Intelligent Micro Grid Management using a Multi-Agent approach

Recent changes in electricity markets (EMs) have been potentiating the globalization of distributed generation. With distributed generation the number of players acting in the EMs and connected to the main grid has grown, increasing the market complexity. Multi-agent simulation arises as an interesting way of analysing players’ behaviour and interactions, namely coalitions of players, as well as their effects on the market. MASCEM was developed to allow studying the market operation of several different players and MASGriP is being developed to allow the simulation of the micro and smart grid concepts in very different scenarios This paper presents a methodology based on artificial intelligence techniques (AI) for the management of a micro grid. The use of fuzzy logic is proposed for the analysis of the agent consumption elasticity, while a case based reasoning, used to predict agents’ reaction to price changes, is an interesting tool for the micro grid operator.

Load Profiling Tool to Support Smart Grid Operation Scenarios

This paper presents the characterization of high voltage (HV) electric power consumers based on a data clustering approach. The typical load profiles (TLP) are obtained selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The choice of the best partition is supported using several cluster validity indices. The proposed data-mining (DM) based methodology, that includes all steps presented in the process of knowledge discovery in databases (KDD), presents an automatic data treatment application in order to preprocess the initial database in an automatic way, allowing time saving and better accuracy during this phase. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ consumption behavior. To validate our approach, a case study with a real database of 185 HV consumers was used.

Performance of small wind turbines: simulation of electricity supply to loads connected to the public or isolated grid

ABSTRACT The successful in the implementation of wind turbines depends on several factors, including: the wind resource at the installation site, the equipment used, project acquisition and operational costs. In this paper, the production of electricity from two small wind turbines was compared through simulation using the computer software HOMER - a national model of 6kW and an imported one of 5kW. The wind resources in three different cities were considered: Campinas (SP/BR), Cubatão (São Paulo/BR) and Roscoe (Texas/ USA). A wind power system connected to the grid and a wind isolated system - batteries were evaluated. The results showed that the energy cost ($/kWh) is strongly dependent on the windmill characteristics and local wind resource. Regarding the isolated wind system – batteries, the full supply guarantee to the simulated electrical load is only achieved with a battery bank with many units and high number of wind turbines, due to the intermittency of wind power.

State of the Art and Future Trends in Grid Codes Applicable to Isolated Electrical Systems

Isolated electrical systems lack electrical interconnection to other networks and are usually placed in geographically isolated areas—mainly islands or locations in developing countries. Until recently, only diesel generators were able to assure a safe and reliable supply in exchange for very high costs for fuel transportation and system operation. Transmission system operators (TSOs) are increasingly seeking to replace traditional energy models based on large groups of conventional generation units with mixed solutions where diesel groups are held as backup generation and important advantages are provided by renewable energy sources. The grid codes determine the technical requirements to be fulfilled by the generators connected in any electrical network, but regulations applied to isolated grids are more demanding. In technical literature it is rather easy to find and compare grid codes for interconnected electrical systems. However, the existing literature is incomplete and sparse regarding isolated grids. This paper aims to review the current state of isolated systems and grid codes applicable to them, specifying points of comparison and defining the guidelines to be followed by the upcoming regulations.

Experiments on the red and quill Peruvian bark: with observations on its history, mode of operation, and uses; and on some other subjects connected with the phænomena and doctrines of vegetable astringents. Being a dissertation which gained the first prize given by the Harveian Society of Edinburgh for the year 1784.

Numbers 133-136 repeated in the pagination.

Fully Connected PLL Networks: How Filter Determines the Number of Nodes

Synchronization plays an important role in telecommunication systems, integrated circuits, and automation systems. Formerly, the masterslave synchronization strategy was used in the great majority of cases due to its reliability and simplicity. Recently, with the wireless networks development, and with the increase of the operation frequency of integrated circuits, the decentralized clock distribution strategies are gaining importance. Consequently, fully connected clock distribution systems with nodes composed of phase-locked loops (PLLs) appear as a convenient engineering solution. In this work, the stability of the synchronous state of these networks is studied in two relevant situations: when the node filters are first-order lag-lead low-pass or when the node filters are second-order low-pass. For first-order filters, the synchronous state of the network shows to be stable for any number of nodes. For second-order filter, there is a superior limit for the number of nodes, depending on the PLL parameters. Copyright (C) 2009 Atila Madureira Bueno et al.

Reachability of the synchronous state in a mutually connected PLL network

Second-order phase locked loops (PLLs) are devices that are able to provide synchronization between the nodes in a network even under severe quality restrictions in the signal propagation. Consequently, they are widely used in telecommunication and control. Conventional master-slave (M-S) clock-distribution systems are being, replaced by mutually connected (MC) ones due to their good potential to be used in new types of application such as wireless sensor networks, distributed computation and communication systems. Here, by using an analytical reasoning, a nonlinear algebraic system of equations is proposed to establish the existence conditions for the synchronous state in an MC PLL network. Numerical experiments confirm the analytical results and provide ideas about how the network parameters affect the reachability of the synchronous state. The phase-difference oscillation amplitudes are related to the node parameters helping to design PLL neural networks. Furthermore, estimation of the acquisition time depending on the node parameters allows the performance evaluation of time distribution systems and neural networks based on phase-locked techniques. (c) 2008 Elsevier GmbH. All rights reserved.

Mutually connected phase-locked loop networks: dynamical models and design parameters

Distribution of timing signals is an essential factor for the development of digital systems for telecommunication networks, integrated circuits and manufacturing automation. Originally, this distribution was implemented by using the master-slave architecture with a precise master clock generator sending signals to phase-locked loops (PLL) working as slave oscillators. Nowadays, wireless networks with dynamical connectivity and the increase in size and operation frequency of the integrated circuits suggest that the distribution of clock signals could be more efficient if mutually connected architectures were used. Here, mutually connected PLL networks are studied and conditions for synchronous states existence are analytically derived, depending on individual node parameters and network connectivity, considering that the nodes are nonlinear oscillators with nonlinear coupling conditions. An expression for the network synchronisation frequency is obtained. The lock-in range and the transmission error bounds are analysed providing hints to the design of this kind of clock distribution system.

MASGriP – a Multi-Agent Smart Grid Simulation Platform

The increasing number of players that operate in power systems leads to a more complex management. In this paper a new multi-agent platform is proposed, which simulates the real operation of power system players. MASGriP – A Multi-Agent Smart Grid Simulation Platform is presented. Several consumer and producer agents are implemented and simulated, considering real characteristics and different goals and actuation strategies. Aggregator entities, such as Virtual Power Players and Curtailment Service Providers are also included. The integration of MASGriP agents in MASCEM (Multi-Agent System for Competitive Electricity Markets) simulator allows the simulation of technical and economical activities of several players. An energy resources management architecture used in microgrids is also explained.

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

Using demand response to deal with unexpected low wind power generation in the context of smart grid

Demand response is assumed an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed aims the minimization of the operation costs in a smart grid operated by a virtual power player. It is especially useful when actual and day ahead wind forecast differ significantly. When facing lower wind power generation than expected, RTP is used in order to minimize the impacts of such wind availability change. The proposed model application is here illustrated using the scenario of a special wind availability reduction day in the Portuguese power system (8th February 2012).

Natural gas system operation: lagrangean optimization techniques

To comply with natural gas demand growth patterns and Europe´s import dependency, the gas industry needs to organize an efficient upstream infrastructure. The best location of Gas Supply Units – GSUs and the alternative transportation mode – by phisical or virtual pipelines, are the key of a successful industry. In this work we study the optimal location of GSUs, as well as determining the most efficient allocation from gas loads to sources, selecting the best transportation mode, observing specific technical restrictions and minimizing system total costs. For the location of GSUs on system we use the P-median problem, for assigning gas demands nodes to source facilities we use the classical transportation problem. The developed model is an optimisation-based approach, based on a Lagrangean heuristic, using Lagrangean relaxation for P-median problems – Simple Lagrangean Heuristic. The solution of this heuristic can be improved by adding a local search procedure - the Lagrangean Reallocation Heuristic. These two heuristics, Simple Lagrangean and Lagrangean Reallocation, were tested on a realistic network - the primary Iberian natural gas network, organized with 65 nodes, connected by physical and virtual pipelines. Computational results are presented for both approaches, showing the location gas sources and allocation loads arrangement, system total costs and gas transportation mode.

Distribution network short term scheduling in Smart Grid context

The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.

Scheduling distributed energy resources in an isolated grid - an artificial neural network approach

Power Systems (PS), have been affected by substantial penetration of Distributed Generation (DG) and the operation in competitive environments. The future PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. Virtual power players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. This paper proposes an artificial neural network (ANN) based methodology to support VPP resource schedule. The trained network is able to achieve good schedule results requiring modest computational means. A real data test case is presented.