Warren Schenler

Electric Sector Simulation: A Tradeoff Analysis of Shandong Province’s Electric Service Options

Three key aspects in transitioning to a sustainable energy future are technology development, deployment and use. This part of the China Energy Technology Program uses electric industry simulation models to explore the deployment and use of numerous electricity supply and end-use options, which could provide Shandong Province with cheaper and cleaner electric service. To do this the Electric Sector Simulation (ESS) team uses the Scenario-Based Multi-Attribute Tradeoff Analysis approach developed at MIT’s Laboratory for Energy and the Environment, and employed in previous Alliance for Global Sustainability projects (Schenler, et. al, 2000 and 2002). With the assistance of the analysis team, the tradeoff analysis approach allows stakeholders to look at a broad range of options and uncertainties and compare the performance of the resulting strategies. This “inclusive”-and therefore extensive-analytic approach was developed to help multi-stakeholder groups jointly evaluate combinations of options that meet their collective interests.

Strategic electricity sector assessment methodology under sustainability conditions: a Swiss case study on the costs of CO2 emissions reductions

Growing concerns about social and environmental sustainability have led to increased interest in planning for the electricity utility sector because of its large resource requirements and production of emissions. A number of conflicting trends combine to make the electricity sector a major concern, even though a clear definition of how to measure progress toward sustainability is lacking. These trends include imminent competition in the electricity industry, global climate change, expected long-term growth in population and pressure to balance living standards (including per capital energy consumption). In order to approach this global problem on a regional level, a project has been established to develop planning methods for electrical power systems related to sustainability called SESAMS (Strategic Electricity Sector Assessment Methodology under Sustainability Conditions), under the Alliance for Global Sustainability formed by the Massachusetts Institute of Technology (MIT), the Swiss Federal Institutes of Technology (ETHZ and EPFL), and the University of Tokyo (UT). SESAMS 97 has brought together multi-attribute, multi-scenario electricity system planning, life-cycle assessment, and multi-criteria decision analysis to create an integrated methodology that has been demonstrated using a case study based on the Swiss electricity system. This case study has simulated system dispatch of the Swiss electricity system for 1296 scenarios over a study period from 1996 to 2025. The results for these scenarios include a wide range of direct and indirect sustainability measures, with conclusions that have focused primarily on cost and CO2 emissions. The pairwise scenario trade-off analysis facilitates searching the strategy option space by identifying the best and most robust options. Decision-makers benefit by being able to focus trade-off discussions on the dominant set of best choices for each trade-off pair, rather than covering the entire decision space.

Comparison and Integration of CETP Tasks

The CETP project has approached the problem of Shandong’s electricity future in a way that has integrated the use of many different and complex methodologies within specific tasks and task interactions. These integration activities were conducted on different levels with varying degrees of implementation, and have included the following:

An Integrated Decision-Support Tool for Sustainable Energy Supply

Within the China Energy Technology Program (CETP), sponsored by ABB in conjunction with the Alliance for Global Sustainability (AGS), PSI, together with American (MIT), numerous Chinese, Japanese (Tokyo University) and Swiss (ETHZ and EPFL) partners, investigated how the future electricity supply in China could be made more sustainable. Most detailed analyses were carried out for the Shandong province though a wide spectrum of results was obtained for whole China. Representatives of major Chinese stakeholders participated in the program.

Strategic electricity sector assessment methodology under sustainability conditions: a Swiss case study on CO 2 emissions, competition and stranded costs

Designing and implementing a sustainable energy sector will be a key element of defining and creating a sustainable society. In the electricity industry, the question of strategic planning for sustainability seems to conflict with the shorter time horizons associated with market forces as deregulation replaces vertical integration. In order to address such questions, a project called SESAMS (Strategic Electricity Sector Assessment Methodology under Sustainability) has been established to develop electricity sector planning methods related to sustainability. This effort is part of the Alliance for Global Sustainability (AGS) formed by the Massachusetts Institute of Technology (MIT), the Swiss Federal Institutes of Technology (ETHZ and EPFL), and the University of Tokyo (UT). The initial phase of SESAMS in 1997 created a methodology integrating multi-scenario simulation, life-cycle analysis and multi-criteria decision analysis. This 1998 case study has expanded the methodology to study the transitional effects of deregulation associated with the issues of stranded cost. This analysis has studied the inclusion of different classes of stranded assets, different recovery periods, and recovery of costs on a fixed vs. variable (per kWh) basis. On a societal basis, stranded costs are a zero-sum transfer payment, but the ownership patterns of stranded assets mean that compensation for stranded assets will produce relative winners and losers. These winners and losers shift according to the stranded cost and other options present in different scenarios. The results of the stranded cost analysis are integrated with updated multi-criteria trade-off analysis and life-cycle analysis results, based on expanded system boundaries.