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Review Version of 11 March 2014
Rani Yesudas and Roger Clarke **
© Rani Yesudas and Xamax Consultancy Pty Ltd, 2014
Available under an AEShareNet licence or a Creative Commons licence.
This document is at http://www.rogerclarke.com/EC/SG-CRA.html
Energy efficiency has been the primary motivation for the introduction of smart meters. But current smart metering projects are facing barriers to adoption from consumers, arising from the failure of project sponsors to understand consumers and their requirements. Consumers view smart meters with suspicion, perceiving them to be energy suppliers' efforts to maximise their profits at the expense of consumer costs, choice, health and privacy. For emergent systems like automated metering infrastructure (AMI) to avoid battling to convince consumers of their benefits, it is essential to have user-centric analysis performed before expensive infrastructures are designed and deployed. Various categories of consumers will have their own particular perspectives, and different expectations about how the system should help them to appropriately manage their energy usage. Hence it is essential to segment energy consumers and identify the requirements for each group. In this paper we look at a number of user-centric methods. We then analyse the effectiveness of combining Contextual Design (CD), focus groups and problem extraction to provide insights into energy consumer needs. Based on the analysis we outline a functional specification for a smart meter that would satisfy the energy requirements for a segment of electricity consumer with medical needs.
Smart meter roll-outs started with promoters claiming that they are a critical step in the transition of the traditional grid to a modern grid [1],[2] . But the current situation shows that there are significant unresolved negative reactions to smart meters, principally based on consumer concerns [3].
Consumers' concerns include both perceived and actual risks. They worry that the detailed data would disclose the private activities that are occurring within a dwelling [4]. They also worry that the radiation from the communication devices in smart meters gives rise to health hazards. With the imposition of Time-Of-Use (TOU) tariffs they worry about having to paying higher bills for unavoidable use during the peaks [5], [6].
In addition, reports appear in the mass media of how the communication technology used for smart meters is not secure and that malicious hackers could break into the system and cause harm [5]. Many consumers have come to believe that a smart meter that records and transmits detailed data benefits only the energy supplier. Consumers have to change their energy choices, pay for operation and maintenance of the new system and yet be worried about their privacy and security. It is not clear to consumers, especially domestic customers, how they can benefit from a smart metering system.
Most of these issues point to the lack of appropriate requirement engineering practices. Requirement engineering is performed with varying breadth of vision. In most cases business requirements and provider requirements are identified but little importance is placed on end-user requirements. Where the system involves even a small degree of user interaction or user impact, the developed system is vulnerable to criticism and resistance from consumers. Critical infrastructure such as the power grid has a great deal of impact on consumers, and hence the requirements and the design need to reflect user requirements in order to avoid the system being pushed to the verge of desertion.
User requirements may be established from predefined notions and using purely analytical methods. That approach lacks the necessary deep inspection of user needs and use contexts. Failure to incorporate user involvement during requirement analysis invites consumer dissatisfaction and rejection of the system. Involvement of users in system design can, on the other hand lead to a robust system.
There are various approaches to involve users. They can be invited to take active roles in design activities, or alternatively they can be asked to provide information or their activities can be subjected to observation [7],[8],[9]. These techniques ensure a clearer understanding of needs, improve levels of acceptance and effective use from the user, avoid unnecessary expenses of building a system with features that are not useful to the user, and avoid the expensive step of retro-fitting features to any already-implemented system.
There are many user-centric analysis methods available. Contextual Design (CD) is one such method. It encompasses a broad class of techniques including open-ended interview, ethnography, and prototyping to build an in-depth understanding of the users of the system [10], [11].
CD places emphasis on the context of work and also places more importance on the end-user in comparison with other stakeholders. CD defines the end-user as those stakeholders who may depend on the output of the system, prepare input for a system, and decide on the need for a system or acceptance of the system in practice [10],[12]. This focus makes it a good choice for gathering the consumer requirements for Smart Metering solutions.
The contributions of the research presented in this paper are:
1. Evaluation of the effectiveness of the contextual design method for gathering the requirements from the stakeholders of the smart grid and smart metering solution, particularly consumers.
2. Application of contextual design, focus group and problem extraction to provide insights into energy consumer needs.
3. Problem extraction of the issues the consumer will face due to the conflicts with business requirements.
4. An outline of a functional specification for smart meters that would satisfy both the business requirements and the energy requirements (demonstrated for a segment of electricity consumer with medical needs).
Smart metering solutions were the much-hyped solution for the management of the growing demands for electricity. Since 2008, many countries have spent millions on the mandatory installation of smart meters and related technologies in residential premises as part of the transformation of the current electrical grid into a smart grid [13],[4]. After smart meter roll-outs started, consumer concerns have been so significant that projects have been suspended. Some news articles even hint that high-value projects may even be abandoned due to heavy criticism from consumers [14],[15],[16].
For example, it has been reported that there is high chance that Germany could reject smart meters due to a small but vocal minority of energy users who are opposed to any storage of information on households and uncomfortable that utilities could have access to data on how and when they use electricity [14]. Similarly, another report states that the state government in Victoria, Australia may suspend the installation of electricity smart meters while it reviews the embattled $2 billion project [16]. It is said that they are currently reviewing for potential improvements and whether it is worth dumping the scheme for an alternative amid concerns that consumer benefits have been overstated.
There have also been a number of consumer review reports [17],[18]. One that was prepared by the Centre for Sustainable Energy for the UK smart metering project mentions that the most concerning aspects for consumers are the rollout costs and the unfair share of the benefits that are acquired by suppliers and others in the system. The proposed remedy was measures to understand consumer concerns followed by the development of interventions to address them [17]. Although the report purported to be oriented toward consumers, the remedies suggested are from the perspective of the solution providers rather than consumers. Interventions and measures have only been considered when consumer concerns have arisen arise after the system was deployed. There is no clear suggestion of a need to elicit and analyse consumer requirements before design and deployment.
Smart meters can be programmed to record the time of use across varying intervals, and to transmit data to the utility at varying intervals, and at varying levels of aggregation. In the past, the data available to the utility was delayed, and aggregated over a month or quarter. More timely transmission of much more detailed usage is justified on the basis that this will enable better network management, and better usage management, through time-of-use (TOU) tariff and remote disconnect/connect services [19]. Through TOU it is expected that peak electricity consumption could be reduced and deferred thereby avoiding the need to construct new power plants [19],[4].
It is also suggested that real-time data from smart meters could be used for preventive measures such as shutting down supply to some areas in order to to avoiding black-outs and brown-outs [19,][5]. But such measures are currently in place in some countries without the use of smart meter. When the load requirement is higher than the capacity of the generator, selective load shedding method is used to avoid damage to the system. All these calculations are done high up in the grid rather than at consumer level. Different sections of cities are chosen for different time frames, in order to achieve load shedding for durations required[20].
There are also reports that suggest that the customer's use cases in smart metering systems are merely limited to: logging into the energy management system, configuring and requesting details of energy usage [21].
This indicates that the system has been designed with very little focus on the consumer. There is no clear evidence that the system provides the consumer with smarter choices to meet their energy needs. Various questions arise from the above information:
1. Does massive collection of fine-grained data make a system smart?
2. To identify peak demand, is it necessary to have a device installed at the consumer end? Can identification of peak period be achieved higher up in the transmission network? Are there ways in which a consumer could still be informed of the varying tariff rates without a smart meter?
3. Why would a consumer use a smart meter? How is the system "smart", if the consumer functionalities are merely limited to normal online management system?
4. If energy efficiency and reduced electricity bills are the motives, where is the evidence to show that a consumer can achieve them at all, or in a convenient manner, and in a manner that has minimal impact on their lifestyle?
5. Is the system smart enough to differentiate between the needs of different segments of consumers and meet their demands?
As a result of vocal opposition by consumer advocacy groups [22],[23],[24], government agencies are undertaking to make privacy policies and security measures more robust for AMI systems[25],[26]. But still the system will be lacking in end-user friendly aspects . Complex projects like those involved in smart grids, are likely to impact upon people and the environment, hence it will be beneficial and cost effective to understand and analyse the needs of all stakeholder before committing to the design, construction and deployment of expensive technology.
Selection of requirements engineering (RE) techniques for a project is a challenge. Some of the factors that need to be considered include problem domain, diversity of stakeholders, criticality, time and cost involved [27].
Introspection is the method usually applied by the analyst to understand the system properties. Introspection involves experts and stakeholder proxies. It relies on thinking, reasoning, and examining of the expert's thoughts [28]. Though this method is helpful there is a high chance that the experts will not be providing designers with appropriate requirements because many of them are too far removed from consumers themselves.
Critical infrastructure such as an electricity grid has many, heterogeneous stakeholders. For the success of a project, satisfactory levels of payback need to exist for all the stakeholders involved. Hence techniques should be chosen to elicit requirements from all stakeholders. To ensure user involvement and appropriate understanding of their needs, user-centric approaches need to be applied during the requirements elicitation phase [29].
There are various forms of user-centric approach. Most of the methods are closely linked and they all include an explanation as to why to involve users and how to involve them [29]. Four groups of methods are usefully distinguished: user-centred design, participatory design, ethnography and contextual design (CD) [30]. User-centred design gives emphasis to usability whereas participatory design gives emphasis to democratic participation. Social aspects of work are important in ethnography, whereas in CD the emphasis is on the context of work [30].
In user-centred design, the design team will have direct contact with potential users rather than intermediaries. Intended users are invited to utilize simulations and prototypes in order to gain insights into their objectives and patterns of work. Their performance and reactions are observed and recoded for analysis. In participatory design, users are invited to participate in the analysis of requirements. Then they are asked to plan appropriate socio-technical structures to support both individual and organisational needs. Ethnographic design is concerned with human activities and culture with a focus on the social aspects of human cooperation. It takes place in natural settings and is focused on the point-of view of the user [29], [30].
CD was developed by Hugh Beyer and Karen Holtzblatt [10],[12]. It is a synthetic method that systematically combines conversation, observation and analysis. It is focused on the context in which users work, and studies work processes in order to produce descriptions of them. Analysts watch users and discuss their work with them, while embedded in their environment. The method thereby achieves direct interaction with the various categories of user [10],[11]. Based on these characteristics, CD is an ideal choice for the requirement analysis of smart meter consumers.
CD consists of the following steps: Contextual Inquiry, Interpretation, Data Consolidation, Visioning, Storyboarding, User Environment Design, and Prototyping [10],[12] . These steps are detailed below:
1) Contextual inquiry
Contextual inquiries focus on the work that the user needs to accomplish. Field interviews are conducted with users, in combination with observation of their work. This ensures that activities of the people using the system are captured and analysed rather than just the self-reported practice and official policies [11]. This step is key is gaining insight into the needs of user segments with different energy requirements.
2) Interpretation sessions
In this section, analysts conduct discussions in which the events of the interview are retold, key points are captured, and models representing the user's work practice are drawn. This detailed debriefing allows the team to build a common understanding of the various users, and capture all the data relevant for system design [10],[12].
3) Consolidation
The data from individual users is consolidated to show a larger picture of user requirements. The affinity notes from all users are brought together into an affinity diagram. Issues are then detailed to reflect users' concerns and needs [10],[12].
4) Visioning
The consolidated data is reviewed and analysis is done on how the system will streamline and transform the work people do. This vision represents the big picture of what the system could do [10],[12].
5) Storyboarding.
The new designs for work tasks are sketched out and a storyboard is created which includes manual practices, business rules, and automation assumptions [10],[12].
6) Paper prototypes
This ensures the basic system function and structure work for different user segments[10],[12].
The research reported in the remainder of this paper comprised a proxy study
of consumer perspectives on the functionalities that smart metering solutions
need to support. The data and material analysed in this research are not from
an operational smart grid nor from interviews with energy users, but from
scientific publications, smart metering system specifications, and research
articles, including [1],[31],[ 32], [34 to 43].
The main research questions in this study are:
1. What are the energy-related needs of a user? Are there specific energy requirements for different consumer segments?
2. What techniques need to be applied and what preparations need to be undertaken, in order to effectively conduct contextual inquiry into users' needs of smart metering systems?
3. What further techniques are helpful in converting the information gathered from the users and user groups into general and specific requirements?
4. How can the user requirements be converted into smart meter functionalities?
As energy consumers are the focus of our study, we will analysis how the smart meter's business goals could affect the consumer's energy-related activities and how consumer resistance could be overcome by having particular functionalities included in the smart meter. As different consumer segments have different expectations [31],[32]; a consumer segment with medical needs have been chosen for the discussion. In a field application of this method,CD, focus groups and problem extraction would be combined to provide detailed insight into the consumer needs.
The key business requirements of smart meters systems are to accurately measure usage; identify leaks and thefts; provide measures to flatten the demand curves and production-cost; provide real-time detection of events such as power failure, and to identify options for quicker response. To fulfil these requirements, a smart meter records usage data at relatively short intervals and communicates this data to the utility at frequencies required by the provider. Apart from consumption data, the meter also sends alerts and events to the back-end. It may also provide the supplier with remote access to manage meter operations [13],[1],[2].
At this stage, CD requires the formulation of potential interview questions. These need to stimulate the extraction of assumptions and concerns, and help identify user activities that need to be studied in depth. These ideas are only intended to guide the interview. They should not put the participants in a passive role like in focus group interviews where they wait to be questioned. Table I demonstrates a sample list of such ideas.
A contextual inquiry requires a balance between interviewing and ethnographic observation. Sessions should be very flexible rather than predictable. The user should perform the tasks naturally without being prompted. The user should be interviewed in a semi-structured way. The participants can be briefed about the focus of interest and they should be observed as they perform a task and they can be questioned while they work in their own environments [12].
Table II provides a template to carry out contextual inquiry on consumers with medical needs. Information gathered from such sessions will provide insight into how a household with medical needs will carry out its energy consuming activities in the presence of a smart meter. This enables the analyst to visualise the extent to which alternative design choices would enable them to make smart energy choices.
The selection of appropriate participants in contextual inquiry may be challenging .The key to a contextual inquiry is that participants need to educate the analyst about their tasks. Participants may wait to be prompted to perform a task and may even not provide all information for their choice of actions. Focus groups can be used to support the contextual inquiry method. Initially, focus groups discussions can be conducted to explore people's knowledge and views through open-ended questions [33]. This will also provide more information on the collective needs of a particular segment of user. User representatives can also participate to give more information. From the responses and willingness of the participants to perform detailed tasks, ideal candidates can be chosen for the contextual inquiry sessions.
From the information collected, a sequence model and affinity notes can be
generated for developing the profiles. Follow-up interviews could also be
conducted with the participants if further information is required [12]. Table
III is a consolidation of the smart metering systems business goal and the user
goals of the consumer with medical needs. Because a contextual inquiry has not
been conducted in this study, the user goals are drawn from a systematic review
of information that has been gathered from scientific publications, and
research articles, including [1],[31],[ 32], [34 to 43].
Analysing the conflicts among user goals and business goals, we can extract user issues, which may be variously real and merely perceived. Table IV provides an indicative representation of the user issues for a consumer with medical needs.
A detailed problem extraction process is helpful to the development of an understanding of the issues that end users will face. Structured Report Formats is one method of problem extraction and it is helpful in gathering data about the difficulties that arise from the problem, the context in which they occur and the assumed causes of the problem [41]. Table V provides an example of a detailed problem extraction for the consumer with medical needs.
Visioning and storyboarding of consolidated data helps us to identify how the business requirements can be reconciled with the user requirements, in order to satisfy both sets. Through storyboards the analyst can discuss a sequence of actions and solutions for a specific task [12]. Table VI provides a sample storyboard relating to a consumer with medical requirement.
Using a paper prototype or a set of mocked-up screens, the analyst can assist users to visualise possible system functionality that meets the user's expectations and needs. This will result in the design of an appropriately user-centric system [12]. Table VII shows an outline for smart meter functionalities that are beneficial for the consumer segment with medical needs. The needs have been categorised into specific and general needs.
Important, high-value infrastructure projects in the smart grid arena are at risk of consumer rejection, and investment failure. The research reported on in this paper has highlighted ways in which the needs of consumers can be elicited, in order to ensure that designs can address the needs of consumers as well as other stakeholders, resulting in a much lower level of consumer opposition.
The article selected a specific method, Contextual Design, and demonstrated its application to a particular user segment. Regardless of the research method chosen to elicit user requirements, the aim should be to understand users' needs and issues. Instead of precisely following the steps mentioned in one method, the analyst can adapt methods to the particular context, by combining a range of techniques. In this paper we have looked into the identification of the user needs of a smart metering system using a combination of contextual design, focus group and problem extraction. Analysts should be aware of range techniques so that they can flexibly combine them to obtain deep insight into user needs. Both open-ended and close-ended interviews form an integral part of user sessions, as does observation of users working in their own environment. In some circumstances, questionnaires may be a useful supplementary technique.
We intend extending this work, in order to identify which requirements engineering techniques can be combined to provide the best elicitation for all smart metering stakeholders.
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Rani Yesudas is a software engineer with experience in the smart meters industry, and a PhD student in the Research School of Computer Science at the Australian National University.
Roger Clarke is Principal of Xamax Consultancy Pty Ltd, Canberra. He is also a Visiting Professor in the Cyberspace Law & Policy Centre at the University of N.S.W., and a Visiting Professor in the Research School of Computer Science at the Australian National University.
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