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access icon openaccess Risk assessment of demand response considering wind power generation

This is an open access article published by the IET under the Creative Commons Attribution-NoDerivs License (http://creativecommons.org/licenses/by-nd/3.0/)
Received 04/09/2018, Accepted 19/09/2018, Published 24/10/2018

Demand response can reduce peak load, transfer part of peak load to valley load, and reduce system risk at peak time. In this study, a calculation model of power grid loss risk is proposed, which is suitable for evaluating the risk changes caused by the demand response, and calculating the corresponding risk value under the demand response load curve. In the calculation of demand response load, considering the impact of two measures of time-of-use (TOU) price and incentive measure, the TOU and incentive load curve are obtained based on the user's maximum benefit. In order to gain the corresponding load risk index, Monte Carlo simulation method is used, demand response load curve is taken as input, and load point fault time, load point fault rate and expected energy not serve indexes are introduced. Moreover, compared with the risk ratio of the original load curve, the simulation results verify the effectiveness of the proposed risk model, and prove that the demand response measures can transfer the risk of partial high load and balance the risk distribution.

Inspec keywords: wind power plants; pricing; Monte Carlo methods; demand side management; power generation economics; risk analysis; power grids

Other keywords: peak load; risk changes evaluation; Monte Carlo simulation method; risk ratio; wind power generation; load point fault rate; load risk index; power grid loss risk calculation model; incentive measure; peak time; load point fault time; demand response measures; incentive load curve; risk assessment; risk distribution; valley load; demand response load curve; risk model; TOU; time-of-use price; partial high load; risk value calculation; system risk reduction

Subjects: Monte Carlo methods; Wind power plants; Power system management, operation and economics

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