Monthly Archives: February 2017

Expert opinion on energy system models – Dr Sara Walker

co-evolution, Energy Systems,

saraAbout the Author 

Dr. Sara Walker is currently an Associate Director and Co-Investigator for the £20m National Centre for Energy Systems Integration (EP/P001173/1). Dr Walker’s research focus is regarding renewable energy technology and transitions to low carbon systems, with a particular focus on policy and building scale solutions.
Dr. Walker has experience of multi-disciplinary projects. For example, her PhD involved an analysis of the renewable energy sector with regards impact of electricity industry deregulation. This was a multi-disciplinary study which involved analysis of the willingness to pay for renewable electricity products, an economic model of the UK in order to estimate future scenarios of electricity demand growth, and a technical renewable resource assessment.
Dr. Walker was recently a Co-Investigator for a European Interreg funded project, led by University of Hamburg. As part of this €6.5m project, she delivered a review of European funded electric vehicle projects and was involved in the evaluation of vehicle-to-grid technical viability. Dr. Walker has also delivered research to third sector clients Gentoo on Retrofit Reality project funded by Housing Corporation, evaluating impact of energy efficiency retrofit on behaviour and evaluating performance of solar thermal systems. The client went on to use the findings of the work to inform their Pay As You Save and Green Deal offerings.

Contact:- sara.walker@ncl.ac.uk

Expert opinion on energy system models

CESI plans to undertake co-evolution cycles, a currently vaguely defined process of bringing together sectors and energy vectors to consider how they interact. Part of the co-evolution cycle involves consulting with experts to review the work done by the partnership. So how can the expert opinion be beneficial to our consideration of energy systems?

What makes an ‘expert’?

Krueger et al (2012) summarise definitions of an expert as “someone having specialist knowledge acquired through practice (also called training), study (also called education) or experience”. The temptation with energy system models is to ask other energy system modelers for their expert view. However, there are others with local experience and practice who can make a valuable contribution, such as the system operator or system user. Equally, some stakeholders may be considered non-expert but be significantly affected by outcomes of models, and be able to contribute an opinion on the impact of model findings.

Why use the term expert ‘opinion’?

In the modelling literature, expert knowledge, expert opinion, expert judgment and expert elicitation are commonly used to describe some process of obtaining feedback from an expert on some shared information. I have deliberately used the term ‘opinion’ since, in many cases, we are asking for an expert to express a view on a relationship, process or parameter which is unknown, to a greater or lesser extent, and which has an associated uncertainty. This is particularly the case when developing scenarios of the future. What value of population should we use, and how confident are we in that value, for example. Modelling involves many choices around the model structure and the processes represented within it, the parameter values, and the boundary conditions. Often, the model developer as the expert makes choices which are implicit and undocumented. This is something we are seeking to avoid in CESI through the process of gathering expert opinion.

How can expert opinion be collected and collated?

There are a number of methods available for gathering expert opinion. Sadly, none are perfect. A key choice is with respect to eliciting individual expert opinion or eliciting opinion in a group context.
A common method used to reach consensus is the Delphi method, for example, where several iterations of opinion are discussed until consensus is reached. “A Delphi is extremely efficient in obtaining consensus, but this consensus is not based on genuine agreement; rather, it is the result of the same strong group pressure to conformity” (Woudenberg, 1991).

Individual expert opinion gathering Group expert opinion gathering
Advantages Disadvantages Advantages Disadvantages
 Can allow more  targeted questioning,  explanation and  feedback  Time cost  Sharing knowledge  can help discount  unnecessary  information  Can be dominated by  small number of people
 Enables a range of  views to be expressed  individually  Interviewer influence on expert  Can help with  aggregation of  opinions  Can over-emphasise  consensus
 No individual learning  or challenge to the  expert  Interviewer influence on  group
 Group motivation to  reach quick agreement
 Group tendency to be  more overconfident and  overestimate

The framing of the questions is very important in collecting expert opinion. Research has shown that expert opinion contains bias, based on two cognitive heuristics; ‘availability’ and ‘anchoring and adjustment’. ‘Availability’ is when the opinion of the likelihood of something is formed based on personal experience of such instances being recalled. ‘Anchoring and adjustment’ are when a value (anchor) is presented as a first guess at a parameter and the expert is asked to adjust – they typically do not adjust enough and the original anchor influences the decision on the final value (Morgan, 2014).

When discussing expert opinion, we should also consider eliciting each expert’s uncertainty in their opinion, which can be more easily expressed for quantitative rather than qualitative or conceptual issues. Uncertainty is sometimes expressed using the NUSAP approach: Numeral (the best guess value); Unit (the units of the parameter); Spread, Assessment (descriptions of uncertainty about the numeral); and Pedigree (a subjective evaluation of confidence in the evidence which support the assumptions within the other elements) (Morgan, 2014; Krueger et al, 2012). Consensus is a method of aggregation of both opinion and uncertainty. In some situations, expert opinion may differ and so mathematical aggregation may be appropriate in order to represent a range of views. Sometimes it is best not to aggregate at all, and to take the diverse views as different case study values to produce a range of scenarios. This way it is possible to identify how much the difference in expert opinion can affect the outcome of the model.

How many experts does it take to check a model?

Sample sizes vary for expert opinion gathering but are typically 3-12. Higher than this, and you get a very little gain in the robustness of findings (i.e. no new knowledge), but for low numbers of experts, it becomes difficult to get a representative sample. In identifying experts, a suggested process is to: “follow a formal nomination and selection process; ensure diversity of opinion, credibility and result reliability; minimise redundancy of information; and have a balanced and broad spectrum of viewpoints, expertise, technical points of view and organisational representation” (Krueger et al, 2012).

Cyber-Security in Smart Grid: Fact vs Hype – Dr Zoya Pourmirza

cyber, Energy Systems, smartgrid,

About the Author

dsc01229

Dr Zoya Pourmirza, is a postdoctoral research associate at Newcastle University within the School of Electrical and Electronic Engineering. She was awarded her PhD in The Information and Communication Technology (ICT) Architecture in the Smart Grid from University of Manchester. Her research expertise includes Smart Grids ICT networks, cyber-security, communication energy efficiency, and data compression.

Zoya carries out a wide range of research for CESI in the area of cyber-security on energy systems.

Contact:- Zoya.Pourmirza@newcastle.ac.uk

Introduction

The Smart Grid has three main characteristics which are, to some degree, antagonistic. These characteristics are the provision of good power quality, energy cost reduction and improvement in the reliability of the grid. The need to ensure that they can be accomplished together demands much richer Information and Communications Technology (ICT) networks than the current systems available. The addition of the ICT to the legacy grid raises concerns among various stakeholders such as consumers, utilities, and regulators. Cyber security is emerging as an important and critical element of modern energy systems that could jeopardise the availability and reliability of energy systems if compromised.

Risks and vulnerabilities associated to cyber-security in Smart Grids

The modern cyber-physical energy system that couples the communication networks to the legacy grid introduces more cyber risks and vulnerabilities, which can seriously affect the energy systems in terms of operation and reliability. While dependability against relatively rare physical failures can be argued on a “one out of n” basis, cyber-attacks have the potential to damage “n out of n” systems simultaneously, because security vulnerabilities can be exploited in parallel. This is particularly worrying as the physical dimension of energy systems is prone to cause a cascading effect in case of targeted failures.

Some of the critical vulnerabilities of smart energy system have been identified as:

  • Physical vulnerabilities
  • Platform vulnerabilities
  • Policy vulnerabilities
  • Interdependency vulnerabilities
  • Information and Communication Technology (ICT) system vulnerabilities.

Impacts:

The full extent of these impacts is, however, hard to grasp due to their highly complex and interdisciplinary nature, and the interdependencies between energy systems and a fast-changing ICT landscape. Any attack on the ICT of the energy system will, therefore, have negative impacts of varying severity on energy system operation. There is a wide range of possible attacks against the ICT of the energy systems. According to the US National Institute of Standards and Technology (NIST), those targeting the availability, integrity, and confidentiality of the ICT are of the highest importance. Such attacks are usually undertaken to:

  • Mislead the operation and control of the utility provider
  • Manipulate market and misguide the billing systems
  • Compete with other utility service providers
  • Disturb the balance between demand and supply
  • Carry out terrorist activities to damage local and national power infrastructure
  • Convey distrust between people and government
  • Increase or decrease the cost of energy consumption and energy distribution

 Are we more vulnerable than before?

A number of cyber experts have already expressed their concerns about the digitization of legacy grids. While some say the energy industry is ignoring the risks associated with the smart energy system, some go further and argue that the security of the country is at stake, due to the possibility of cyber-attacks on digitized energy systems. This trend is transforming cyber security complications from a problem to a hype. However, the truth lies somewhere between these two extremes. Currently, there seems to be a lack of evidence in the form of particular incidents suggesting smart technologies can be held exclusively responsible for compromising the operation of energy systems. Traditional energy systems are already exposed to a range of cyber threats. Although smart technologies are not yet embedded in a large scale in energy systems, their deployment can increase the risk of vulnerabilities and introduce new ones. This is more likely to be associated with increased connectivity between various assets and with the internet.

Over past few years, a number of incidents have been reported in which legacy energy systems have been compromised due to their partial dependence on smart technologies. Based on these recent incidents it is envisaged that similar types of attacks could increase in numbers as smart technology deployment increases introducing additional access points (cyber and physical) for infiltrators. Potential attacks in equipment could lead to financial loss and disruption of services for buildings and households and possible safety concerns both for the owners/occupants and the broader network depending on the power ratings and role of the asset attacked.

In order to address the diverse cyber-security issues related to the smart energy systems, there is an increasing need for experts in multidisciplinary fields to work jointly in the identification and treatment of these. Newcastle University has recently launched a multi-disciplinary team comprising cyber security, and smart grid experts co-funded by EPSRC and working with other stakeholders from industry and academia offering a powerful collaboration of electrical power systems, ICT architecture and cyber-systems expertise to tackle this pressing problem.

Saving on Domestic Energy Bills – How to compare domestic energy bill tariffs

Domestic, energy bills

 

As part of a series of posts focussing on consumer energy consumption reduction in the UK, this post highlights some advice in understanding a domestic consumer energy bill based on advice from Ofgem,  the government regulator for gas and electricity markets in Great Britain

ofgem_icons

Saving on Domestic Energy Bills by finding a cheaper supplier 

In the UK, the energy regulator Ofgem, has encouraged domestic energy consumers to reduce their annual energy bills by switching to alternative tariffs with their supplier or switching supplier altogether. Tariffs are the prices that Energy Companies change per unit of energy used.

To help the consumer navigate the complex world of energy tariffs, Ofgem regulated that Energy Supply Companies must provide a “Tariff Comparison Rate” for all the energy tariffs that they bring to market.

Tariff Comparison Rate1

The Tariff Comparison Rate  (TCR) is there to act as a price comparison guide for all energy customers. It breaks down the cost of an energy tariff by combining everything from the unit rates, standing charges, VAT and discounts into one amount and then dividing it by the average annual consumption figures published by Ofgem – the energy regulator.

The idea is to allow all tariffs to be compared against one another, by giving you a single price per kilowatt hour for the energy you use.

This is how it is calculated:- 

  • multiple the unit cost by ofgem’s average energy consumption figures 
  • Add a year’s standing charge (this is a daily charge and can vary significantly between tariffs)
  • Take away any discounts that might be applicable
  • Add the VAT
  • Finally, divide this figure by Ofgem’s average consumption figures
  • This gives you the TCR in pence per kWh (kilowatt hour)

Common Energy Tariffs2

There are two main types of energy tariff – fixed or variable rate. Dual fuel and online options are an opportunity for further cost saving.

  • Fixed– this is a tariff with a fixed end date
  • Variable– the prices of this tariff aren’t fixed, so your supplier can change them as long as they give you advance notice.
  • Duel Fuel– based on a supply of energy for both your gas and electricity from one supplier – sometimes more economical
  • Online– specifically operated online, meaning paperless bills etc. so may be slightly cheaper than other tariffs

Does this save energy?

Switching supplier or finding a cheaper tariff will not reduce energy consumption – it will only reduce the amount the consumer pays for their energy. Look out for our next blog which provides some easy ideas on how to save energy within the home.

1https://www.ovoenergy.com/blog/ovo-news/tariff-comparison-rates.html

2http://www.goenergyshopping.co.uk/energy-tariffs-and-deals/common-tariffs