Research on ancillary service management mechanism in the smart grid

2011 ◽  
Author(s):  
Ju Ge ◽  
Shasha Luo ◽  
Chen Chen
Keyword(s):  
Smart Grid ◽  
Service Management ◽  
Ancillary Service ◽  
Management Mechanism

Proposed DSO ancillary service processes considering smart grid requirements

2017 ◽  
Vol 2017 (1) ◽  
pp. 2846-2847 ◽  
Author(s):  
Ahmad Alkandari ◽  
Ayman Ahmed Sami ◽  
Ahmed Sami
Keyword(s):  
Smart Grid ◽  
Ancillary Service

scholarly journals Droop based Demand Dispatch for Residential Loads in Smart Grid Application

2018 ◽  
Vol 19 (3) ◽  
Author(s):  
Andisheh Ashourpouri ◽  
Arindam Ghosh ◽  
Sumedha Rajakaruna
Keyword(s):  
Smart Grid ◽  
Power Consumption ◽  
Power System ◽  
Demand Side ◽  
Ancillary Service ◽  
Generation System ◽  
Demand And Supply ◽  
Grid Application ◽  
Aggregated Load ◽  
Maximum Minimum

Abstract Aggregated loads play a significant role in maintaining the frequency of power system when the generation is not able to follow frequency deviations. An automatic Demand Dispatch (DD) enables the power system to employ the aggregated loads for balancing demand and supply. In this paper, a Demand Side Frequency Droop (DSFD) has been proposed which provides ancillary service to the grid and maintains the frequency of the power system when the generation system is not capable of following the demand. At the time of a frequency fall/rise, Balancing Authority (BA) can detect aggregated load or group of aggregated loads that have power consumption above or below their standard maximum/minimum consumption levels. Then, the BA issues a droop-based signal to the relevant aggregator. Afterwards, the DSFD will be implemented in the aggregator or the group of aggregators to specify the required power consumption amount for bringing the frequency back to its rated level. Subsequently, this signal will be sent to the Appliance Management Unit (AMU) at each participating house. The AMU sends the signal in the form of deferral or interruptible commands to the appliances depending on the priority, availability and the specification of the appliances. It will be demonstrated that the proposed DSFD control maintains the frequency of the power system within a specified range.

The Value of Demand Response (DR) to Mitigate Wind Integration Costs in a Smart Grid

2011 ◽  
Author(s):  
Nikhil Kumar ◽  
Steven A. Lefton
Keyword(s):  
Smart Grid ◽  
Demand Response ◽  
Power Plants ◽  
Ancillary Service ◽  
Wind Integration ◽  
Load Following ◽  
Point Of Interest ◽  
Generation Capacity ◽  
Energy Products ◽  
Variable Wind

In the last five years the electric grid worldwide has seen increasing amounts of installed wind generation capacity. Over the last five years, North America (USA and Canada) has witnessed wind capacity grow at an annual rate of over 30%. At the same time, increasing investments in smart grid technologies have enabled improvements in energy products such as Demand Response (DR). The utility industry, system operators and regulators are investing heavily to understand and determine the impacts of increasing wind penetration on the power system. As explored below, an often neglected, but important point of interest to the authors has been the effect of increased cycling of large fossil, formerly base loaded power plants due to increasing penetration of variable wind or solar power. Various types of DR programs have been implemented by utilities and system operators and these DR programs may be classified based on the time it takes to call upon a DR event or the energy market that the programs are allowed to participate within. Hence, we may have a “slow” DR that participates in a Day-Ahead market and the events are called upon well in advance. On the other hand, “fast” DR programs would participate in Real-Time and Ancillary Services markets. DR from a power dispatch perspective can be considered a “virtual power plant” providing energy, ancillary service and capacity in energy markets. Energy benefits of DR have been explored extensively, especially in terms of reduced fuel costs due to reduction in demand. In this paper we explore the conceptual use and value of DR in providing benefits associated with reduced damage to a fleet of fossil-fueled power plants if it is used to reduce startups and/or load following/cycling.

scholarly journals Model-based Approach to Multi-domain Monitoring Data Aggregation

2021 ◽  
Author(s):  
Antonio Pastor ◽  
Diego R. López ◽  
Jose Ordonez-Lucena ◽  
Sonia Fernández ◽  
Jesús Folgueira
Keyword(s):  
Data Aggregation ◽  
Service Management ◽  
Closed Loop ◽  
Ad Hoc ◽  
Data Sources ◽  
Management Mechanism ◽  
Model Based ◽  
Closed Loop Systems ◽  
Disparate Data ◽  
Network Orchestration

The essential propellant for any closed-loop management mechanism is data related to the managed entity. While this is a general evidence, it becomes even more true when dealing with advanced closed-loop systems like the ones supported by Artificial Intelligence (AI), as they require a trustworthy, up-to-date and steady flow of state data to be applicable. Modern network infrastructures provide a vast amount of disparate data sources, especially in the multi-domain scenarios considered by the ETSI Industry Specification Group (ISG) Zero Touch Network and Service Management (ZSM) framework, and proper mechanisms for data aggregation, pre-processing and normalization are required to make possible AI-enabled closed-loop management. So far, solutions proposed for these data aggregation tasks have been specific to concrete data sources and consumers, following ad-hoc approaches unsuitable to address the vast heterogeneity of data sources and potential data consumers. This paper presents a model-based approach to a data aggregator framework, relying on standardized data models and telemetry protocols, and integrated with an open-source network orchestration stack to support their incorporation within network service lifecycles.

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