CS13: Energy Transition

This work introduces demand‑based adjustments of heating based on actual room usage. Previous measures primarily targeted predefined schedules and general optimisations to reduce heating energy consumption. LoRaWAN and sensors provide real‑time room usage and environmental data, which are fused with thermal histories to optimise energy consumption and maintain comfort via existing Energy Management Systems (EMS). A key innovation of this project lies in the use of artificial intelligence (AI) to enable demand‑based adjustments based on actual room usage. The approach targets intermittently used buildings across a rural German municipality- such as sports halls, kindergartens, town halls, and meeting rooms - that are often heated when not in use. CO₂ is used as a presence proxy to avoid personal data collection. Optimisations will be integrated into algorithms to create intelligent municipal buildings and transform them to significantly reduce energy consumption and CO₂ emissions.
A preparatory phase deployed >500 sensors across 100+ buildings, established LoRaWAN coverage, and enabled central visualisation in an EMS and open urban data platform, allowing initial operational adjustments. In the current roll‑out, demand‑based, automated control is implemented using the above pipeline. Early adjustments indicate energy savings of 10–15% by switching from time schedules to presence‑based control; with potentials up to ~30% reported in cooperation projects. We evaluate (i) runtime reductions of heating equipment, (ii) preheating timing accuracy, (iii) comfort compliance rates, (iv) effects of false‑positive/negative occupancy detection on energy and comfort, and (v) integration cost vs savings. The approach leverages local ecosystems and infrastructure under an open‑source, vendor‑neutral architecture, minimising the need for costly improvements to building insulation or replacement of existing energy technologies.

The global transition to sustainable energy systems has accelerated the rise of renewable energy communities, where individuals or entities share energy infrastructures. These communities foster local energy production, democratic governance, and social equity while promoting energy security, resilience and climate-change mitigation. This paper applies club theory as an analytical framework, offering insights into voluntary participation, congestion management, exclusion mechanisms, and the determination of optimal membership size in energy communities. By framing energy infrastructures as club goods, the study demonstrates how efficiency, equity, and long-term viability can be achieved through well-designed governance structures. We assume that club members are homogeneous who possess identical preferences and resources, and that club managers compete to attract members. In such a competitive game, each club manager makes optimal choices that maximize the utility of the representative club member. 
We examine two settings. To derive key economic insights regarding the important role that membership size plays in the optimal configuration with multiple club facilities, we first assume that the renewable resource is not subject to exogenous climate shocks. Later, this simple setting is extended to account for the fact that renewable resources (e.g., solar energy) are intermittent. We focus on solar energy production. We introduce uncertainty and demonstrate how the club manager chooses one of two competing technologies (single source or hybrid) ex-ante and the economic arrangement that takes place ex-post. Under uncertainty, we assume that there are two possible states of nature, sunny and cloudy. The results of the analysis produce crucial insights about the complex nature of energy clubs as these entities provide multiple sharing facilities in stochastic settings. 

Energy is essential for powering economic activities and providing a healthier and more prosperous future for all. In recent years, the challenge of environmental sustainability has attracted considerable attention, and policymakers have targeted the energy sector's revolution to promote green energy consumption as an alternative source and so accelerate the energy transition process (Singh et al., 2019). With knowledge of the existing energy fuel sources in use and producing significant pollution to the global environment, countries are argued to deliberately innovate and shift from traditional energy to green energy resources. Such endeavors are yet to be satisfactorily accommodated the satisfactory by many states. The ongoing implementation of technology transformation from the old energy system into a more efficient one is appreciated; however, the share of green energy in the overall energy mix is still minimal (Sun et al., 2022). It is necessary to institute a revolutionary transition from traditional energy to green energy resources for the global energy system (Yu and Guo, 2023). Relevant energy reforms to signal impact at the policy level are tested and have resulted in mixed outcomes experienced across countries. Heterogeneity in policy supporting environment and infrastructures provides fundamental differences in energy transition across countries' domains. In this paper, policy reforms to accelerate energy transition are explored and tested for their effectiveness.

Global energy-transition investment reached USD 2.4 trillion in 2024, yet 90% remains concentrated in advanced economies and China, leaving developing countries critically underfunded relative to 1.5°C pathways. Targeted energy investment is therefore essential to address financial gaps and balance energy trilemma. Against this backdrop, this study asks: (i) How do different forms of public investment in energy, including total, renewable, and non-renewable, affect the energy trilemma in developing countries, and to what extent do financial development and economic complexity influence this relationship?; and (ii) how do financial development and economic complexity moderate the relationship between total public investment in energy and the energy trilemma in developing countries?. To address these questions, this study examines the impact of public investment in energy (total, renewable, and non-renewable) on the energy trilemma in 49 developing countries for 2000–2023. We have constructed the energy trilemma index using energy security, energy equity, and environmental sustainability components of energy systems provided by the World Energy Council. This study employs Driscoll–Kraay standard errors to address cross-sectional dependence, instrumental variable estimation with fixed effect two-step generalized method of moments to tackle endogeneity issues, and panel quantile to deal with heteroscedasticity. The findings reveal a positive effect of public investment on the energy trilemma. The analysis further explores the moderating roles of financial development and economic complexity, showing that stronger financial systems and robust economic foundations enhance the effectiveness of public energy investment in addressing the energy trilemma. Regression results also highlight that the positive effects of public investment on the energy trilemma are more pronounced at higher quantiles. Overall, the study underscores the need for tailored policy interventions, emphasizing the importance of reinforcing economic and institutional frameworks to effectively direct public investment in energy toward achieving a balanced energy trilemma in developing countries.

This study investigates the links between CO₂ emissions (TCO2E) and energy consumption variables: Oil, Natural Gas, Coal, Renewable Energy, and GDP being an economic factor, deploying an Autoregressive Distributed Lag (ARDL) framework for analysis in Nigeria taking data from 1990 to 2021. The study seeks to answer the question in a different perspective from a previous research conducted ' Analysis of the relationship between carbon dioxide emissions, energy supply from fossil fuel, energy consumption and gdp: Nigerian case' ; "What is the relationship and the causal direction between carbon dioxide emissions and energy and economic growth?" and "What are the appropriate energy policies to attain the goal of greenhouse gas reduction in an economy mainly dependent on fossil fuel production and consumption?" inline with the National Determine Contribution and also the mandate of the Nigerian Upstream Petroleum Regulatory Commission in decarbonization.
The ARDL model indicates a strong cointegration which was derived from the bound test.
The Error Correction Model (ECM) shows notable short-term results, revealing that natural gas and oil consumption exert considerable positive impacts on CO₂ emissions, however oil has more positive significance than oil. Conversely, coal usage, renewable energy use, and GDP demonstrate negligible influence. lagged error correction term is insignificant, indicating minimal feedback modifications in the short term. Pairwise Granger causality tests reveal no significant direct causality between CO₂ emissions and certain energy consumption factors, prompting inquiries regarding possible omitted variable bias or indirect pathways, which prompted for an Impulse Response Function been done to further investigate the shocks of the dependent variable on the independent variable, no noticeable causality noticed especially with oil and natural gas variables.
The impulse response functions indicates oil and natural gas consumption significantly affect emissions in the short term and cumulatively, while disturbances in coal, renewable energy, and GDP provide negligible effects.