Modeling smart grids as complex systems through the implementation of intelligent hubs

ICINCO 2010

Implementation Experiences from Smart Grid Security Applications and Outlook on Future Research

Experiences from smart grid cyber-security incidents in the past decade have raised questions on the applicability and effectiveness of security measures and protection mechanisms applied to the grid. In this chapter we focus on the security measures applied under real circumstances in today’s smart grid systems. Beginning from real world example implementations, we first review cyber-security facts that affected the electrical grid, from US blackout incidents, to the Dragonfly cyber-espionage campaign currently focusing on US and European energy firms. Provided a real world setting, we give information related to energy management of a smart grid looking also in the optimization techniques that power control engineers perform into the grid components. We examine the application of various security tools in smart grid systems, such as intrusion detection systems, smart meter authentication and key management using Physical Unclonable Functions, security analytics and resilient control algorithms. Furthermore we present evaluation use cases of security tools applied on smart grid infrastructure test-beds that could be proved important prior to their application in the real grid, describing a smart grid intrusion detection system application and security analytics results. Anticipated experimental results from the use-cases and conclusions about the successful transitions of security measures to real world smart grid operations will be presented at the end of this chapter.

People or machines? Assessing the impacts of smart meters and load controllers in Italian office spaces

Government initiatives in several developed and developing countries to roll-out smart meters call for research on the sustainability impacts of these devices. In principle smart meters bring about higher control over energy theft and lower consumption, but require a high level of engagement by end-users. An alternative consists of load controllers, which control the load according to pre-set parameters. To date, research has focused on the impacts of these two alternatives separately. This study compares the sustainability impacts of smart meters and load controllers in an occupied office building in Italy. The assessment is carried out on three different floors of the same building. Findings show that demand reductions associated with a smart meter device are 5.2% higher than demand reductions associated with the load controller.

Short-term Load Forecasting Using Neural Network For Future Smart Grid Application

Short-term load forecasting of power system has been a classic problem for a long time. Not merely it has been researched extensively and intensively, but also a variety of forecasting methods has been raised. This thesis outlines some aspects and functions of smart meter. It also presents different policies and current statuses as well as future projects and objectives of SG development in several countries. Then the thesis compares main aspects about latest products of smart meter from different companies. Lastly, three types of prediction models are established in MATLAB to emulate the functions of smart grid in the short-term load forecasting, and then their results are compared and analyzed in terms of accuracy. For this thesis, more variables such as dew point temperature are used in the Neural Network model to achieve more accuracy for better short-term load forecasting results.

Beyond demand management : the value of sharing electricity information

Technologies such as smart meters and electricity feedback are becoming an increasingly compelling focus for HCI researchers in light of rising power prices and peak demand. We argue, however, that a pre-occupation with the goal of demand management has limited the scope of design for these technologies. In this paper we present our work-in-progress investigating the potential value of socially sharing electricity information as a means of broadening the scope of design for these devices. This paper outlines some preliminary findings gathered from a design workshop and a series of qualitative interviews with householders in Brisbane, Australia, regarding their attitudes towards electricity feedback and sharing consumption information. Preliminary findings suggest that; (1) the social sharing of electricity feedback information has the potential to be of value in better informing consumption decisions, however; (2) the potential for sharing may be constrained by attitudes towards privacy, trust and the possibility of misinformation being shared. We conclude by outlining ideas for our future research on this topic and invite comments on these ideas.

Correlation based method for phase identification in a three phase LV distribution network

Low voltage distribution networks feature a high degree of load unbalance and the addition of rooftop photovoltaic is driving further unbalances in the network. Single phase consumers are distributed across the phases but even if the consumer distribution was well balanced when the network was constructed changes will occur over time. Distribution transformer losses are increased by unbalanced loadings. The estimation of transformer losses is a necessary part of the routine upgrading and replacement of transformers and the identification of the phase connections of households allows a precise estimation of the phase loadings and total transformer loss. This paper presents a new technique and preliminary test results for a method of automatically identifying the phase of each customer by correlating voltage information from the utility's transformer system with voltage information from customer smart meters. The techniques are novel as they are purely based upon a time series of electrical voltage measurements taken at the household and at the distribution transformer. Experimental results using a combination of electrical power and current of the real smart meter datasets demonstrate the performance of our techniques.

Consumer phase identification in a three phase unbalanced LV distribution network

A new technique is presented for automatically identifying the phase connection of domestic customers. Voltage information from a reference three phase house is correlated with voltage information from other customer electricity meters on the same network to determine the highest probability phase connection. The techniques are purely based upon a time series of electrical voltage measurements taken by the household smart meters and no additional equipment is required. The method is demonstrated using real smart meter datasets to correctly identify the phase connections of 75 consumers on a low voltage distribution feeder.

Graph-based algorithms for comparison and prediction of household-level energy use profiles

We present an efficient graph-based algorithm for quantifying the similarity of household-level energy use profiles, using a notion of similarity that allows for small time–shifts when comparing profiles. Experimental results on a real smart meter data set demonstrate that in cases of practical interest our technique is far faster than the existing method for computing the same similarity measure. Having a fast algorithm for measuring profile similarity improves the efficiency of tasks such as clustering of customers and cross-validation of forecasting methods using historical data. Furthermore, we apply a generalisation of our algorithm to produce substantially better household-level energy use forecasts from historical smart meter data.

Control methodologies: Peak reduction algorithms for DNO owned storage devices on the Low Voltage network

The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

Long term individual load forecast under different electrical vehicles uptake scenarios

More and more households are purchasing electric vehicles (EVs), and this will continue as we move towards a low carbon future. There are various projections as to the rate of EV uptake, but all predict an increase over the next ten years. Charging these EVs will produce one of the biggest loads on the low voltage network. To manage the network, we must not only take into account the number of EVs taken up, but where on the network they are charging, and at what time. To simulate the impact on the network from high, medium and low EV uptake (as outlined by the UK government), we present an agent-based model. We initialise the model to assign an EV to a household based on either random distribution or social influences - that is, a neighbour of an EV owner is more likely to also purchase an EV. Additionally, we examine the effect of peak behaviour on the network when charging is at day-time, night-time, or a mix of both. The model is implemented on a neighbourhood in south-east England using smart meter data (half hourly electricity readings) and real life charging patterns from an EV trial. Our results indicate that social influence can increase the peak demand on a local level (street or feeder), meaning that medium EV uptake can create higher peak demand than currently expected.

Investigating preferences for dynamic electricity tariffs: the effect of environmental and system benefit disclosure

Dynamic electricity pricing can produce efficiency gains in the electricity sector and help achieve energy policy goals such as increasing electric system reliability and supporting renewable energy deployment. Retail electric companies can offer dynamic pricing to residential electricity customers via smart meter-enabled tariffs that proxy the cost to procure electricity on the wholesale market. Current investments in the smart metering necessary to implement dynamic tariffs show policy makers’ resolve for enabling responsive demand and realizing its benefits. However, despite these benefits and the potential bill savings these tariffs can offer, adoption among residential customers remains at low levels. Using a choice experiment approach, this paper seeks to determine whether disclosing the environmental and system benefits of dynamic tariffs to residential customers can increase adoption. Although sampling and design issues preclude wide generalization, we found that our environmentally conscious respondents reduced their required discount to switch to dynamic tariffs around 10% in response to higher awareness of environmental and system benefits. The perception that shifting usage is easy to do also had a significant impact, indicating the potential importance of enabling technology. Perhaps the targeted communication strategy employed by this study is one way to increase adoption and achieve policy goals.

Sistema de medição de energia baseado no medidor de energia Teridian 71M6515H

Esta tese de mestrado descreve o desenvolvimento, implementação e teste de um sistema de medição de energia concebido para um ambiente doméstico, baseado no circuito integrado medidor de energia Teridian 71M6515H. O sistema desenvolvido envia periodicamente os valores monitorizados para uma base de dados, através de uma rede sem fios com base no protocolo IEEE 802.11 (Wi-Fi). Os dados podem ser acedidos remotamente em tempo real, através de uma página na internet, onde é possível consultar a quantidade de energia consumida acumulada. Na primeira fase deste trabalho realizou-se o enquadramento do tema no contexto atual, realizando-se o estudo de alguns sistemas domésticos de monitorização do consumo de energia elétrica existentes no mercado. Numa segunda fase foi realizado o estudo dos componentes a serem utilizados, o desenho da placa de circuito impresso e o desenvolvimento do firmware, para que todo o processamento e manipulação dos dados fossem realizados pela unidade de aquisição de dados. Em seguida procedeu-se à construção da unidade de aquisição e à programação para o registo dos valores numa base de dados. A última fase consistiu nos testes de funcionamento da unidade de aquisição em conjunto com a aplicação de registo de dados. Com a implementação do sistema desenvolvido o consumidor doméstico poderá ter conhecimento, em tempo real, do custo de funcionamento dos equipamentos que possui e assim tomar decisões para os utilizar de forma mais racional, o que se pode traduzir numa economia dos recursos energéticos.

O papel dos consumidores residencias no ambiente das redes inteligentes: medidores eletrônicos de energia

Pós-graduação em Engenharia Mecânica - FEG

Load analyser using conservative power theory

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Impatto della propagazione elettromagnetica sulle prestazioni delle reti M3N

Con il termine Smart Grid si intende una rete urbana capillare che trasporta energia, informazione e controllo, composta da dispositivi e sistemi altamente distribuiti e cooperanti. Essa deve essere in grado di orchestrare in modo intelligente le azioni di tutti gli utenti e dispositivi connessi al fine di distribuire energia in modo sicuro, efficiente e sostenibile. Questo connubio fra ICT ed Energia viene comunemente identificato anche con il termine Smart Metering, o Internet of Energy. La crescente domanda di energia e l’assoluta necessità di ridurre gli impatti ambientali (pacchetto clima energia 20-20-20 [9]), ha creato una convergenza di interessi scientifici, industriali e politici sul tema di come le tecnologie ICT possano abilitare un processo di trasformazione strutturale di ogni fase del ciclo energetico: dalla generazione fino all’accumulo, al trasporto, alla distribuzione, alla vendita e, non ultimo, il consumo intelligente di energia. Tutti i dispositivi connessi, diventeranno parte attiva di un ciclo di controllo esteso alle grandi centrali di generazione così come ai comportamenti dei singoli utenti, agli elettrodomestici di casa, alle auto elettriche e ai sistemi di micro-generazione diffusa. La Smart Grid dovrà quindi appoggiarsi su una rete capillare di comunicazione che fornisca non solo la connettività fra i dispositivi, ma anche l’abilitazione di nuovi servizi energetici a valore aggiunto. In questo scenario, la strategia di comunicazione sviluppata per lo Smart Metering dell’energia elettrica, può essere estesa anche a tutte le applicazioni di telerilevamento e gestione, come nuovi contatori dell’acqua e del gas intelligenti, gestione dei rifiuti, monitoraggio dell’inquinamento dell’aria, monitoraggio del rumore acustico stradale, controllo continuo del sistema di illuminazione pubblico, sistemi di gestione dei parcheggi cittadini, monitoraggio del servizio di noleggio delle biciclette, ecc. Tutto ciò si prevede possa contribuire alla progettazione di un unico sistema connesso, dove differenti dispositivi eterogenei saranno collegati per mettere a disposizione un’adeguata struttura a basso costo e bassa potenza, chiamata Metropolitan Mesh Machine Network (M3N) o ancora meglio Smart City. Le Smart Cities dovranno a loro volta diventare reti attive, in grado di reagire agli eventi esterni e perseguire obiettivi di efficienza in modo autonomo e in tempo reale. Anche per esse è richiesta l’introduzione di smart meter, connessi ad una rete di comunicazione broadband e in grado di gestire un flusso di monitoraggio e controllo bi-direzionale esteso a tutti gli apparati connessi alla rete elettrica (ma anche del gas, acqua, ecc). La M3N, è un’estensione delle wireless mesh network (WMN). Esse rappresentano una tecnologia fortemente attesa che giocherà un ruolo molto importante nelle futura generazione di reti wireless. Una WMN è una rete di telecomunicazione basata su nodi radio in cui ci sono minimo due percorsi che mettono in comunicazione due nodi. E’ un tipo di rete robusta e che offre ridondanza. Quando un nodo non è più attivo, tutti i rimanenti possono ancora comunicare tra di loro, direttamente o passando da uno o più nodi intermedi. Le WMN rappresentano una tipologia di rete fondamentale nel continuo sviluppo delle reti radio che denota la divergenza dalle tradizionali reti wireless basate su un sistema centralizzato come le reti cellulari e le WLAN (Wireless Local Area Network). Analogamente a quanto successo per le reti di telecomunicazione fisse, in cui si è passati, dalla fine degli anni ’60 ai primi anni ’70, ad introdurre schemi di rete distribuite che si sono evolute e man mano preso campo come Internet, le M3N promettono di essere il futuro delle reti wireless “smart”. Il primo vantaggio che una WMN presenta è inerente alla tolleranza alla caduta di nodi della rete stessa. Diversamente da quanto accade per una rete cellulare, in cui la caduta di una Base Station significa la perdita di servizio per una vasta area geografica, le WMN sono provviste di un’alta tolleranza alle cadute, anche quando i nodi a cadere sono più di uno. L'obbiettivo di questa tesi è quello di valutare le prestazioni, in termini di connettività e throughput, di una M3N al variare di alcuni parametri, quali l’architettura di rete, le tecnologie utilizzabili (quindi al variare della potenza, frequenza, Building Penetration Loss…ecc) e per diverse condizioni di connettività (cioè per diversi casi di propagazione e densità abitativa). Attraverso l’uso di Matlab, è stato quindi progettato e sviluppato un simulatore, che riproduce le caratteristiche di una generica M3N e funge da strumento di valutazione delle performance della stessa. Il lavoro è stato svolto presso i laboratori del DEIS di Villa Grifone in collaborazione con la FUB (Fondazione Ugo Bordoni).