Expanded Study on the accumulation effect of tourism under the constraint of structure

There is a mutual influence between departmental structure and accumulation and growth. Therefore, the accumulation and growth of the tourism industry will be subject to certain restrictions on the industrial structure, and, conversely, it will have an impact on the existing industrial structure. Li Jingyi reported special research in the paper called “Research on tourism growth based on structural constraints” about the relationship between the growth of tourism and the existing industrial structure. It pointed out the specific interdependence between tourism and other economic sectors in terms of accumulation and growth. However, the research of Li Jingyi is based on the trichotomy of social product value. It is too abstract, while the study is understandable in theory. In practice, it is difficult to use the model of the paper to deal with specific problems. Therefore, how to improve the industry association model in the paper of Li and make it more in line with the actual situation becomes our concern. In this paper, the author hopes to improve the model of Li’s paper by simplifying the decomposition of social product value. At the same time, it makes a further study on accumulation elasticity and growth elasticity. On this basis, some suggestions are put forward to guide the development of other industries based on the tourism industry

Review of Information Disclosure in Different Electricity Markets

Electricity markets have been established in many countries of the world. Electricity and services are traded in the competitive environment of electricity markets, which generates a large amount of information during the operation process. To maintain transparency and foster competition of electricity markets, timely and precise information regarding the operation of electricity market should be disclosed to the market participants through a centralized and authorized information disclosure mechanism. However, the information disclosure mechanism varies greatly in electricity markets because of different market models and transaction methods. This paper reviews information disclosure mechanisms of several typical electricity markets with the poolco model, bilateral contract model, and hybrid model. The disclosed information and clearing models in these markets are summarized to provide an overview of the present information disclosure mechanisms in typical deregulated power systems worldwide. Moreover, the various experiences for establishing an efficient information disclosure mechanism is summarized and discussed

Research on the Application Integration Model for the Agricultural Enterprise of Integrative Production and Marketing

International audienceTo integrate application systems under heterogeneous environments has gradually become a pressing demand for most agricultural enterprise. The vast diversity of implementation technologies increases the complexity of applications integration. With the aim of facilitating the development of integration solutions, we propose the specification of application integration. To achieve this, we analyzed the current situation of information, the environment of application systems, and the specific requirements of integration. We also studied the integration technologies. And then the ESB-SOA model for the agricultural enterprise of integrative production and marketing was proposed on the basis of a number of advanced technologies, such as ESB, SOA, EAI and Web Service. Based on ESB and SOA technologies, the model is able to utilize and integrate effectively various service resources on the geographically distributed computing environments. And through intelligent agent technologies, it supports cooperation and coordination mechanisms for the service activities. To exemplify and validate the profile, a case study is presented in which the proposed profile is used

Research and Application of Data Security for Mobile Devices

International audienceMobile devices have been increasingly become important tools for the information system application in agriculture, but the safe problem that follow also results in risks of economy lose. Considering above problems and combining the application of an agriculture chain logistics management system, a series of jobs have been done. This paper presents a data security solution which encrypts the configuration files to protect sensitive information and uses SSL protocol to protect the network transmission security. At present, this solution has been modular integrated with the agriculture chain logistics management system. This paper also provides reference for data security problems of other mobile devices

Optimal scheduling for electricity–gas integrated energy system under the carbon-neutrality goal

In light of China’s carbon-neutral policy and the Energy Internet, it is crucial to reduce the carbon emissions resulting from the operation of the electricity–gas integrated energy system (EGIES). To address this issue, this paper proposes an optimal scheduling strategy for EGIES in line with the carbon-neutrality goal. Firstly, the oxygen-enriched combustion power plant, equipped with a power to gas unit, is modeled to maximize its carbon capture ability. Next, an optimal scheduling model for EGIES is proposed, which considers the bonus-penalty ladder carbon price and the oxygen-enriched combustion power plant, with the aim of minimizing the total operation costs and carbon emissions of the EGIES. Finally, the proposed model is applied to an EGIES, consisting of a 33-bus electric distribution network and a 20-bus natural gas network. The simulation results demonstrate that the proposed method can reduce the operation costs of the EGIES by up to 22.5% and the carbon emissions by up to 75.1t when compared to existing models

Data-driven Two-step Day-ahead Electricity Price Forecasting Considering Price Spikes

In the electricity market environment, electricity price forecasting plays an essential role in the decision-making process of a power generation company, especially in developing the optimal bidding strategy for maximizing revenues. Hence, it is necessary for a power generation company to develop an accurate electricity price forecasting algorithm. Given this background, this paper proposes a two-step day-ahead electricity price forecasting algorithm based on the weighted $K$-nearest neighborhood (WKNN) method and the Gaussian process regression (GPR) approach. In the first step, several predictors, i.e., operation indicators, are presented and the WKNN method is employed to detect the day-ahead price spike based on these indicators. In the second step, the outputs of the first step are regarded as a new predictor, and it is utilized together with the operation indicators to accurately forecast the electricity price based on the GPR approach. The proposed algorithm is verified by actual market data in Pennsylvania-New Jersey-Maryland Interconnection (PJM), and comparisons between this algorithm and existing ones are also made to demonstrate the effectiveness of the proposed algorithm. Simulation results show that the proposed algorithm can attain accurate price forecasting results even with several price spikes in historical electricity price data

Two-stage optimal scheduling of virtual power plant with wind-photovoltaic-hydro-storage considering flexible load reserve

In view of the current situation of China’s power system to make regulation for power generation and load side balance mainly by power plants that are subject to unified scheduling, the existing non-uniformly scheduled small hydropower resources of China can be integrated and utilized effectively when considering the aggregation and control of virtual power plant (VPP) towards distributed resources. Meanwhile, the economic operation of VPP under different seasons of rivers can be achieved, and the consumption of renewable energy such as wind power and photovoltaic (PV) can be promoted. In addition, a certain flexible load reserve (FLR) capacity can be obtained by signing medium and long-term contracts. In this context, a day-ahead and real-time two-stage rolling optimal scheduling strategy for VPP including distributed wind power, PV, and small hydropower is proposed. In the day-ahead stage, aiming at the minimization of operation cost and adopting the multi-scenarios analysis method, the day-ahead scheduling and FLR plan of VPP is formulated. In the real-time stage, with preciser wind and PV prediction, the economic scheduling considering deviation penalty cost can be achieved. The case study of VPP in Jingning County, Lishui City, Zhejiang Province of China verifies the effectiveness and practicability of the proposed method

Comprehensive Quality Assessment Algorithm for Smart Meters

With the improvement of operation monitoring and data acquisition levels of smart meters, mining data associated with smart meters becomes possible. Besides, precisely assessing the operation quality of smart meters plays an important role in purchasing metering equipment and improving the economic benefits of power utilities. First, seven indexes for assessing operation quality of smart meters are defined based on the metering data and the Gaussian mixture model (GMM) clustering algorithm is applied to extract the typical index data from the massive data of smart meters. Then, the combination optimization model of index’s weight is presented with the subject experience of experts and object difference of data considered; and the comprehensive assessment algorithm based on the revised technique for order preference by similarity to an ideal solution (TOPSIS) is proposed to evaluate the operation quality of smart meters. Finally, the proposed data-driven assessment algorithm is illustrated by the actual metering data from Zhejiang Ningbo power supply company of China and practical application is briefly introduced. The results show that the proposed algorithm is effective for assessing the operation quality of smart meters and could be helpful for energy measurement and asset management