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Photovoltaic storage system (PVSS) has been spawned with the combined application of photovoltaic (PV), energy storage (ES) and energy blockchain (EB), which has also made important contributions to the energy structure adjustment, energy transaction security and ecological environment protection. The establishment of a reasonable task matching mechanism can further improve the operation efficiency and quality of the system under the EB environment, and this paper consequently constructs a task matching model of PVSS based on GA-CLOUD-GS algorithm. Firstly, the decision-making committee is set up and the index system is determined for the to-be-matched task. Secondly, the Genetic Algorithm (GA) comprehensive weighting method is introduced to integrate the subjective and objective weights to achieve the weight optimization. Thirdly, the cloud model is used to obtain the preference order and priority order of the to-be-matched subjects. Fourthly, the Gale-Shapley (GS) algorithm is used to obtain the task matching results. Finally, the operability, the stability and the effectiveness of the model are separately verified through numerical simulation, sensitivity analysis and comparative analysis. Corresponding suggestions for the task matching of PVSS in the EB environment are also put forward according to the research content. • The necessity, superiority, and application scenarios of collaborative development between PVSS and EB are clarified, and the importance of research on task matching mechanism is identified. • A task matching mechanism model based on the GA-CLOUD-GS algorithm is established, the feasibility, stability, and effectiveness of the established model were verified. • Relevant suggestions are provided for the development of PVSS in the EB environment. [ABSTRACT FROM AUTHOR]

Abstract In recent years, the wind curtailment has become a serious problem in China and the government are actively seeking solutions to deal with this energy loss. Therefore, the use of non-grid-connected wind power has received great attention since it can be supplied to local end users equipped with energy storage and then mitigate wind curtailment. Since the non-grid-connected wind power and local power load have to confront dramatic power fluctuations, a hybrid energy storage system (HESS) including batteries and supercapacitors is applied. This paper proposes a multi-objective optimization model of HESS configuration in non-grid-connected wind power/energy storage/local user system. In this model, two decision variables, numbers of batteries and supercapacitors, are determined based on the objective of annual profit maximization and wind curtailment rate minimization. To solve this model, a non-dominated sorting genetic algorithm II (NSGA-II) is employed to obtain Pareto front and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) technique is applied to select the optimal solution from Pareto solutions. Finally, a wind farm in Hebei province is studied and discussed. A scenario analysis, a sensitivity analysis and a comparative analysis are performed to show the advantages of the proposed model. Highlights • The local consumption of non-grid-connected wind is a solution to wind curtailment. • Hybrid energy storage increases the profit and reduces the wind curtailment rate. • NSGA-II-VIKOR is effective to determine the optimal energy storage capacity. • Energy storage cost and objective weight both influence the optimization result. [ABSTRACT FROM AUTHOR]

"Photovoltaic + energy storage" is considered as one of the effective means to improve the efficiency of clean energy utilization. In the era of energy sharing, the "photovoltaic - energy storage - utilization (PVESU)" model can create a more favorable market environment. However, the various uncertainties in the construction of the PVESU project have become the main obstacles to the development of the PVESU model. This paper aims to evaluate the risk level of China's PVESU projects through an improved Cloud-TODIM (Cloud-an acronym in Portuguese for Interative Multi-criteria Decision Making) method. First of all, 18 critical risk factors are identified using the constructed five-dimensional risk analysis model. Secondly, the improved method is used to calculate the weight of the comprehensive criteria and rank 14 PVESU alternatives. Finally, the accuracy and feasibility of the hybrid method are verified by sensitivity analysis tests concluding the loss decay coefficient adjustment and comparison analysis with the Cloud-TOPSIS(Cloud-Technique for Order of Preference by Similarity to Ideal Solution) method. Meanwhile, in terms of energy storage, some suggestions are made for the future development of China's PVESU project. This study can also provide insightful enlightenment for PVESU project investors, risk management professionals and decision makers. • The highlights stated are as follows: • Construct an evaluation system of Photovoltaic - Energy storage - Utilization (PVESU) project risk assessment. • Contribute to adding five-dimensional risk analysis method to select critical risk factors. • Propose an improved Cloud-TODIM method to analyze the risk level of PVESU projects. • Extend the research on integrated projects on the field of clean energy and energy storage. [ABSTRACT FROM AUTHOR]