Exploring the challenges in developing a multi-criteria assessment for smart local energy systems

Several countries worldwide, including the United Kingdom, are investing in and introducing policies to foster the development and deployment of Smart Local Energy Systems. Smart Local Energy Systems are complex and socio-technical, with a wide range of stakeholders and multiple social, technical, environmental and economic aims. It is, therefore, essential to develop a standardised assessment tool to monitor the implementation of these systems and their social, technological, environmental and economic benefits and impacts. This paper presents work related to developing such a multi-criteria assessment tool, focusing on exploring and identifying the challenges of applying multi-criteria assessment to the development and deployment of Smart Local Energy Systems. The research involved semi-structured interviews with relevant expert stakeholders concerning six core assessment themes, corresponding sub-themes, and associated criteria/metrics. The results provide insights into the challenges of applying multi-criteria assessment to Smart Local Energy Systems and highlight the complex nature of these systems. Furthermore, stakeholder burnout (due to too many stakeholder engagement activities), data collection issues, and the broad definition and/or limited scope of assessment criteria were identified as the principal challenges faced in developing such an assessment tool, potentially affecting the reliability of its outputs

Developing the framework for multi-criteria assessment of smart local energy systems

In response to the climate emergency, energy landscapes are rapidly shifting to cleaner, decentralised smart local energy systems (SLESs). SLES will facilitate connection of transport, heat and power through flexible energy supply, demand and storage options supported by digital technology. SLESs are expected to contribute to tackling the energy trilemma (cost, security and sustainability), but there is also scope for them to offer many co-benefits aligned with the United Nations (UN) Sustainable Development Goals (SDGs). These benefits may drive for ongoing political and financial investment in SLES; therefore, there’s a need to indicate how a SLES is performing over time relative to each of them. Currently, there is no standardised approach to evaluate SLES and most of the existing techno-socio-economic tools have limited scope to assess the complex multiple performance indices, scenarios and stakeholders. The Innovate UK-funded EnergyREV research consortium is developing a multi-criteria assessment tool (MCA) for SLES. This paper describes the first step in this process – developing a simplified and standardised framework for assessing the performance of the system and the realization of benefits. It explores existing protocols and stakeholder opinion to identify 50 potential factors that are important in monitoring the system performance. These are clustered into 10 key themes to create a taxonomy for SLES performance that are aligned with relevant UN SDGs to track wider co-benefits. The resulting MCA tool will be instrumental to project stakeholders in providing evidence to support performance claims and identifying potential benefits beyond targeted key performance indicators

Smart Local Energy Systems (SLES): A framework for exploring transition, context, and impacts

Energy systems globally are becoming increasingly decentralised; experiencing new types of loads; incorporating digital or “smart” technologies; and seeing the demand side engage in new ways. These changes impact on the management and regulation of future energy systems and question how they will support a socially equitable, acceptable, net-zero transition. This paper couples a meta-narrative literature review with expert interviews to explore how socio-technical regimes associated with centralised systems of provision (i.e. the prevailing paradigm in many countries around the world) differ to those of smart local energy systems (SLES). Findings show how SLES regimes incorporate niche technologies, business models and governance structures to enable new forms of localised operation and optimisation (e.g. automated network management), smarter decision making and planning, by new actors (e.g. local authorities, other local stakeholders), and engaging users in new ways. Through this they are expected to deliver on a wide range of outcomes, both within the SLES boundary and to the wider system. However, there may be trade-offs between outcomes due to pressures for change originating from competing actors (e.g. landscape vs. incumbents in the regime); understanding the mapping between different outcomes, SLES elements and their interconnections will be key to unlocking wider benefits

Weighting Key Performance Indicators of Smart Local Energy Systems: A Discrete Choice Experiment

The development of Smart Local Energy Systems (SLES) in the UK is part of the energy transition tackling the energy trilemma and contributing to achieving the Sustainable Development Goals (SDGs). Project developers and other stakeholders need to independently assess the performance of these systems: how well they meet their aims to successfully deliver multiple benefits and objectives. This article describes a step undertaken by the EnergyREV Research Consortium in developing a standardised Multi-Criteria Assessment (MCA) tool—specifically a discrete choice experiment (DCE) to determine the weighting of key performance indicators (KPIs). The MCA tool will use a technology-agnostic framework to assess SLES projects, track system performance and monitor benefit realisation. In order to understand the perceived relative importance of KPIs across different stakeholders, seven DCEs were conducted via online surveys (using 1000minds software). The main survey (with 234 responses) revealed that Environment was considered the most important criterion, with a mean weight of 21.6%. This was followed by People and Living (18.9%), Technical Performance (17.8%) and Data Management (14.7%), with Business and Economics and Governance ranked the least important (13.9% and 13.1%, respectively). These results are applied as weightings to calculate overall scores in the EnergyREV MCA-SLES tool