In addition to the national decarbonization strategy mentioned in NZAP, a growing number of states and Independent System Operator (ISO) are pledging to reduce emission deeply as well. To explore what technologies, policies, market designs and planning strategies will increase the likelihood that state and ISO can decarbonize their electricity supply; we have conducted a project assessing the role of New Jersey (NJ) in the deep decarbonization of PJM gird, which is the regional transmission organization responsible for electricity supply of 13 states in upper east coast of US. In this project, we strive to understand understanding how to maximize benefits and minimize costs associated with the deployment of 3500 MW of offshore wind (OSW) electricity generating capacity to be installed off the NJ coast. In the project, we first identify the optimal backbone transmission requirement to accommodate NJ’s projected 3500 MW of OSW, and then identify interregional backbone transmission requirements to accommodate 15000 MW of OSW projected for PJM. In the second step, we use the planned OSW resources, together with transmission configurations identified in step 1, as inputs to simulations of the evolution of the supply resource mix (including capacity retirements and additions), to assessments of wholesale market prices and revenues expected to accrue to OSW resources, and to emission reductions estimates. We use GenX, an electricity capacity expansion model in Julia, to study the evolution of the resource mix and simulate wholesale market outcomes. Since the evolution of the resource mix substantially depends on capacity factors and capital cost of generation resources, higher capacity factors justify investment in higher capital cost resources. In that case, technology-cost sensitivity analysis is conducted: in baseline scenarios, the cost of OSW is based on middle-range values from annual technology baseline of NREL; in high/low technology cost cases, we varied that to low-range and high-range respectively. Moreover, the change of electrification, in particular heat pump for residential heating and electric vehicles, is investigated in the study as well. Finally, we evaluate the sensitivity of our assessments to anticipated market design enhancements, including fast-start pricing in the energy market and clean Minimum Offer Pricing Rule (clean-MOPR). Using electricity market simulation tool (EMST), a custom-built modeling package (written in CPLEX and MATLAB), we manage to integrate day-ahead, intra-day, and real-time unit commitment and economic dispatch optimization models to faithfully replicate day-ahead and real-time energy markets and grid operations in scaled version representative of PJM.
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The Energy Systems Analysis Group (ESAG), Princeton University