Electricity markets face a substantial amount of uncertainty. Traditionally this uncertainty has been due to varying demand. With the integration of larger proportions of volatile renewable energy, this added uncertainty from generation must also be faced. Conventional electricity market designs cope with uncertainty by running two markets: a day ahead or pre-dispatch market that is cleared ahe...

Approximations made in day-ahead markets can result in suboptimal or even infeasible schedules for generating units and inaccurate predictions of actual costs and wind curtailment. Here we compare different optimal models of day-ahead markets based on unit commitment (UC) formulations, especially energyvs. power-based UC; excluding or including startup and shutdown trajectories; and determinist...

Approximations made in day-ahead markets can result in suboptimal or even infeasible schedules for generating units and inaccurate predictions of actual costs and wind curtailment. Here we compare different optimal models of day-ahead markets based on unit commitment (UC) formulations, especially energyvs. power-based UC; excluding or including startup and shutdown trajectories; and determinist...

In future energy systems, peaks in the daily electricity generation and consumption are expected to increase. The “smart grid” concept aims to maintain high levels of efficiency in the energy system by establishing distributed intelligence. Software agents (operating on devices with unknown computational capabilities) can implement dynamic and autonomous decision making about energy usage and g...

In this paper a novel approach for sequential bidding on day-ahead auction markets for spot energy and power systems reserve is presented. For the spot market a relatively simple method is considered as a competitive market is assumed. For the reserve market one bidder is assumed to behave strategically and the behavior of the competitors is summarized in a probability distribution of the marke...

NOTICE The submitted manuscript has been offered by an employee of the Midwest Research Institute (MRI), a contractor of the US Government under Contract No. DE-AC36-99GO10337. Accordingly, the US Government and MRI retain a nonexclusive royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for US Government purposes. This report was pre...