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A Dynamic Penalty Cost Allocation Based Uncertain Wind Energy Scheduling in Smart Grid

The intermittent nature of wind energy conversion presents a risk to the Independent System Operator (ISO) in a real time electricity market. Consequently, there is a need to appropriately incorporate this risk in the wind energy scheduling paradigm. In the present work, the intermittency associated risk has been modeled as part of a cost optimization problem for the ISO in real time. A model to minimize the risk has also been proposed using various cost models that use dynamic risk aversion costs and reflect the market and system operating conditions. The two dynamic penalty cost/risk models included are, rescheduling cost and contractual compensation cost for wind energy deviation. The results obtained are compared with those from the deterministic model. The proposed approach is simulated on the IEEE 30 bus system and the findings from the proposed approach for wind energy scheduling lead to a low operational cost to the ISO in the real time market considered in the study. Among other observations, the consideration of uncertainty in Day-Ahead market leads to increase in cost savings of ISO with increase in wind uncertainty, but a corresponding reduction in the scheduled wind energy in the same market.