As the global energy landscape evolves with urgent calls for sustainable and equitable development, the role of energy modelling tools in shaping transition strategies has become undeniably crucial. These sophisticated analytical frameworks allow policymakers to simulate future energy scenarios, optimizing for affordability, sustainability, and resilience. However, prevailing models have predominantly been tailored to high-income countries with robust data infrastructures and regulatory frameworks, leaving significant gaps when applied to the complex realities of low- and middle-income countries (LMICs). The intricacies of these contexts demand a fresh approach—one that innovates both methodologically and contextually—to ensure that models genuinely support inclusive and effective energy transitions.
Low- and middle-income countries face an exceptional combination of challenges. The pressure to meet rapidly increasing energy demands clashes with financial constraints, infrastructural deficits, and diverse socio-political dynamics. Conventional modelling paradigms often inadequately capture these multifaceted challenges due to limited data availability, fewer analytical capacities, and the heightened uncertainties inherent in LMIC environments. Consequently, reliance on standard models risks providing misleading policy advice that is misaligned with on-the-ground realities, potentially exacerbating vulnerabilities and marginalizing critical stakeholder interests.
At the heart of this innovation imperative lie three pivotal features of modelling practice: the choice of paradigm, the modelling process itself, and the pluralism of expertise engaged. These components shape the capacity of tools to cope with LMIC-specific contexts, embody system dynamics effectively, and incorporate interconnected systemic feedback loops. By recalibrating these features, models can transition from abstract, one-size-fits-all blueprints to dynamic, participatory instruments that guide adaptive, context-sensitive planning.
The paradigm shift recommended centers on embracing complexity and uncertainty. In LMICs, energy systems are characterized by rapidly evolving infrastructures, informal markets, and diverse demand patterns influenced by socioeconomic disparities. Traditional deterministic models that produce single-point forecasts ignore such fluctuations, thereby limiting strategic foresight. Incorporating stochastic methods, scenario analysis, and adaptive modelling frameworks allows for more nuanced representations of potential futures. This approach acknowledges not only the probabilistic nature of outcomes but also the contingency of decisions on unfolding political and climatic events.
Enhanced modelling processes entail engaging a broader spectrum of stakeholders, from local energy practitioners and community representatives to interdisciplinary experts. In LMICs, rich experiential knowledge resides outside official data channels, embedded in lived realities. Integrating this tacit knowledge into model construction and validation processes deepens the authenticity and relevance of outputs. Participatory modelling enhances local ownership of energy strategies, fosters trust, and facilitates contextual adjustments that pure technical analyses might miss.
A critical avenue for advancement lies in system pluralism—recognizing energy systems as interlaced with water, agriculture, health, and economic sectors. LMICs often experience pronounced interdependencies where fluctuations in one domain cascade unpredictably across others. Conventional siloed modelling fails to anticipate these interactions, causing underestimation of risks and missed optimization opportunities. Multiplex modelling frameworks that simulate cross-sectoral dynamics enable more robust policy designs capable of addressing the multifactorial realities of sustainable development.
However, the aspiration for sophisticated, context-attuned modeling must grapple with ground realities of limited data infrastructure. Many LMICs suffer from sporadic energy usage records, insufficient monitoring equipment, and fragmented statistical systems. To combat these gaps, the research advocates for innovations in data sourcing, including crowdsourced data, remote sensing, and the deployment of low-cost sensors. Additionally, creating open-access platforms that democratize data availability can empower local analysts and institutions, catalyzing a bottom-up improvement in model fidelity.
Addressing the acute shortage of technical expertise is equally paramount. Many LMICs lack institutional capacity for sustainable energy modelling boosted by advanced computational techniques. Strengthening local analytical capabilities through targeted training, international partnerships, and knowledge exchange networks fosters an ecosystem where locally relevant modelling thrives. Such efforts not only boost methodological quality but also uphold principles of equity and sovereignty in energy planning.
Beyond technical dimensions, innovations must reflect the deeply political nature of energy transitions. Modelling exercises that overlook governance structures, power relations, and socio-economic equity risk producing technocratic, top-down policies ill-equipped to navigate real-world contestations. Integrative models increasingly incorporate political economy perspectives to reveal the implications of different pathways on marginalized groups, resilience against geopolitical shocks, and alignment with developmental aspirations.
One especially promising frontier involves integrating model outputs into iterative decision-making processes. Unlike static tools that yield fixed recommendations, adaptive models can be recalibrated continuously as new data emerges and conditions evolve. This feature is vital in LMICs, where volatility and uncertainty are norms rather than exceptions. Embedding feedback loops between real-world outcomes and model updates enables a learning-oriented governance framework that remains responsive to emerging challenges and opportunities.
The research highlights that today’s energy modelling paradigms must transcend technical innovation and become embedded within supportive institutional environments. Without political commitment, sustained funding, and cooperative governance structures, even the most advanced models risk obsolescence or marginalization. Therefore, a holistic approach is imperative—one that synchronizes methodological innovation with capacity building, stakeholder empowerment, and governance reforms.
A corollary of this systemic perspective recognizes the importance of building extensive, collaborative networks of practice. Modellers, policymakers, academics, civil society, and private sector actors must coalesce in knowledge-sharing platforms that transcend national borders. These networks facilitate the dissemination of best practices, harmonize modelling standards, and catalyze innovation diffusion tailored to diverse LMIC settings. Such alliances strengthen global solidarity in energy transition efforts and uphold commitments to climate justice.
The dynamic nature of LMIC energy landscapes also demands models capable of integrating emerging technologies and disruptive innovations, such as decentralized renewables, energy storage solutions, and digitized energy management systems. These technologies dramatically alter demand-supply paradigms and introduce novel regulatory challenges. Future-ready models must simulate their cascading effects on grid stability, affordability, and equity to guide forward-looking policies that harness technological leapfrogging potential.
Moreover, incorporating climate resilience into energy modelling frameworks is indispensable. LMICs disproportionately suffer from climate-related shocks, ranging from extreme weather events to shifting resource availability. Models that evaluate vulnerabilities and adaptive capacities within energy systems inform resilience-building strategies, ensuring that transitions do not merely address emissions reductions but also safeguard communities against climate-induced disruptions.
Critically, the evolution toward inclusive energy modelling in LMICs calls for rethinking the very metrics of success. Beyond traditional cost-optimization, models must integrate indicators capturing social welfare, environmental justice, local employment, and energy access equity. Such multidimensional evaluation frameworks encourage holistic policies aligned with the Sustainable Development Goals, reflecting the broader aspirations of many LMIC societies.
The challenges elucidated in this body of work resonate with wider debates in global energy governance, underscoring the ethical dimensions of knowledge production and policy advice. Modelling is not a neutral exercise; it inherently embodies assumptions, value judgements, and interests. Heightened reflexivity within the modelling community regarding these aspects fosters transparency, accountability, and legitimacy—qualities essential for broad-based acceptance and effective implementation.
In conclusion, the path toward context-sensitive, resilient, and participatory energy modelling in low- and middle-income countries demands a concerted, multipronged innovation agenda. By reimagining paradigms, embracing pluralistic knowledge systems, enhancing data environments, and strengthening institutional capacities, this approach holds promise for catalyzing just and transformative energy transitions. As the global community confronts intertwined energy, climate, and development crises, tailoring analytical tools to diverse realities emerges as a critical prerequisite for sustainable futures worldwide.
Subject of Research:
Energy modelling paradigms and their application challenges in low- and middle-income countries, emphasizing methodological innovation and context-specific adaptation for sustainable energy transitions.
Article Title:
Addressing context-specific energy modelling risks and dynamics in low- and middle-income countries.
Article References:
Daly, M., Pye, S., Trotter, P. et al. Addressing context-specific energy modelling risks and dynamics in low- and middle-income countries. Nat Energy (2026). https://doi.org/10.1038/s41560-025-01962-y
Image Credits:
AI Generated
DOI:
https://doi.org/10.1038/s41560-025-01962-y
Tags: addressing vulnerabilities in energy policyaffordability and sustainability in energy systemsanalytical frameworks for energy modelingenergy modeling challenges in developing nationsenergy policy and stakeholder engagementinclusive energy planning practicesinnovative energy modeling methodslow- and middle-income countries energy demandsovercoming data limitations in energy modelingresilience in energy infrastructuresocio-political dynamics in energy transitionsustainable energy transition strategies
