Near-optimal energy planning strategies with modeling to generate alternatives to flexibly explore practically desirable options

Cost-optimizing energy planning models are widespread in supporting energy transition planning decisions. Nonetheless, finding a “cost-optimal” planning strategy provides only a false sense of certainty. Stakeholders may prefer other economically comparable alternatives due to unaccounted-for features. Multi-objective or robust optimization, among others, can efficiently explore alternatives whose desired secondary features are well defined. “Modeling to generate alternatives” (MGA) explores alternatives systematically, including alternatives whose features, such as social viability, are hard to model, albeit key to practical implementation. Computational and interpretation barriers hindered past MGA usage and integration with other methods, but recent developments enable going beyond such barriers. We synthesize such developments and provide practical recommendations for applying MGA in five levels of increasing benefit. Even the simplest levels, requiring little computational effort, can substantially improve the quality of energy planning analyses. At the highest level of integration, MGA can facilitate identifying consensus strategies, accelerating the energy transition.