Essentially, Indonesia has used several tools for energy planning process. The most common tools in Indonesia are engineering-based models, also known as bottom-up models. Both have been used to provide long term optimal energy composition targets such as in documents of National Energy Management, National Energy Policy, yearly Indonesia Energy Outlook, National Energy Master Plan and Regional Energy Master Plan. Unfortunately, mostly none of the targets can be achieved for example total geothermal power plant capacity was expected by 2005 – 2025 National Energy Management to be 1,158 MW in 2013 but the realization was only 568 MW (PLN, 2014). Bottom up models have ignored broader economic linkages from all market players.

Without the linkages and its feedback, supporting policy such as fiscal incentives to induce required investment and its impact on the economy cannot be evaluated. Such analysis requires another different type of modelling which is top down models. CGE models, as example of top down models, have been frequently used by Indonesian economists in particular to analyse impact of rising energy prices because structure of the model has integrated economic sectors. However, top-down models are unsuited for long-term energy planning because energy technology has been aggregated and therefore it is not as detailed as in bottom-up models. Top-down models also use a substitution elasticity to capture technological change but the elasticity may inappropriate if there is any structural change such as obligation to end oil-based power plant operation. On the bottom up model, the elasticity is equivalent to accurate and detail technology data. 

This research then attempts to provide new approach model by integrating bottom up and top down models for Indonesia case. The integrated model, called hybrid energy model, could resolve each weakness of the models by using complementarity feature to combine smooth functional form in top down model and stepwise functional form in bottom up model. The Indonesia hybrid model then will be used to (i) determine optimal feed in tariff needed to achieve national energy policy target; (ii) investigate other fiscal incentive feasibility to obtain optimal energy subsidy; and (iii) re-evaluate whether KEN’s target is already optimal in broader economic perspectives. The analysis will also be enriched by dynamic systems and agent based modelling to improve the understanding of the complex system of renewable energy development in Indonesia.

Funding: Indonesia Endowment Fund for Education (LPDP) – Ministry of Finance
Advisors:  Dr Anthony Halog, Dr Rabindra Nepal

Project members

Muhammad Al Irsyad

Muhammad Al Irsyad

PhD Candidate