Due to the rapid development of Internet of Things (IoT) technology, there is a closer and more complex coupling relationship between energy network and information network in the integrated energy park than ever that...
Due to the rapid development of Internet of Things (IoT) technology, there is a closer and more complex coupling relationship between energy network and information network in the integrated energy park than ever that included electricity, heat and other energy forms, constituting the IoT-Enable integrated energy park (IIEP). In the IIEP, massive data information can be comprehensively collected and managed, which provides the possibility of energy sharing among the internal prosumers. In order to improve the utilization rate of equipment and reduce the energy costs of prosumers in the IIEP, this paper presents a distributed energy sharing service mechanism. Firstly, the architecture and business process of the sharing service mechanism are designed. And then, the coordinated operation model and strategy aiming at minimizing the net energy cost of all prosumers in the IIEP are established. Furthermore, to provide clarity on the benefits and costs for each participating entity, the sharing benefit allocation and the cost settlement models are set up. Finally, the results of case study demonstrate that the presented sharing service mechanism effectively improves the overall utilization of distributed energy supply and storage systems, promotes local sharing and consumption of distributed energy, and reduces the energy costs of prosumers.
Traditional farm autonomous feeding robot path planning systems have low target detection accuracy, poor planning efficiency, and insufficient adaptability to environmental changes when facing complex farm environment...
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ISBN:
(数字)9798350318609
ISBN:
(纸本)9798350318616
Traditional farm autonomous feeding robot path planning systems have low target detection accuracy, poor planning efficiency, and insufficient adaptability to environmental changes when facing complex farm environments. This article aims to solve the problems existing in traditional systems by introducing the YOLOv3 algorithm, in order to improve the performance and efficiency of robots in autonomous feeding tasks on farms. Firstly, this article utilizes the YOLOv3 algorithm to achieve target detection and localization in the system, and then uses sensor data fusion technology to perceive the environment and construct a map. It then integrates map information for path planning and optimization, achieving system adjustment and obstacle avoidance, and finally selects commonly used path planning algorithms for experimental comparison. The results show that the target detection accuracy of the task path planning system for autonomous feeding robots in three-dimensional farms based on the YOLOv3 algorithm is the highest, exceeding 99%. In addition, the operating efficiency of the system is also the highest, above 95%. In summary, the YOLOv3 algorithm is very suitable for the research of task path planning systems for autonomous feeding robots in three-dimensional farms.
The distributed trading of power among multi-microgrid clusters has the potential to enhance energy mutual aid between microgrids in a region and improve local consumption of renewable energy. However, the primary obj...
The distributed trading of power among multi-microgrid clusters has the potential to enhance energy mutual aid between microgrids in a region and improve local consumption of renewable energy. However, the primary objective of each microgrid entity is profit maximization, and the conventional mode of transaction based on price matching may result in serious breaches of contract by users. Therefore, this paper proposes a multi-microgrid distributed energy trading model based on blockchain technology and Gale-Shapley algorithm. First, each microgrid entity constructs user preference indicators, such as the maximum available power, user reputation, and price, to evaluate and score both parties involved in the transaction. Second, a bilateral matching mechanism based on the Gale-Shapley algorithm is proposed, which ensures stable matching results for buyers and sellers in the two-way selection of the trading market. Third, to guarantee the secure operation of the distribution network, a method for verifying the transaction matching results using a distribution network security constraint checking technique is proposed. Finally, the rationality of the transaction model is demonstrated through verification on the Matlab simulation platform.
This paper proposes a cloud energy storage service mechanism for the distributed energy storage scenario in industrial parks, and studies the pricing of cloud energy storage resources in this mechanism, which is orien...
This paper proposes a cloud energy storage service mechanism for the distributed energy storage scenario in industrial parks, and studies the pricing of cloud energy storage resources in this mechanism, which is oriented to the new power system. By optimally solving the distributed energy devices and energy demand of the campus users, the users' energy storage idle and energy storage demand are derived, and the cloud energy storage service platform benefits by matching the idle and demand quantities. For the pricing of cloud energy storage resources, this paper uses classical social welfare function and Nash social welfare function as the objective function to build a two-layer optimization model, and uses particle swarm algorithm to solve the cloud energy storage pricing model. Simulation analysis shows that the mechanism can effectively improve the utilization of energy storage resources and reduce the cost of energy use while ensuring the overall benefits of the platform and users.
Bitcoin's notable success at operating autonomously as a global peer-to-peer network opened the door to a new revolutionary class of distributedsystems: blockchain. However, with the rising popularity of this new...
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ISBN:
(纸本)9781665435789
Bitcoin's notable success at operating autonomously as a global peer-to-peer network opened the door to a new revolutionary class of distributedsystems: blockchain. However, with the rising popularity of this new paradigm, the concept of blockchain shifted greatly to the point where many systems marketed as "blockchain" without sharing the key components introduced by Bitcoin. It has therefore become quite challenging for system designers or decision-makers to achieve a sufficient understanding of different types of existing blockchains or to design and adopt the correct blockchain solution. To overcome this problem, we propose DCEA a holistic reference model for conceptualizing and closely examining blockchains and globally distributed ledger technologies (DLT) using a layer-wise framework that envisions all these systems as constructed of four layers: the data, consensus, execution and application layers.
The sharing economy is a new economic mode that can effectively promote the optimal allocation and utilization of the existing resources. Its integration with the distributed energy domain has a great significance in ...
The sharing economy is a new economic mode that can effectively promote the optimal allocation and utilization of the existing resources. Its integration with the distributed energy domain has a great significance in enhancing the utilization rate of equipment and reducing the cost of energy consumption of users. Therefore, this paper presents a distributed photovoltaic (PV) sharing service mechanism for the distributed PV existing resources of users in the park. Firstly, the architecture of the distributed PV sharing service mechanism is established, and the business process of the service mechanism is designed. Then, a model of distributed PV sharing user group is established, which can effectively analyze the sharing power, the net energy cost, and the purchased and sold power of the sharing user group. After that, a distributed PV sharing benefit model, a benefit allocation model based on a heuristic method, and a cost settlement model are established. Afterwards, the coupling relationship between the sharing benefit and the tariff profit interval and the amount of sharing electricity is discussed, and the heuristic benefit allocation method is compared and interpreted from the perspective of the tariff. Finally, it is verified through case study that the presented mechanism can effectively promote the localized sharing of distributed PV energy and reduce the cost of energy consumption of users.
Underwater wireless sensor networks (UWSNs) are a prominent research topic in academia and industry, with a wide range of underwater applications including ocean monitoring, seismic monitoring, environmental monitorin...
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Underwater wireless sensor networks (UWSNs) are a prominent research topic in academia and industry, with a wide range of underwater applications including ocean monitoring, seismic monitoring, environmental monitoring, and seabed exploration. However, UWSNs face a number of restrictions and obstacles, including high ocean interference and noise, long propagation times, narrow bandwidth, changeable network architecture, and sensor's battery life. One of the solutions to these problems is to build efficient routing protocols. A routing protocol can move data from a source node to a destination node in the network efficiently. A review of underwater routing protocols for UWSNs is presented in this paper. Existing underwater routing protocols are categorized into three categories: energy-based, data-based, and geographic information-based protocols. Recent underwater routing protocols are discussed in depth, by presenting their benefits, drawbacks and performance. In addition, We discuss challenges and future directions of underwater routing protocols, which can assist researchers interested to explore further this important research topic.
In today's cities, shopping and browsing for things in shopping malls have become a regular activity. At shopping malls, during vacations and weekend breaks., a diverse range of people is observed. When there are ...
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In recent years, the distributed PV industry has developed rapidly, and more and more residential customers have started to install distributed PV power generation systems, while the unobservable characteristics of be...
In recent years, the distributed PV industry has developed rapidly, and more and more residential customers have started to install distributed PV power generation systems, while the unobservable characteristics of behind-the-meter distributed PV bring great challenges to the demand response aggregated baseline load (ABL) prediction. To improve the one-inch accuracy of ABL under high penetration distributed PV, a aggregated baseline load forecasting method based on decoupling of distributed PV-containing customers is proposed. Firstly, the abnormal load data is identified and corrected based on t-test in mathematical statistics, and the temperature data is corrected; secondly, a PV user identification method based on weather state characteristics is used to separate PV users and non-PV users; then, the aggregated baseline load of non-PV users is predicted by considering the differentiation of users' electricity consumption patterns; again, the aggregated baseline load for PV users is classified by typical weather types and a prediction model is built for each weather type using SVR for aggregated baseline load prediction; finally, the predicted values for both types of users are combined to obtain the final ABL prediction values. The simulation results show that the proposed method reduces the average absolute error index by 2.65 and the root mean square error index by 0.76 on average compared with the direct prediction method and other classification prediction methods.
Since the primordial days of human settlements emergence, metropolitan regions and traffic congestion have developed concomitantly. The factors that cause commuters to congregate in modern cities also contribute to of...
Since the primordial days of human settlements emergence, metropolitan regions and traffic congestion have developed concomitantly. The factors that cause commuters to congregate in modern cities also contribute to often intolerable levels of traffic congestion. Air quality gets severely deteriorated as a result of rising urbanization and traffic congestion. When poor emission standards are instigated by existing older vehicles, this makes air quality even worse. In this paper we propose a real-time pollution detection solution model using cost efficient Internet of Things (IoT) devices and distributed streaming techniques which can detect infringing vehicles instantaneously and calculate the present air quality levels on specific regions to reflect updates regularly. For our study, we have used a four-wheel prototype robot car, radio frequency identification (RFID) tagging unit, NodeMCU V3 Lua board, ATmega328P Arduino board, few electro-chemical toxic gas sensors like MQ-2, MQ-7, MQ-135, etc and a wireless sensor network (WSN) to connect the devices. Also, in this paper we propose a real time complex event processing (CEP) monitoring dashboard which receives feeds from the devices network using Apache Flink distributed streaming technology. Especially in urban areas our proposed solution model can be used cost efficiently to detect and control emission violations.
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