Daniel Olsen

TL;DR: This work describes and implements a methodology to construct detailed temporal and spatial representations of demand response resources and to incorporate those resources into power system models and demonstrates how the combination of these three analyses can be used to assess economic value of the realizable potential ofDemand response for ancillary services.

TL;DR: In this paper, the Weighted sum bisection method is used to determine the lowest emission tax rate that can reduce the anticipated emissions of the power sector below a prescribed, regulatorily defined target.

TL;DR: The U.S. Department of Energy (DOEIA) Demand Response and Energy Storage Integration Study as mentioned in this paper is a multinational laboratory effort to assess the potential value of demand response (DR) and energy storage to electricity systems with different penetration levels of variable renewable resources and to improve our understanding of associated markets and institutions.

TL;DR: This paper proposes a centralized model to co-optimize the transformer loss-of-life with the benefits for EVs’ owners on charging/discharging management and shows the benefit of the centralized strategy in maintaining the grid assets, while modestly reducing consumers’ arbitrage benefits.

TL;DR: This paper presents four frameworks for incentivizing energy hub equipment investments for low-carbon operation targets, and compares the cost of less efficient institutional frameworks with the most efficient approach, i.e., cooperation between builder and operator with constraints on emissions.