Multi-agent systems for power engineering applications - part 2 : Technologies, standards and tools for building multi-agent systems

This is the second part of a 2-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part 1 of the paper examined the potential value of MAS technology to the power industry, described fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications, and presented a comprehensive review of the power engineering applications for which MAS are being investigated. It also defined the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part 2 of the paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented. Given the significant and growing interest in this field, it is imperative that the power engineering community considers the standards, tools, supporting technologies and design methodologies available to those wishing to implement a MAS solution for a power engineering problem. The paper describes the various options available and makes recommendations on best practice. It also describes the problem of interoperability between different multi-agent systems and proposes how this may be tackled

Multi-agent systems for power engineering applications - part 1 : Concepts, approaches and technical challenges

This is the first part of a 2-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part 1 of the paper examines the potential value of MAS technology to the power industry. In terms of contribution, it describes fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications. As well as presenting a comprehensive review of the meaningful power engineering applications for which MAS are being investigated, it also defines the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part 2 of the paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented

Designing an innovative educational toolbox to support the transition to new technologies

Our economies and societies are becoming more and more knowledge based which implies that increasing numbers of people need to be educated and trained on new subjects and processes. Thus, the reduction of the effort needed to design and prepare educational and training programmes that meet the needs of the society and the market is of paramount importance. To achieve this goal, first, we define a learning programme model so that programme designers can easily exchange and re-use programme structures and learning materials. The proposed model additionally enables easier creation of interdisciplinary programmes which is another need of today’s market. Second, we deploy a web-based tool that adopts this model towards facilitating the re-use of structures and materials. Third, to reduce the time required for the training actors to sense the market needs, we propose the establishment of an educational programme marketplace. All three endeavours have been validated in the energy transition sector and (positively) evaluated by experts during an international workshop

Design and Accuracy Analysis of Multilevel State Estimation Based on Smart Metering Infrastructure

© 1963-2012 IEEE. While the initial aim of smart meters is to provide energy readings for billing purposes, the availability of these measurements could open new opportunities for the management of future distribution grids. This paper presents a multilevel state estimator that exploits the smart meter measurements for monitoring both low and medium voltage grids. The goal of this paper is to present an architecture that is able to efficiently integrate smart meter measurements and to show the accuracy performance achievable if the use of real-Time smart meter measurements for state estimation purposes was enabled. The design of the state estimator applies the uncertainty propagation theory for the integration of the data at different hierarchical levels. The coordination of the estimation levels is realized through a cloud-based infrastructure, which also provides the interface to auxiliary functions and the access to the estimation results for other distribution grid management applications. A mathematical analysis is performed to characterize the estimation algorithm in terms of accuracy and to show the performance achievable at different levels of the distribution grid when using the smart meter data. Simulations are presented, which validate the analytical results and demonstrate the operation of the multilevel estimator in coordination with the cloud-based platform

Archetyps of wisdom: intercultural communication competences training in multicultural students groups

This paper presents a new approach to the problem of system decoupling in a power-system state estimation problem. The complexity of power systems is growing, thus challenging the way measurements for state estimation are traditionally managed. Following a previous experience in defining a decentralized solution for state estimation, the authors here propose a decentralized dynamic state estimation method for a large-scale power system in combination with a procedure to automatically identify how and which state information to exchange for reconstructing the states starting from partial knowledge. In particular, the problem of selecting the variables that each observer has to estimate is partially solved within the framework of a stochastic approach, i.e., the so-called collocation method. An optimization algorithm based on dynamic programming is also developed to determine the optimal set of strongly coupled variables necessary for a sufficiently accurate estimation. The developed method is evaluated by applying to an IEEE test bus system

An efficient and accurate solution for distribution system state estimation with multiarea architecture

Distribution system state estimation (DSSE) is an essential tool for the management and control of future distribution networks. Distribution grids are usually characterized by a very large number of nodes and different voltage levels. Moreover, different portions of the system can be operated by different distribution system operators. In this context, multiarea approaches are key tools to efficiently perform DSSE. This paper presents a novel approach for multiarea state estimation in distribution systems. The proposed algorithm is based on a two-step procedure, where the first-step local estimations are refined through a newly designed second step that allows the integration of the measurement information available in the adjacent areas. The main novelty in this paper is the mathematical analysis of the impact brought by possible measurements shared among different areas, which drives the design of a new efficient weighted least squares formulation of the second step to maximize the achievable estimation accuracy. Tests performed on the unbalanced IEEE 123-bus network prove the goodness of the new multiarea estimator proposed and show the accuracy and efficiency enhancements obtainable with respect to previous literature

Low voltage system state estimation based on smart metering infrastructure

© 2016 IEEE. The accurate monitoring of distribution grids is essential to enable the intelligent management and control of future Smart Grids. Several challenges prevent an easy development of the state estimation tools needed to assess the operating conditions of distribution networks. The lack of a suitable measurement infrastructure is one of the most challenging aspects to face. However, in last years, several utilities started a massive deployment of smart meters in their networks. The proper use of these measurements is key to enhance the performance of distribution system state estimators. This paper presents a two-level approach conceived to efficiently include smart meter measurements in low voltage grid state estimation. The proposed solution relies on a cloud-based smart metering architecture, which allows scalability and interoperability among different off-the-shelf meters. Moreover, a suitable design of the estimation algorithm, using the uncertainty propagation theory, is proposed in order to maximize the accuracy of the estimation results. Tests performed on a sample low voltage network show the performance and the main features of the proposed state estimation solution

A cloud-based smart metering infrastructure for distribution grid services and automation

© 2017 The Authors The evolution of the power systems towards the smart grid paradigm is strictly dependent on the modernization of distribution grids. To achieve this target, new infrastructures, technologies and applications are increasingly required. This paper presents a smart metering infrastructure that unlocks a large set of possible services aimed at the automation and management of distribution grids. The proposed architecture is based on a cloud solution, which allows the communication with the smart meters from one side and provides the needed interfaces to the distribution grid services on the other one. While a large number of applications can be designed on top of the cloud, in this paper the focus will be on a real-time distributed state estimation algorithm that enables the automatic reconfiguration of the grid. The paper will present the key role of the cloud solution for obtaining scalability, interoperability and flexibility, and for enabling the integration of different services for the automation of the distribution system. The distributed state estimation algorithm and the automatic network reconfiguration will be presented as an example of coordinated operation of different distribution grid services through the cloud

Bayesian Approach for Distribution System State Estimation With Non-Gaussian Uncertainty Models

To deal with the increasing complexity of distribution networks that are experiencing important changes, due to the widespread installation of distributed generation and the expected penetration of new energy resources, modern control applications must rely on an accurate picture of the grid status, given by the distribution system state estimation (DSSE). The DSSE is required to integrate all the available information on loads and generators power exchanges (pseudomeasurements) with the real-time measurements available from the field. In most cases, the statistical behavior of the measured and pseudomeasured quantities cannot be approximated by a Gaussian distribution. For this reason, it is necessary to design estimators that are able to use measurements and forecast data on power flows that can show a non-Gaussian behavior. In this paper, a DSSE algorithm based on Bayes's rule, conceived to perfectly match the uncertainty description of the available input information, is presented. The method is able to correctly handle the measurement uncertainty of conventional and synchronized measurements and to include possible correlation existing between the pseudomeasurements. Its applicability to medium voltage distribution networks and its advantages, in terms of accuracy of both estimated quantities and uncertainty intervals, are demonstrated

The Eastern Orthodox Church in New Zealand

This thesis is a study of the Eastern Orthodox Church in New Zealand. It examines both the ethnic jurisdictions and the recent phenomenon of conversion to Eastern Orthodoxy. The opening chapter provides a brief history of Eastern Orthodoxy by concentrating on a number of major events. The second chapter describes the ethnic jurisdictions found in New Zealand and examines local origins and subsequent development. The first of two hypotheses tested in this thesis is discussed in Chapter 3. It is argued that Church affiliation inhibits immigrant assimilation into the wider society. Data obtained from an Interview Schedule and personal observations are deployed to test this hypothesis. Those Orthodox Churches which have a high ethnic membership are shown to display signs of ethnoreligion and ethnocentrism. The second hypothesis, discussed in Chapter 4, suggests that converts are motivated to change denominational allegiance because of feelings of deficiency and the desire for an intergrative force in modern society. Because of a lack of evidence the second claim of this hypothesis remains untested. The conclusion is reached that converts to Eastern Orthodoxy are influenced by two different motivations. It is argued that converts to the ethnic jurisdictions are, in general, motivated by a sense of personal searching. In contrast, most converts to the Antiochian Orthodox Church represent, in general, a change of denominational affiliation in reaction to what is perceived as unacceptable doctrinal change in the Anglican Church