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Energy Futures Lab

Energy Futures Lab Overview

Energy Futures Lab (EFL)

ACPET’s Energy Futures Lab is an in-house advanced modelling and analytics lab to strengthen the centre’s work across verticals and to spearhead an informed debate at various levels.

Outcomes

Student Resources
  • Evidence-based policy through scenario modelling and simulations.
  • Improved integration of renewables and grid resilience.
  • Enhanced institutional capacity for data-driven decision-making.
  • Creation of new generation ACPET REBOOST Tools, Products
  • Development of innovative modelling systems
  • Creation of a legacy knowledge system

Outputs

  • Co-creation of decision support systems and dashboards
  • Renewable transition models (LEAP, TIMES, IESS)
  • Behavioural nudge simulations using AI/ML
  • Integrated energy-economy forecasting tools
  • Grid intermittency and rare-event stress-test models
  • Knowledge and methodological advancement
  • Future-proofing modelling
Student Resources

Activities

Student Resources
  • Collaborative modelling with vertical leads
  • Scenario-based simulations and least-cost pathways
  • Organizing regular workshops, tutorials and boot camps
  • Publication of knowledge products as an evidence bae for policymaking
  • Host an Energy Modelling Forum: a collaborative platform to exchange ideas
  • Facilitate knowledge partnerships with academia and international institutions
  • Co-create an open-access energy data repository

Indicators

  • Number of models produced and adopted
  • Number of policy inputs and recommendations
  • Uptake of modelling tools by government and industry
Student Resources

Objective of an Energy Futures Lab

These labs are essential for advancing the global transition to sustainable energy systems, combining cutting-edge technology with practical applications to address the world's energy challenges.

Data-Driven Decision Making

By analyzing vast amounts of data from energy systems, these labs provide insights that help optimize operations, reduce costs, and improve reliability. In the Indian context, this application can pertain to running cost optimization simulations, with multiple demand-supply scenarios considering technology constraints, to arrive at an optimal least cost pathway. As a part of this it will also run scenarios of social nudges to understand its impact on net zero pathways which thereafter will also affect the energy and electricity demand projections.

Renewable Energy Integration

Labs work on integrating renewable energy sources like solar and wind into existing power grids, addressing challenges related to intermittency and storage. In India, the lab can therefore work on simulation of price trajectories and its optimization by integrating grid intermittency (including storage).

Grid Modernization

Research in these labs focuses on developing smart grid technologies that enhance the efficiency and resilience of power distribution systems. This will pertain to conducting high end AI, Machine Learning based Grid Security and Power System Modelling for a more integrated and smart energy system.

Energy Efficiency

Labs analyze energy consumption patterns and develop strategies to improve energy efficiency in industrial, commercial, and residential sectors. As a part of this, the energetics lab will conduct scenario based forecasting, projections, cost optimization models to understand how energy efficiency strategies can impact energy consumption in industrial, commercial, residential sectors in future for different sets of endogenous steady state economic growth and developmental pathways.

Policy Development

Insights from energy analytics research help shape energy policies that promote sustainability and security. Based on the above simulation/s, the lab will recommend policy action/s sensitive to ecology, environment, culture, growth and wellbeing.

Focus Areas

ACPET’s energy analytics lab will therefore have the following four focus areas:

Classrooms
Renewable Energy Transitions, Decarbonisation and Integration Models People centric renewable energy transition, decarbonisation and integration models will facilitate private sector decarbonisation strategies, climate risks adoption, inform adaptation and optimisation approaches. For example, IEA Decarbonisation Model, IIASA System Model
Classrooms
Data Driven Behavioural Nudge Effects of Energy Transition Data-driven decision support models driving “Behavioural And Nudge Effects” of energy transition – For example, Modelling Mission LiFE into IESS V4.0; Working Model of The Nudge Institute
Classrooms
Energy Policy and Forecasting Models Futuristic energy policy models facilitate policy framing based on the simulations of the Energy Systems. For example, Shell and BP Model based Integrated Policy Framing
Classrooms
Grid Transitions, RE Intermittency Simulation & Stress Tests Grid Transitions, RE Intermittency Simulation & Stress Tests facilitate AI/ ML based cyber security models for grid security and future infra planning. For example, working model of rare events of IIT Kanpur, Working Model of Organisation of Rare Diseases, University of Chicago, University of Maryland

Working Model of ACPET’s Energy Futures (Analytics) Lab

The lab will function like a “Hub and Spoke” model and be set up as a hub of different analytical futuristic system based integrated models and at the same time, while building the hub it will collaborate with a range of institutions as a spoke of knowledge networks to the core hub which will be built at ACPET.

It is therefore essential to understand how with the core hub of the Energy Analytics Lab, certain models will be built and why they will be built to understand what research question and perspective:

The principal research question that this model hub will look onto is – a) What are the people centric renewable energy transition and decarbonisation pathways for the future of India and the developing world? In order to explore that question, this hub will build up energy economy based cost optimisation models which will project how for different external growth and degrowth scenarios of the economy, the sectoral demand of energy across the sectors of the economy will pan out to be till 2070. Additionally, the hub will build up system based macro models to indicate how for different decarbonisation and renewable energy transition scenarios, the possible impacts on economy, jobs, environment, biodiversity, revenue collection, fiscal deficit of the country will pan out to be. Possible scenarios will be created till 2070 and projections for each scenario will be estimated by usage of LEAP, Times, IESS, Python and Other Macro Models. Effects of the people centric renewable energy transition and decarbonisation trends on development indicators, sustainability indicators will also be mapped out and projected through these scenario based models.
The principal research question that this model hub will explore will be – “What are the social nudges that impact people centric energy transition and how do those nudges impact the final adoption of any people centric renewable energy choice?”. To explore the question, this hub will create agent based behaviour and network effect models to understand how a particular nudge impact the adoption behaviour of agents (or people) towards a certain renewable energy choice in a people centric way. Further, scenarios using AI and Machine Learning Models will be used to understand how such nudges impact the adoption behaviour for a range of behavioural patterns amongst the actors (or agents or people), tactics followed by the actors (or agents or people). This will help in shaping up policy prescriptions and prioritisation of social nudging actions towards attainment of the goal of adopting a people centric energy transition.
This model hub will explore and understand the principal research question of – “How the energy demand of sectors of an economy change when an economy moves towards a people centric energy transition path and how the economy change when the energy demand of sectors of an economy move towards a people centric energy transition path?”. The model hub will indicate how the economy impacts the people centric energy demand and how the people centric energy demand impacts the economy in a feedback loop method by using MARKAL-CGE Integrated Macro Models.
This model hub will delve into the principal question of – “How does rare events like cyber attacks, grid collapse, lack of grid integration impact the people centric energy transition?”. In order to explore this research question, the hub will create rare event probabilistic models to estimate the probabilities of future projections of such rare event and to what extent the occurrence of such events impact a people centric renewable energy based grid transition. Moreover, the models will also estimate the future projections of financial risks associated with the occurrence of such events and hence will enable of creating a mechanism of projecting insurance estimates, coverage of financial losses to redeem such financial risks for smooth people centric grid transitions.