A Greek Green Deal: building energy democracy and fighting energy poverty

While implementing the New Green Deal, the European Union is faced with major energy challenges and dilemmas. Energy poverty is an issue of critical importance affecting many Europeans. Since Greece has experienced a prolonged period of crises, the strengthening of energy democracy and the fight against energy poverty must be among the top national priorities. Collective energy actions can pave the way towards the uptake of renewable energy, enabling and incentivizing consumers to become prosumers. This study first outlines the main theoretical perspectives on the politics of energy and proposes a new approach to understand renewable energy. Then it describes the EU energy policy and the transition to a climate-neutral economy. It briefly explains the concept of energy communities before focusing on the case of Greece. The study examines the rise of the country’s energy communities, including the Agrinio and Minoan communities. It also explains the measures taken in Greece during the last decade to tackle energy poverty by offering incentives for energy savings. Moreover, the study describes the national energy and climate plan by examining the case of Tilos. Finally, the study summarises the main findings and offer some policy recommendations

A Machine Learning-Based Framework for Clustering Residential Electricity Load Profiles to Enhance Demand Response Programs

Load shapes derived from smart meter data are frequently employed to analyze daily energy consumption patterns, particularly in the context of applications like Demand Response (DR). Nevertheless, one of the most important challenges to this endeavor lies in identifying the most suitable consumer clusters with similar consumption behaviors. In this paper, we present a novel machine learning based framework in order to achieve optimal load profiling through a real case study, utilizing data from almost 5000 households in London. Four widely used clustering algorithms are applied specifically K-means, K-medoids, Hierarchical Agglomerative Clustering and Density-based Spatial Clustering. An empirical analysis as well as multiple evaluation metrics are leveraged to assess those algorithms. Following that, we redefine the problem as a probabilistic classification one, with the classifier emulating the behavior of a clustering algorithm,leveraging Explainable AI (xAI) to enhance the interpretability of our solution. According to the clustering algorithm analysis the optimal number of clusters for this case is seven. Despite that, our methodology shows that two of the clusters, almost 10\% of the dataset, exhibit significant internal dissimilarity and thus it splits them even further to create nine clusters in total. The scalability and versatility of our solution makes it an ideal choice for power utility companies aiming to segment their users for creating more targeted Demand Response programs.Comment: 29 pages, 19 figure

Managing stakeholder knowledge for the evaluation of innovation systems in the face of climate change

Purpose – The aim of this paper is to frame the stakeholder-driven system mapping approach in the context of climate change, building on stakeholder knowledge of system boundaries, key elements and interactions within a system and to introduce a decision support tool for managing and visualising this knowledge into insightful system maps with policy implications. Design/methodology/approach – This methodological framework is based on the concepts of market maps. The process of eliciting and visualising expert knowledge is facilitated by means of a reference implementation in MATLAB, which allows for designing technological innovation systems models in either a structured or a visual format. Findings – System mapping can contribute to evaluating systems for climate change by capturing knowledge of expert groups with regard to the dynamic interrelations between climate policy strategies and other system components, which may promote or hinder the desired transition to low carbon societies. Research limitations/implications – This study explores how system mapping addresses gaps in analytical tools and complements the systems of innovation framework. Knowledge elicitation, however, must be facilitated and build upon a structured framework such as technological innovation systems. Practical implications – This approach can provide policymakers with significant insight into the strengths and weaknesses of current policy frameworks based on tacit knowledge embedded in stakeholders. Social implications – The developed methodological framework aims to include societal groups in the climate policy-making process by acknowledging stakeholders’ role in developing transition pathways. The system map codifies stakeholder input in a structured and transparent manner. Originality/value – This is the first study that clearly defines the system mapping approach in the frame of climate policy and introduces the first dedicated software option for researchers and decision makers to use for implementing this methodology

Integrated policy assessment and optimisation over multiple sustainable development goals in Eastern Africa

Heavy reliance on traditional biomass for household energy in eastern Africa has significant negative health and environmental impacts. The African context for energy access is rather different from historical experiences elsewhere as challenges in achieving energy access have coincided with major climate ambitions. Policies focusing on household energy needs in eastern Africa contribute to at least three sustainable development goals (SDGs): climate action, good health, and improved energy access. This study uses an integrated assessment model to simulate the impact of land policies and technology subsidies, as well as the interaction of both, on greenhouse gas (GHG) emissions, exposure to air pollution and energy access in eastern Africa under a range of socioeconomic pathways. We find that land policies focusing on increasing the sustainable output of biomass resources can reduce GHG emissions in the region by about 10%, but also slightly delay progress in health and energy access goals. An optimised portfolio of energy technology subsidies consistent with a global Green Climate Funds budget of 30-35 billion dollar, can yield another 10% savings in GHG emissions, while decreasing mortality related to air pollution by 20%, and improving energy access by up to 15%. After 2030, both land and technology policies become less effective, and more dependent on the overall development path of the region. The analysis shows that support for biogas technology should be prioritised in both the short and long term, while financing liquefied petroleum gas and ethanol technologies also has synergetic climate, health and energy access benefits. Instead, financing PV technologies is mostly relevant for improving energy access, while charcoal and to a lesser extend fuelwood technologies are relevant for curbing GHG emissions if their finance is linked to land policies. We suggest that integrated policy analysis is needed in the African context for simultaneously reaching progress in multiple SDGs.The authors thank Francesco Dalla Longa for his comments, and Brennan Bowman and Sebastien Huclin for their help with regard to data and methodology. This research is supported by the European Union's Horizon 2020 research and innovation program under Grant Agreements No. 642260 (TRANSrisk project) and No. 820846 (Paris Reinforce), and by the Spanish Ministry of Economy and Competitiveness MINECO through BC3 Maria de Maeztu excellence accreditation MDM-2017-0714. Dirk-Jan van de Ven and Jon Sampedro acknowledge financial support from the Ministry of the Economy and Competitiveness of Spain (ECO2015-68023). Jon Sampedro also acknowledges financial support from the Basque Government (PRE_2018_2_0076). Sha Yu was supported by the Global Technology Strategy Project (GTSP). The views and opinions expressed in this paper are those of the authors alone

Coupling circularity performance and climate action : from disciplinary silos to transdisciplinary modelling science

Technological breakthroughs and policy measures targeting energy efficiency and clean energy alone will not suffice to deliver Paris Agreement-compliant greenhouse gas emissions trajectories in the next decades. Strong cases have recently been made for acknowledging the decarbonisation potential lying in transforming linear economic models into closed-loop industrial ecosystems and in shifting lifestyle patterns towards this direction. This perspective highlights the research capacity needed to inform on the role and potential of the circular economy for climate change mitigation and to enhance the scientific capabilities to quantitatively explore their synergies and trade-offs. This begins with establishing conceptual and methodological bridges amongst the relevant and currently fragmented research communities, thereby allowing an interdisciplinary integration and assessment of circularity, decarbonisation, and sustainable development. Following similar calls for science in support of climate action, a transdisciplinary scientific agenda is needed to co-create the goals and scientific processes underpinning the transition pathways towards a circular, net-zero economy with representatives from policy, industry, and civil society. Here, it is argued that such integration of disciplines, methods, and communities can then lead to new and/or structurally enhanced quantitative systems models that better represent critical industrial value chains, consumption patterns, and mitigation technologies. This will be a crucial advancement towards assessing the material implications of, and the contribution of enhanced circularity performance to, mitigation pathways that are compatible with the temperature goals of the Paris Agreement and the transition to a circular economy

From Integrated to Integrative: Delivering on the Paris Agreement

In pursuit of the drastic transformations necessary for effectively responding to climate change, the Paris Agreement stresses the need to design and implement sustainable, robust, and socially acceptable policy pathways in a globally coordinated and cooperative manner. For decades, the scientific community has been carrying out quantitative modelling exercises in support of climate policy design, primarily by means of energy systems and integrated assessment modelling frameworks. Here, we describe in detail the context of a hitherto ineffective scientific contribution to policymaking, highlight the available means to formulate a new paradigm that overcomes existing and emerging challenges, and ultimately call for change. In particular, we argue that individual modelling exercises alone widen the gap between formal representation and real-life context in which decisions are taken, and investigate major criticisms to which formalised modelling frameworks are subject. We essentially highlight the importance of employing diverse modelling ensembles, placing the human factor at the core of all modelling processes, and enhancing the robustness of model-driven policy prescriptions through decision support systems. These altogether compose a truly integrative approach to supporting the design of effective climate policy and sustainable transitions and, therefore, strengthen the modelling–policymaking interface

The Green Versus Green Trap and a Way Forward

Massive deployment of renewables is considered as a decisive step in most countries’ climate efforts. However, at the local scale, it is also perceived by many as a threat to their rich and diverse natural environment. With this perspective, we argue that this green versus green pseudo-dilemma highlights how crucial a broad societal buy-in is. New, transparent, participatory processes and mechanisms that are oriented toward social licensing can now be employed. A novel, integrative research agenda must orbit around co-creation to enable and promote resource co-management and co-ownership where possible, with increased consensus

An Advanced IoT-based System for Intelligent Energy Management in Buildings

The energy sector is closely interconnected with the building sector and integrated Information and Communication Technologies (ICT) solutions for effective energy management supporting decision-making at building, district and city level are key fundamental elements for making a city Smart. The available systems are designed and intended exclusively for a predefined number of cases and systems without allowing for expansion and interoperability with other applications that is partially due to the lack of semantics. This paper presents an advanced Internet of Things (IoT) based system for intelligent energy management in buildings. A semantic framework is introduced aiming at the unified and standardised modelling of the entities that constitute the building environment. Suitable rules are formed, aiming at the intelligent energy management and the general modus operandi of Smart Building. In this context, an IoT-based system was implemented, which enhances the interactivity of the buildings’ energy management systems. The results from its pilot application are presented and discussed. The proposed system extends existing approaches and integrates cross-domain data, such as the building’s data (e.g., energy management systems), energy production, energy prices, weather data and end-users’ behaviour, in order to produce daily and weekly action plans for the energy end-users with actionable personalised information

Cooperation or Localization in European Capacity Markets? A Coalitional Game over Graph Approach

Capacity markets, as a means to address the capacity adequacy issue, are constantly becoming an important part of the European internal electricity market. The debate focuses on how the capacity markets will be smoothly integrated in one Pan-European power market, without resulting in multiple national fragmentations and consequently in economic efficiency losses. Cross-border participation and regional cooperation are considered as two sine qua non conditions in this respect. The present paper provides a coalitional game theoretical approach aiming to facilitate the cooperation of neighboring countries, when it comes to the security of electricity supply and the necessity of establishing a capacity market. Such an approach can support respective decisions about capacity markets cooperation as well as stress-test the benefits considering all cooperation possibilities

Renewable energy policy dialogue towards 2030

In view of the 2030 energy and climate objectives of the European Union, there is a need to evaluate the different options to shape the future framework for renewable energy sources (RES) policies and targets. The Special Issue focuses in seven papers on the following dimension of this future framework: (i) interactions between support for RES in the electricity sector and other climate and energy instruments in the European Union, (ii) challenges related to renewable energy technologies that have achieved a certain level of maturity, (iii) assessment of renewable and energy efficiency policies on natural gas markets and supply security, (iv) contribution of increasing district heating based on renewables to the renewable target achievements of Central and Eastern European, (v) how to support the successful achievement of renewable energy targets in the short and medium term and in a time horizon up to 2030, and how to share the efforts required among individual countries or groups of European Member States, (vi) influence of the rapidly increasing shares of variable renewable on the price on electricity markets as well as flexibility requirements in the electricity system, (vii) principal design features and context factors which increase or reduce the effectiveness and efficiency of RES-E auctions