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Optimization of energy planning for growth and sustainable development has become very important in the context of climate change mitigation imperatives in developing countries. Existing models do not capture developing country realities adequately. The purpose of this paper is to conceptualizes a framework for energy strategy optimization of the Indian energy sector, which can be applied in all emerging economies.

Hierarchical multi‐objective policy optimization methodology adopts a policy‐centric approach and groups the energy strategies into multi‐level portfolios based on convergence of objectives appropriate to each level. This arrangement facilitates application of the optimality principle of dynamic programming. Synchronised optimization of strategies with respect to the common objectives at each level results in optimal policy portfolios.

The reductionist policy‐centric approach to complex energy economy modelling, facilitated by the dynamic programming methodology, is most suitable for policy optimization in the context of a developing country. Barriers to project implementation and cost risks are critical features of developing countries which are captured in the framework in the form of a comprehensive risk barrier index. Genetic algorithms are suitable for optimization of the first level objectives, while the efficiency approach, using restricted weight stochastic data envelopment analysis, is appropriate for higher levels of the objective hierarchy.

The methodology has been designed for application to the energy sector planning for India's 12th Five Year Plan for which the objectives of faster growth, better inclusion, energy security and sustainability have been identified. The conceptual framework combines, within the policy domain, the bottom‐up and top‐down processes to form a hybrid modelling approach yielding optimal outcomes, transparent and convincing to the policy makers. The research findings have substantial implications for transition management to a sustainable energy framework.

The methodology is general in nature and can be employed in all sectors of the economy. It is especially suited to policy design in developing countries with the ground realities factored into the model as project barriers. It offers modularity and flexibility in implementation and can accommodate all the key strategies from diverse sectors along with multiple objectives in the policy optimization process. It enables adoption of an evidence‐based and transparent approach to policy making. The research findings have substantial value for transition management to a sustainable energy framework in developing countries.

In the context of the negotiations for apportionment of emission reduction post‐Kyoto regime, issues of equity and fairness have emerged. The purpose of this paper is to generate a model for equitable emission reduction apportionment.

The mathematical model has been designed utilizing mitigation capacity (based on gross domestic product (GDP)) and cumulative excess emissions as the criteria for apportionment. Quantitative results have been arrived at, using cumulative γ and parabolic mitigation emission reduction trajectories to demonstrate the impact on stakeholders.

The apportionment outcomes are independent of the specific trajectory fine‐tuned in the feasibility region. Since the apportionment takes into account entitlements and the mitigation capacity, Africa and India have negligible reduction targets in tune with the development goals in these economies. Substantial reduction commitments would fall on the USA and the EU countries. China gets a moderate target due to higher emissions and GDP.

The approach is in consonance with the principle of common but differentiated responsibility enunciated in the UNFCCC and the Kyoto Protocol. The method can easily incorporate emissions trading. The issue of population as a driving factor of emissions has been partially accounted for by considering the entire national GDP as an emission reduction responsibility factor, without considering population based GDP entitlements.

The generalized framework can be extended to situations involving responsibility apportionment in public policies dealing with externalities. The framework is original and will be useful to policymakers and other stakeholders dealing with climate change, as well as researchers looking at externalities of a global or national dimension.