Energy Management in Microgrids: A Combination of Game Theory and Big Data‐Based Wind Power Forecasting

Energy internet provides an open framework for integrating every piece of equipment involved in energy generation, transmission, transformation, distribution, and consumption with novel information and communication technologies. In this chapter, the authors adopt a combination of game theory and big data to address the coordinated management of renewable and traditional energy, which is a typical issue on energy interconnections. The authors formulate the energy management problem as a three‐stage Stackelberg game and employ the backward induction method to derive the closed‐form expressions of the optimal strategies. Next, we study the big data‐based power generation forecasting techniques and introduce a scheme of the wind power forecasting, which can assist the microgrid to make strategies. Simulation results show that more accurate prediction results of wind power are conducive to better energy management

A Review of the Monitoring of Market Power The Possible Roles of TSOs in Monitoring for Market Power Issues in Congested Transmission Systems

The paper surveys the literature and publicly available information on market power monitoring in electricity wholesale markets. After briefly reviewing definitions, strategies and methods of mitigating market power we examine the various methods of detecting market power that have been employed by academics and market monitors/regulators. These techniques include structural and behavioural indices and analysis as well as various simulation approaches. The applications of these tools range from spot market mitigation and congestion management through to long-term market design assessment and merger decisions. Various market-power monitoring units already track market behaviour and produce indices. Our survey shows that these units collect a large amount of data from various market participants and we identify the crucial role of the transmission system operators with their access to dispatch and system information. Easily accessible and comprehensive data supports effective market power monitoring and facilitates market design evaluation. The discretion required for effective market monitoring is facilitated by institutional independence.Electricity, liberalisation, market power, regulation

On the Exploitation of Admittance Measurements for Wired Network Topology Derivation

The knowledge of the topology of a wired network is often of fundamental importance. For instance, in the context of Power Line Communications (PLC) networks it is helpful to implement data routing strategies, while in power distribution networks and Smart Micro Grids (SMG) it is required for grid monitoring and for power flow management. In this paper, we use the transmission line theory to shed new light and to show how the topological properties of a wired network can be found exploiting admittance measurements at the nodes. An analytic proof is reported to show that the derivation of the topology can be done in complex networks under certain assumptions. We also analyze the effect of the network background noise on admittance measurements. In this respect, we propose a topology derivation algorithm that works in the presence of noise. We finally analyze the performance of the algorithm using values that are typical of power line distribution networks.Comment: A version of this manuscript has been submitted to the IEEE Transactions on Instrumentation and Measurement for possible publication. The paper consists of 8 pages, 11 figures, 1 tabl

HARQ Buffer Management: An Information-Theoretic View

A key practical constraint on the design of Hybrid automatic repeat request (HARQ) schemes is the size of the on-chip buffer that is available at the receiver to store previously received packets. In fact, in modern wireless standards such as LTE and LTE-A, the HARQ buffer size is one of the main drivers of the modem area and power consumption. This has recently highlighted the importance of HARQ buffer management, that is, of the use of buffer-aware transmission schemes and of advanced compression policies for the storage of received data. This work investigates HARQ buffer management by leveraging information-theoretic achievability arguments based on random coding. Specifically, standard HARQ schemes, namely Type-I, Chase Combining and Incremental Redundancy, are first studied under the assumption of a finite-capacity HARQ buffer by considering both coded modulation, via Gaussian signaling, and Bit Interleaved Coded Modulation (BICM). The analysis sheds light on the impact of different compression strategies, namely the conventional compression log-likelihood ratios and the direct digitization of baseband signals, on the throughput. Then, coding strategies based on layered modulation and optimized coding blocklength are investigated, highlighting the benefits of HARQ buffer-aware transmission schemes. The optimization of baseband compression for multiple-antenna links is also studied, demonstrating the optimality of a transform coding approach.Comment: submitted to IEEE International Symposium on Information Theory (ISIT) 2015. 29 pages, 12 figures, submitted to journal publicatio

A novel mode-switching hydraulic hybrid for an on-highway vehicle: A study of architecture and control

Increasing demand for fossil fuels, their limited reserves and the environmental effects resulting from the transportation sector has raised severe concerns to government agencies, transportation industry as well as the end-users. This has raised interests in improving the fuel economy of road vehicles. One of the promising technologies in this regard is hybridization of vehicle transmission. Hydraulic hybrids have progressively gained acceptance due to their high power density and low component costs relative to their electric counterpart. Many different hydraulic hybrid architectures have been developed to achieve better power management and regenerative braking and have been tested for performance and efficiency on transmission test rigs and off-highway vehicles. The most commonly used architecture is the series hybrid which offers great flexibility for implementation of power management strategies. But the direct connection of the high pressure accumulator to the system often results in operation of the hydraulic units in high pressure and low displacement mode. However, in this operating mode the hydraulic units are highly inefficient. Also, the accumulator renders the system highly compliant and makes the response of the transmission sluggish. In contrast, a hydrostatic transmission has a very stiff response which ensures a good drivability. However, it lacks energy storage. Keeping these in mind, a blended hybrid architecture was recently developed. However, the complexity of the architecture results in diculties while developing control strategies and results in poor drivability while mode switching. Drivability is a major concern along with performance in an on-highway vehicle. This work focuses on the development of a new hydraulic hybrid architecture called the Mode-Switching Hybrid . This novel architecture combines the merits of a hydrostatic transmission as well as a series hybrid and separates the power transmission and energy recovery function to achieve better drivability. The hydrostatic mode facilitates stiff response and hence, a good driving experience. On the other hand the energy recovered through regenerative braking can be used at a later time to boost the performance of the vehicle by operating it in secondary control mode. The aim of this work is to design the mode switching hybrid for an on-highway vehicle and implement it on a prototype and develop control strategies to improve its drivability. For this work, a non linear system model was developed and the operating modes like acceleration, deceleration and braking along with energy recovery were simulated. The model was linearized and control strategies were developed to improve the drivability of the vehicle. A 1999 Range Rover 4.0 was selected as the prototype vehicle to test the new transmission. A packaging architecture was designed using 3D modeling and implemented on the prototype vehicle. A data acquisition system was designed to record different parameters while conducting the experiments. Different control strategies were implemented and the performance of these control strategies was demonstrated

Asset Management in Grid Companies Using Integrated Diagnostic Devices

The digitization of power grids envisages a transition to new models of fault diagnosis, repair and maintenance of electric power grid equipment. The most promising tools for implementing advanced production asset management strategies are integrated technologies that are based on robotic diagnostic platforms, various hardware–software instruments and smart data analysis systems. The article analyzes other countries’ experience of developing robotic methods of fault diagnosis and maintenance of overhead power transmission lines, which present a major challenge in terms of monitoring, failure prediction and localized repairs. The Cablewalker robotic system was used as an example for identifying the advantages of integrated diagnostic hardware systems as opposed to traditional methods of power grid equipment maintenance and overhaul. Recommendations are given for adopting the technology in grid companies. During trials of the technology on a 2.34-km section of a power transmission line 112 defects were detected versus three that were identified by means of ‘manual’ inspection. A digital twin of the transmission line was created to manage its technical condition with regard to various risks.The work was supported by Act 211 of the Government of the Russian Federation, contract № 02.A03.21.0006

A Review of the Monitoring of Market Power The Possible Roles of TSOs in Monitoring for Market Power Issues in Congested Transmission Systems

The paper surveys the literature and publicly available information on market power monitoring in electricity wholesale markets. After briefly reviewing definitions, strategies and methods of mitigating market power we examine the various methods of detecting market power that have been employed by academics and market monitors/regulators. These techniques include structural and behavioural indices and analysis as well as various simulation approaches. The applications of these tools range from spot market mitigation and congestion management through to long-term market design assessment and merger decisions. Various market-power monitoring units already track market behaviour and produce indices. Our survey shows that these units collect a large amount of data from various market participants and we identify the crucial role of the transmission system operators with their access to dispatch and system information. Easily accessible and comprehensive data supports effective market power monitoring and facilitates market design evaluation. The discretion required for effective market monitoring is facilitated by institutional independence

Modeling and managing energy consumption of mobile devices

Thanks to the significant improvement in the processing and networking capabilities of mobile devices, mobile devices today can run applications that require complex computation and high network bandwidth. As these applications become ever more popular, a rise is seen in the energy demand that is generated by a typical usage of mobile devices, with the result that existing battery technology is not able to satisfy the growing demand. Improving the energy efficiency of mobile devices and applications has, therefore, become essential. In this thesis, we investigate the energy consumption of mobile devices and propose practical solutions for improving the energy efficiency of wireless data transmission. We propose power models of wireless data transmission over Wi-Fi and show how the power consumption is related to power-saving mechanisms, to Internet traffic characteristics, and to the network throughput. We utilize the linear dependency of transmission costs on network throughput in order to extend the linear regression power models from microprocessor level to system level. These power models provide us with an insight into developing software with energy-efficient wireless data transmission. In this thesis, we present three strategies for reducing transmission cost: applying lossless data compression to network traffic data, scheduling the transmission based on the prediction of network conditions, and power management of the wireless network interface based on the predicted traffic intervals. Our strategies consider the trade-offs between computational and transmission costs, and between energy consumption and transmission performance. In addition, we apply statistical methods for implementing prediction utilities. Finally, considering the complexity in the context collection and processing, we propose an event-driven framework that can be used for implementing, deploying and managing various energy-efficient strategies on mobile platforms