reducing urban carbon emission intensity is more significant in the western region and in cities with low economic development. Against the background of the carbon peaking and carbon neutrality goals, we find that accelerating the development of digital inclusive finance can effectively promote the green and low-carbon transition of cities.

A Strategic Analysis of Photovoltaic Energy Projects: The Case Study of Spain

The Spanish photovoltaic sector could be a serious opportunity for the recovery and economic growth of the country, by serving as a support platform for the National Integrated Energy and Climate Plan (NIECP) 2021–2030, whose objective is to determine the lines of action required for the appropriate and efficient use of clean energy in order to benefit the economy, employment, health, and the environment. Bearing in mind the notable increase in the economic competitiveness of photovoltaic energy in Spain when compared to traditional and other renewable energy sources, it is necessary to carry out a strategic analysis of the macro-environment, using a PESTEL (Political, Economical, Social, Technological, Environmental and Legal) analysis so as to identify the most relevant external aspects that are vital for the performance of photovoltaic industries/markets and to facilitate decision making when developing short-, medium-, and long-term strategies, and the micro-environment, using Porter’s five forces (threat of new entrants, threat from substitution products and/or services, the bargain power of suppliers, the bargaining power of buyers and competitive rivalry) framework, to determine and examine the main factors that define the structure and level of competition that exists within the Spanish industry/market. The results obtained have been combined in a SWOT (Strengths, Weaknesses, Opportunities, and Threats) chart, which facilitates an understanding of the current strengths, weaknesses, opportunities, and threats as regards the photovoltaic sector in Spain.

Spatiotemporal evolution and influencing factors of China’s economic development performance under carbon emission constraints

BackgroundChina’s high-quality economic development depends on achieving sustainable economic development, reaching peak carbon emissions, achieving carbon neutrality, and intensifying the development of an industrial and energy structure that saves resources and protects the environment. This study used the data envelopment analysis (DEA) model and the Malmquist productivity index to measure the economic development performance of mainland China under carbon emission constraints. Then, it described the spatiotemporal evolution of economic development performance and analyzed its influencing factors using the Tobit model.ResultsThe results revealed that there were obvious differences in the trends of the static and dynamic performance of economic development. On the one hand, the static performance of economic development exhibited an upward trend from 2008 to 2020. Its distribution characteristics were dominant in the higher and high-level areas. On the other hand, the dynamic performance had a downward trend from 2008 to 2016 and then an upward trend from 2016 to 2020. In most provinces, the dynamic performance was no longer constrained by technological progress but rather by scale efficiency. It was found that the main factors influencing economic development performance were urbanization level, energy efficiency, vegetation coverage, and foreign investment, while other factors had no significant influence.ConclusionsThis study suggests that China should improve its economic development performance by increasing the use of clean energy, promoting human-centered urbanization, increasing carbon absorption capacity, and absorbing more foreign capital in the future.

Optimal Operation Strategy of Combined Heat and Power System Considering Demand Response and Household Thermal Inertia

With the development of energy Internet and renewable energy, the combined heat and power micro-energy grid (CHPMEG) has become an important carrier for the use of clean energy. In order to improve the living comfort of households and the utilization efficiency of wind power in winter, this paper proposes a coordinated optimal operation strategy of CHPMEG considering the load demand side response and the thermal inertia of the user side. First, the load demand side response is introduced into the optimal operation of CHPMEG, and a load demand response model is proposed based on reward mechanism. Then, the household thermal inertia is taken into account in the system operation, and a heat load model considering thermal inertia is established to describe the corresponding characteristics more exactly. On this basis, an optimization model is further developed and solved to minimize the operation cost of the system. Finally, the case simulations demonstrate the effectiveness of the optimal operation strategy of CHPMEG proposed in this paper.

Reinforcement Learning Based Truck-and-Drone Coordinated Delivery

Coronavirus disease 2019 has brought a great challenge to the supply of daily necessities and medical items for home-quarantined people. Considering the unmanned operation, agility and use of clean energy of drones, we propose a novel truck-and-drone coordinated delivery system that does not require direct human contact during the delivery process. All final deliveries are completed by the drone while the truck acts as a movable charging station and a carrier, so that the contagion risks are reduced. Moreover, we spilt the whole delivery problem into the customer clustering problem and the routing problems of both the truck and the drone. An encoder-decoder framework combined with reinforcement learning is created to solve the routing problems without handcrafted designed heuristics. We design the different problem contexts specific to the truck routing problem and the drone routing problem. The experimental results show the proposed approach has good generality and can consequently be applied to problems of different scales with high time efficiency.