This study examines the impact of environmental, social, and governance (ESG) factors on economic investment from a statistical perspective, aiming to develop a tested investment strategy that capitalizes on the conne...
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This paper addresses two issues that concern the electricity market participants under the European day-ahead market(DAM)framework,namely the feasibility of the attained schedules and the non-confiscation of cleared *...
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This paper addresses two issues that concern the electricity market participants under the European day-ahead market(DAM)framework,namely the feasibility of the attained schedules and the non-confiscation of cleared *** address the first issue,new resource-specific orders,i.e.,thermal orders for thermal generating units,demand response orders for load responsive resources,and energy limited orders for storage resources,are proposed and incorporated in the existing European DAM clearing *** address the second issue,two approaches which lead to a non-confiscatory market are analyzed:①discriminatory pricing with side-payments(***);and②non-discriminatory pricing excluding out-ofmoney orders(European paradigm).A comparison is performed between the two approaches to investigate the most appropriate pricing rule in terms of social welfare,derived revenues for the sellers,and efficiency of the attained *** proposed model with new resource-specific products is evaluated in a European test system,achieving robust *** feasibility of the attained schedules is demonstrated when using resource-specific orders compared with block ***,the results indicate the supremacy of discriminatory pricing with side-payments compared with the current European pricing rule.
Modulation depth and its associated loss pose a significant challenge in electro-optical telecommunication systems. Optimal modulators strive to enhance modulation depth while minimizing loss rates. We propose a high-...
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In this paper,we present a Deep Neural Network(DNN)based framework that employs Radio Frequency(RF)hologram tensors to locate multiple Ultra-High Frequency(UHF)passive Radio-Frequency Identification(RFID)*** RF hologr...
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In this paper,we present a Deep Neural Network(DNN)based framework that employs Radio Frequency(RF)hologram tensors to locate multiple Ultra-High Frequency(UHF)passive Radio-Frequency Identification(RFID)*** RF hologram tensor exhibits a strong relationship between observation and spatial location,helping to improve the robustness to dynamic environments and *** RFID data is often marred by noise,we implement two types of deep neural network architectures to clean up the RF hologram *** the spatial relationship between tags,the deep networks effectively mitigate fake peaks in the hologram tensors resulting from multipath propagation and phase *** contrast to fingerprinting-based localization systems that use deep networks as classifiers,our deep networks in the proposed framework treat the localization task as a regression problem preserving the ambiguity between *** also present an intuitive peak finding algorithm to obtain estimated locations using the sanitized hologram *** proposed framework is implemented using commodity RFID devices,and its superior performance is validated through extensive experiments.
The increasing penetration of renewable energy resources with highly fluctuating outputs has placed increasing concern on the accuracy and timeliness of electric power system state estimation(SE).Meanwhile,we note tha...
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The increasing penetration of renewable energy resources with highly fluctuating outputs has placed increasing concern on the accuracy and timeliness of electric power system state estimation(SE).Meanwhile,we note that only a fraction of system states fluctuate at the millisecond level and require to be *** such,refreshing only those states with significant variation would enhance the computational efficiency of SE and make fast-continuous update of states ***,this is difficult to achieve with conventional SE methods,which generally refresh states of the entire system every 4–5 *** this context,we propose a local hybrid linear SE framework using stream processing,in which synchronized measurements received from phasor measurement units(PMUs),and trigger/timingmode measurements received from remote terminal units(RTUs)are used to update the associated local ***,the measurement update process efficiency and timeliness are enhanced by proposing a trigger measurement-based fast dynamic partitioning algorithm for determining the areas of the system with states requiring *** particular,non-iterative hybrid linear formulations with both RTUs and PMUs are employed to solve the local SE *** timeliness,accuracy,and computational efficiency of the proposed method are demonstrated by extensive simulations based on IEEE 118-,300-,and 2383-bus systems.
In the era of big data, with the increase in volume and complexity of data, the main challenge is how to use big data while preserving the privacy of users. This study was conducted with the aim of finding a solution ...
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In light of the escalating privacy risks in the big data era, this paper introduces an innovative model for the anonymization of big data streams, leveraging in-memory processing within the Spark framework. The approa...
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Edge computing has emerged as a promising technology to satisfy the demand for data computational resources in Internet of Things (IoT) networks. With edge computing, processing of the massive data-intensive tasks can...
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Bidirectional interlinking converter(BIC)is the core equipment in a hybrid AC/DC microgrid connected between AC and DC ***,the variety of control modes and flexible bidirectional power flow complicate the influence of...
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Bidirectional interlinking converter(BIC)is the core equipment in a hybrid AC/DC microgrid connected between AC and DC ***,the variety of control modes and flexible bidirectional power flow complicate the influence of AC faults on BIC itself and on DC sub-grid,which potentially threaten both converter safety and system *** study first investigates AC fault influence on the BIC and DC bus voltage under different BIC control modes and different pre-fault operation states,by developing a mathematical model and equivalent sequence ***,based on the analysis results,a general accommodative current limiting strategy is proposed for BIC without limitations to specific mode or operation *** amplitude is predicted and constrained according to the critical requirements to protect the BIC and relieving the AC fault influence on the DC bus *** with conventional methods,potential current limit failure and distortions under asymmetric faults can also be ***,experiments verify feasibility of the proposed method.
While there has beensignificant progress in recent years to incorporate the dynamics of distribution systems and industrial loads into the transmission using aggregated composite load models (CLM);there is no study th...
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