Optimal Operation of Active Distribution Network Involving the Unbalance and Harmonic Compensation of Converter

Jian, Wang; Zhou, Niancheng; Ran, Yunhao; Wang, Qianggang

doi:10.1109/tsg.2018.2880680

Cited by 32 publications

(7 citation statements)

References 33 publications

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“…However, without this assumption, trading through an auction design, as described by, e.g., Block et al [9] or Buchmann et al [8], and implemented in a smart contract by Mengelkamp et al [6] is not possible. Unfortunately, this forecasting task is not trivial due to the extremely high volatility of individual households' energy patterns [18]. However, research by Arora and Taylor [21], Kong et al [22], Shi et al [23], and Li et al [24] shows that advances in the energy forecasting field also extend to household-level energy forecasting problems and serve as a promising basis for the present study.…”

Section: Related Researchmentioning

confidence: 91%

“…Despite this, it is frequently assumed in existing research on (blockchain-based) LEMs that such accurate forecasts are readily available (see, e.g., [6][7][8]16,17]). However, forecasting the consumption/production of single households is difficult due to the inherently high degree of uncertainty, which cannot be reduced by the aggregation of households [18]. Hence, the assumption that accurate forecasts are available cannot be taken in practice to be correct.…”

Section: Introductionmentioning

confidence: 99%

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Forecasting in Blockchain-Based Local Energy Markets

Kostmann

Härdle

2019

Energies

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Increasingly volatile and distributed energy production challenges traditional mechanisms to manage grid loads and price energy. Local energy markets (LEMs) may be a response to those challenges as they can balance energy production and consumption locally and may lower energy costs for consumers. Blockchain-based LEMs provide a decentralized market to local energy consumer and prosumers. They implement a market mechanism in the form of a smart contract without the need for a central authority coordinating the market. Recently proposed blockchain-based LEMs use auction designs to match future demand and supply. Thus, such blockchain-based LEMs rely on accurate short-term forecasts of individual households' energy consumption and production. Often, such accurate forecasts are simply assumed to be given. The present research tested this assumption by first evaluating the forecast accuracy achievable with state-of-the-art energy forecasting techniques for individual households and then, assessing the effect of prediction errors on market outcomes in three different supply scenarios. The evaluation showed that, although a LASSO regression model is capable of achieving reasonably low forecasting errors, the costly settlement of prediction errors can offset and even surpass the savings brought to consumers by a blockchain-based LEM. This shows that, due to prediction errors, participation in LEMs may be uneconomical for consumers, and thus, has to be taken into consideration for pricing mechanisms in blockchain-based LEMs.

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Section: Related Researchmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Forecasting in Blockchain-Based Local Energy Markets

Kostmann

Härdle

2019

Energies

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“…Finally, utility interfaces (UIs) were added in each sub-network close to the PCC; these units, equipped with energy storage and three-phase PWM converters, perform as controllable voltage sources and act as voltage trackers during on-grid operation, and as voltage formers during off-grid operation [17][18][19]. Further to their voltage support action, these units allow reactive power and unbalance compensation in the proximity of each PCC, resulting in unity power factor at the utility terminals [20]. This action is possible thanks to the ability of three-phase grid-tied converters to exchange active power among the phases, and to generate compensating reactive power, without requiring net energy from the storage unit, the only limitation being due to the VA rating of the converter.…”

Section: The Considered Benchmark Networkmentioning

confidence: 99%

Generalized Control of the Power Flow in Local Area Energy Networks

Tenti

Caldognetto

2022

Energies

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Local area energy networks (E-LANs) are cyber-physical systems whose physical layer is a meshed low-voltage microgrid fed by a multiplicity of sources, i.e., utilities, energy storage systems, and distributed power sources. The cyber layer includes distributed measurement, control, and communication units, located at end-user premises, as well as centralized supervision and dispatchment control. As compared with standard microgrid, the E-LAN encompasses the ability for end-users to actively contribute to the operation of the microgrid while acting as independent energy traders in the electrical market. Operational goals include active contribution of end-users to power sharing, loss reduction, voltage stability, demand response, fault identification and clearing, isolation of sub-grids for maintenance, islanding, and black start. Economic goals include the possibility, for each end-user, to decide in every moment, based on convenience, how his energy and power capacity is shared with other users, e.g., for demand response or to trade energy in the electric market. This paper introduces a comprehensive theoretical approach of E-LAN control to achieve all the above operational goals while providing a high level of dynamic protection against faults or other events affecting the system functionality, e.g., overloads or fast transients. It shows that meshed microgrids are the necessary infrastructure to implement the desired functionalities.

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“…For example, in [2] the share of electric power costs makes 12 -15 %, and in [1] it makes 16 %. The level of active power losses is directly associated with electric power quality [4][5][6][7][8][9][10][11]. In connection therewith, it is required to improve electric power quality, especially at enterprises with a high share of electric power costs in the prime cost of production.…”

Section: Introductionmentioning

confidence: 99%

“…However, the state standard of the Russian Federation does not standardize either the level of current harmonic distortions, or the level of reactive power, although it is these distortions that primarily increase active power losses, reducing the energy efficiency of an enterprise. There are many devices to improve electric power quality [5,[22][23][24], as well as multiple variants of their connection. Having analyzed the methods for selecting the connection points of compensating devices [25][26][27], a new method based on the point connection of compensating devices directly at the load, which distorts electric power quality, was developed.…”

Section: Introductionmentioning

confidence: 99%

Increasing the energy efficiency of an enterprise by point compensating of power quality distortions

2019

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The cost of any product includes the cost of electrical energy in its production. Enterprises use various methods to reduce the cost of electric energy. One of the most common methods is to reduce the loss of active power in the distribution network of an enterprise. This is achieved by compensating for distortions in the power quality of electrical energy using compensating devices. The method presented in the article offers point compensation of distortions in the power quality indicators of electric energy. Point connection of compensating devices allows their small number to be used. But, at the same time, a greater effect is achieved. The connection points of compensating devices are determined by the developed method. The method includes three stages: collecting data on consumers of electric energy at an enterprise and on the topology of the distribution electric network, analyzing the results obtained using the developed algorithm, and determining connection points using the Pareto method. Also, the developed method was compared with the classical ones according to the criterion of the ratio of implementation costs to the effect of its application.

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Optimal Operation of Active Distribution Network Involving the Unbalance and Harmonic Compensation of Converter

Cited by 32 publications

References 33 publications

Forecasting in Blockchain-Based Local Energy Markets

Forecasting in Blockchain-Based Local Energy Markets

Generalized Control of the Power Flow in Local Area Energy Networks

Increasing the energy efficiency of an enterprise by point compensating of power quality distortions

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