DEVELOPMENT OF ENERGY MODELING AND DECISION SUPPORT FRAMEWORK FOR SUSTAINABLE ELECTRICITY SYSTEM OF PAKISTAN

Abstract

Pakistan’s energy and power sector underperformed over the decades for its failure to adequately plan, formulate and implement the policies. As a result, the country which is believed to have abundant energy resources is coping significant electricity shortfall since 2006. This situation is confronting governments for many years to address these crises. However, in the absence of effective energy planning, various conformist planning and policy initiative could not deliver and decrease the reliance on imported fuels for power generation. The imported fossil fuels are huge burden for the national exchequer, on one hand, and are also unsustainable as they adversely add to climate change on the other hand. These circumstances warrant an energy security concern since the obscure future with growing population and economy pose a serious challenge to meet unprecedented electricity demand. It is, therefore, inevitable that Pakistan undertakes sustainable energy planning thereby acknowledging indigenous renewable energy resources and focusing energy efficiency and conservation. This research develops an energy modeling and decision support framework for the judicious energy policy development by incorporating sustainability criteria for the sustainable electricity system of Pakistan. This planning framework addresses two key shortcomings of unaided energy modeling for energy planning. First, the models typically provide a set of scenario alternatives which are based on the modeling parameters and not on the sustainability criteria as well as without appropriate decision support, and secondly, the energy policy makers in the developing countries little understand the inherent complexities of the energy models. As such, in this study following energy modeling, using Long-range Energy Alternatives Planning System (LEAP), sustainability assessment of modeling results is undertaken using Expert Choice Comparion® decision tool. The Expert Choice Comparion® decision tool is based on the Analytical Hierarchy Process (AHP) methodology of Multi-Criteria Decision Making (MCDM) methods. This research covers the study period of 20152050. Pakistan’s LEAP model results for the electricity demand forecast 1706.1 TWh of electricity requirements in 2050 which is 19 folds higher than the base year demand at an annual average growth rate of 8.35%. The four supply side scenarios alternatives namely; Reference (REF), Renewable Energy Technologies (RET), Clean Coal Maximum (CCM) and Energy Efficiency and Conservation (EEC) are developed in the LEAP model while considering the resource potential, techno-economic parameters, and CO2 emissions. All four scenarios with various fuel and technology mix, meet the electricity demand during the study period. In terms of CO2 emissions, RET and CCM scenarios have emissions lower than EEC scenario. However, in the REF scenario, CO2 emissions are the highest of all the scenarios. Further, the EEC scenario has the lowest Net Present Value (NPV) requirement followed by REF, RET and CCM scenarios at all the discount rates (4%, 6%, 8%, 10%) considered in the study. The AHP methodology of this study comprises of four main-criteria which include technological, environmental, socio-political and economic criteria and seventeen subcriteria for the judicious evaluation of the four scenario alternatives of the study. The questionnaire feedbacks under AHP methodology, using a pairwise comparison, determined weightages of the sustainability criteria which were further used towards the ranking of the scenario alternatives. The AHP based sustainability assessment ranks EEC scenario as the most preferred electricity generation scenario followed by REF, RET and CCM scenarios. However, CO2 emissions under EEC scenario are higher than the RET and CCM scenarios, as such, it is recommended that Pakistan should adopt energy efficiency and conservation as the focus of the energy policy alongside increasing the renewable energy share for the electricity generation. The dynamic and performance sensitivity analysis of the AHP decision support framework establishes the robustness of this study. Overall, the results of the developed planning framework are elaborative of the contemplation that how energy policy makers, experts, and stakeholders view future of energy system in Pakistan for next 35 years. The main achievement of this study is the development of a sustainable energy planning framework and providing a future insight pertaining the alternative energy pathways that Pakistan could follow for a sustainable electricity system. This study also proposes a set of policy recommendations that could contribute towards a sustainable energy system and thus sustainable development in Pakistan.