Abstract
This paper presents a dynamic energy balancing cost model for day ahead market scheduling under generation uncertainties and demand response penetration. The proposed dynamic models include temporally coupled system conditions to model various types of costs incurred due to uncertain wind energy generation and conventional generation uncertainty. The cost models of wind energy schedule in real-time markets for the deviation from DA estimations is modeled using compensation cost, dynamic adjustment cost, and rescheduling cost. The generation uncertainties and outages considered for conventional generation facility is expressed using geometric distribution to include temporal characteristics of generation outage rate. The problem is formulated as an operational cost minimization problem. The efficacy of the proposed dynamic balancing cost approach is verified using various levels of uncertainty. Further, sensitivity analysis is carried out with respect to various levels of wind penetration and outage rates for all the technoeconomic aspects of resource scheduling. The simulation results for the proposed approach are presented and discussed against static penalty cost methodology. The sensitivity analysis demonstrate the superiority of the proposed dynamic cost models in terms of technoeconomic performance attributes compared to the static cost models.
Original language | English |
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Article number | 8373735 |
Pages (from-to) | 4908-4916 |
Number of pages | 9 |
Journal | IEEE Transactions on Industry Applications |
Volume | 54 |
Issue number | 5 |
DOIs | |
Publication status | Published - 1 Sept 2018 |
Externally published | Yes |
Keywords
- Binary grey Wolf optimizer (BGWO)
- day ahead markets (DAM)
- demand response
- generation uncertainty
- mean adjustment cost
- stochastic wind energy scheduling
ASJC Scopus subject areas
- Control and Systems Engineering
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering