Deep-Ensemble Learning Method for Solar Resource Assessment of Complex Terrain Landscapes

As the global demand for renewable energy grows,solar energy is gaining attention as a clean,sustainable energy source.Accurate assessment of solar energy resources is crucial for the siting and design of photovoltaic power plants.This study proposes an integrated deep learning-based photovoltaic resource assessment method.Ensemble learning and deep learning methods are fused for photovoltaic resource assessment for the first time.The proposed method combines the random forest,gated recurrent unit,and long short-term memory to effectively improve the accuracy and reliability of photovoltaic resource assessment.The proposed method has strong adaptability and high accuracy even in the photovoltaic resource assessment of complex terrain and landscape.The experimental results show that the proposed method outperforms the comparison algorithm in all evaluation indexes,indicating that the proposed method has higher accuracy and reliability in photovoltaic resource assessment with improved generalization performance traditional single algorithm.

New power system development path mechanism design

Carrying out green energy transformation,implementing clean energy power replacement and supply,and developing a new power system are some primary driving forces needed to fulfill China’s carbon-peak and carbon-neutral strategic goals.The construction of new power systems in China’s provinces and cities is developing rapidly,and the lack of a typical model promotes the application.The new power system path design should be based on the actual development of the power grid in different regions,energy use characteristics,and other actual needs to carry out the differentiated path design.In this context,this study analyzes the characteristics of the new domestic power system based on the policy background of the new domestic power system,constructs a new model for power system development stage identification,and proposes the overall design of the new power system development path from the power supply,transmission and distribution,and load sides.It also uses the Hebei South Network as an example to explore the development stage of the Hebei South Grid based on actual development needs.Finally,this study designs a novel power system development path for the entire supply and demand chain for the Hebei South Grid to propose ideas for constructing a new power system in China and to help green energy transformation.

Life-cycle cost model and evaluation system for power grid assets based on fuzzy membership degree

Life-cycle cost(LCC)theory can be effectively applied to improve the efficiency and quality of power plant equipment and asset management.However,specific aspects of the LCC calculation and evaluation model require further research for practical application.This paper proposes an LCC assessment model for the management of electric power plant equipment during its service life.A membership function method based on fuzzy logic is used to improve the allocation of modernization and overhaul projects to multiple equipment assets.An LCC assessment model and evaluation system for power equipment are proposed and successfully applied to the equipment and project management of a Guangzhou power plant in the China Southern Power Grid,providing a decision-making mechanism that facilitates efficient operation and optimal utilization of power plant equipment and assets.

Capacity Optimization Configuration of Hydrogen Production System for Offshore Surplus Wind Power

To solve the problem of residual wind power in offshore wind farms,a hydrogen production system with a reasonable capacity was configured to enhance the local load of wind farms and promote the local consumption of residual wind power.By studying the mathematical model of wind power output and calculating surplus wind power,as well as considering the hydrogen production/storage characteristics of the electrolyzer and hydrogen storage tank,an innovative capacity optimization allocation model was established.The objective of the model was to achieve the lowest total net present value over the entire life cycle.The model took into account the cost-benefit breakdown of equipment end-of-life cost,replacement cost,residual value gain,wind abandonment penalty,hydrogen transportation,and environmental value.The MATLAB-based platform invoked the CPLEX commercial solver to solve the model.Combined with the analysis of the annual average wind speed data from an offshore wind farm in Guangdong Province,the optimal capacity configuration results and the actual operation of the hydrogen production system were obtained.Under the calculation scenario,this hydrogen production system could consume 3,800 MWh of residual electricity from offshore wind power each year.It could achieve complete consumption of residual electricity from wind power without incurring the penalty cost of wind power.Additionally,it could produce 66,500 kg of green hydrogen from wind power,resulting in hydrogen sales revenue of 3.63 million RMB.It would also reduce pollutant emissions from coal-based hydrogen production by 1.5 tons and realize an environmental value of 4.83 million RMB.The annual net operating income exceeded 6 million RMB and the whole life cycle NPV income exceeded 50 million RMB.These results verified the feasibility and rationality of the established capacity optimization allocation model.The model could help advance power system planning and operation research and assist offshore wind farm operators in improving economic and environmental benefits.

Price prediction of power transformer materials based on CEEMD and GRU

The rapid growth of the Chinese economy has fueled the expansion of power grids.Power transformers are key equipment in power grid projects,and their price changes have a significant impact on cost control.However,the prices of power transformer materials manifest as nonsmooth and nonlinear sequences.Hence,estimating the acquisition costs of power grid projects is difficult,hindering the normal operation of power engineering construction.To more accurately predict the price of power transformer materials,this study proposes a method based on complementary ensemble empirical mode decomposition(CEEMD)and gated recurrent unit(GRU)network.First,the CEEMD decomposed the price series into multiple intrinsic mode functions(IMFs).Multiple IMFs were clustered to obtain several aggregated sequences based on the sample entropy of each IMF.Then,an empirical wavelet transform(EWT)was applied to the aggregation sequence with a large sample entropy,and the multiple subsequences obtained from the decomposition were predicted by the GRU model.The GRU model was used to directly predict the aggregation sequences with a small sample entropy.In this study,we used authentic historical pricing data for power transformer materials to validate the proposed approach.The empirical findings demonstrated the efficacy of our method across both datasets,with mean absolute percentage errors(MAPEs)of less than 1%and 3%.This approach holds a significant reference value for future research in the field of power transformer material price prediction.

Input-output efficiency model of urban greenenergy development from the perspective of a low-carbon economy

With the acceleration of urbanization,cities are the main targets for carbon neutrality and urban energy is the terminal of energy consumption and the integration point of various energy systems.Therefore,there is a need to promote the development of urban green energy and achieve low input and high output to achieve a low-carbon economy in cities.Previous studies have not considered the input-output efficiency of urban green-energy development.This study fills this gap.Based on the economic-energy-environmental framework,an input-output efficiency-evaluation index system for urban green-energy development was constructed.Based on improved data-envelopment analysis,a comparative evaluation of the input-output efficiency of green-energy development was carried out in 30 provinces in China in 2019.Considering the differences in regions,the development of urban green energy in different provinces was classified.From the perspective of a low-carbon economy,economic growth factors and environmental constraint factors were set.Together with the generalized Divisia index approach,the input-output efficiency optimization directions of urban green-energy development were obtained.The results showed that the input-output efficiencies of urban green-energy development in Jiangsu,Zhejiang,Fujian,Inner Mongolia,Ningxia and other provinces and cities were relatively high.Provinces with faster economic development and higher environmental carrying capacity have advantages after optimization and will become pilot areas for the development of urban green energy.This research provides a reference for the development of urban green energy in various provinces from the input and output perspective.

Generation of typical operation curves for hydrogen storage applied to the wind power fluctuation smoothing mode

In this paper,a typical-operation-curve generation method of a hydrogen energy storage system operating under the mode of stabilizing wind power fluctuations is proposed.This method is used to optimize the power and capacity configuration of the energy storage system.The time series curves of the charging and discharging powers of the hydrogen energy storage are obtained by EMD decomposition,and the curves are classified according to the similarities and differences of the characteristic parameters in different time periods.After the classification,typical charging and discharging power values of each type of curve at each moment are obtained by a cloud model,and then,typical operation curves of each type are obtained by integration.On this basis,the power and capacity of the energy storage system are optimized with the objective of economic optimization through the MATLAB CPLEX toolbox.Combined with the measured data of a wind farm with an installed capacity of 400 MW in Northeast China,the validity and rationality of the typical operation curve generation method proposed in this paper are verified.

Learning to branch in the generation maintenance scheduling problem

To maximize the reliability index of a power system,this study modeled a generation maintenance scheduling problem that considers the network security constraints and rationality constraints of the generation maintenance practice in a power system.In view of the computational complexity of the generation maintenance scheduling model,a variable selection method based on a support vector machine(SVM)is proposed to solve the 0-1 mixed integer programming problem(MIP).The algorithm observes and collects data from the decisions made by strong branching(SB)and then learns a surrogate function that mimics the SB strategy using a support vector machine.The learned ranking function is then used for variable branching during the solution process of the model.The test case showed that the proposed variable selection algorithm-based on the features of the proposed generation maintenance scheduling problem during branch-and-bound-can increase the solution efficiency of the generation-scheduling model on the premise of guaranteed accuracy.

Multi-objective optimal allocation strategy for the energy internet in Huangpu District, Guangzhou, China

To improve the overall efficiency of the energy system,the basic structure for the energy internet of coordination and optimization of“generation-grid-load-storage”of Huangpu District,Guangzhou,China is designed,while the arrangement for the output of centralized and distributed energy module and energy storage are proposed.Taking economic benefit maximization,environmental benefit maximization and energy efficiency maximization as sub-objectives,the mathematical model of multi-objective optimal allocation and operation strategy of the energy internet is established considering supply-demand balance constraints,equipment characteristic constraints,operation mode constraints,and energy conditions constraints.The calculation results show that without considering the outsourced electricity,the balanced strategy,the economic development strategy,the environmental protection strategy,and the energy efficiency strategy are obtained by calculation,which are all superior to the traditional energy supply strategy.Moreover,considering the outsourced electricity,the proportion of outsourced electricity to total electricity is 19.8%,which is the system optimization of the energy internet under certain power demand.Compared with other strategies without outsourced electricity,the outsourced electricity strategy can have a certain emission reduction effect,but at the same time reduce the economic benefit.Furthermore,the huge difference in demand for thermal and cooling load between industrial and commercial areas results in the installed capacity of gas distributed energy stations in industrial areas being nearly twice as large as that in commercial areas.The distributed photovoltaic power generation is allocated according to the proportion of the installed roof areas of photovoltaic power generation system in residential,industrial,and commercial areas.

Review of Market Power Assessment and Mitigation in Reshaping of Power Systems

The deregulation of the power industry requires avoiding market power abuse to maintain the market competitiveness. To this end, a sequence of assessment measurements or mitigation mechanisms is required. Meanwhile, the increasing renewable energy resources(RESs) and flexible demand response resources(DRSs) are changing the behaviors of market participants and creating new cases of market power abuse.Such new circumstances bring the new evaluation and control methods of market power to the forefront. This paper provides a comprehensive review of market power in the reshaping of power systems due to the increasing RES and the development of DRS. The market power at the supply side, demand side,and in the multi-energy system is categorized and reviewed. In addition, the applications of market power supervision measures in the US, the Nordics, UK, and China are summarized.Furthermore, the unsolved issues, possible key technologies,and potential research topics on market power are discussed.