Abstract
Inverter air conditioners (IACs) have gradually become the mainstream of resident air-conditioning equipment. Similar to traditional fixed-frequency air conditioners, IACs have the potential for demand response and load scheduling. However, the uncertainty of IACs is nonnegligible in generation-load scheduling. In this paper, the uncertain demand-response cost of IACs is studied for the first time. Meanwhile, based on the cost, a generation-load coordinative day-ahead scheduling model is proposed. In the scheduling, an IACs aggregator and traditional generators are coordinately dispatched to minimize the expected scheduling cost of the power system. The case study shows that the coordinative scheduling model can reduce the scheduling cost of the power system and encourage the IACs aggregator to improve their responsiveness or reduce their uncertainty, so as to improve the economy and reliability of power scheduling.
Highlights
Increasing renewable energy generation [1, 2] and load [3] have led to difficulty in power dispatch, maintenance, and safe operation
To address the above problems, this paper proposes a risk evaluation-based generation-load collaborative scheduling optimization model, where the objective function is to minimize the scheduling cost of power system and the solution is subject to the operational reliability of power system. e contributions are as follows: (1) From the perspective of the scheduler, this paper proposes a payment cost model of Inverter air conditioners (IACs) considering the uncertainty in demand response for the first time, which includes the payment cost of demand response and uncertain-risk cost
In the traditional load-scheduling contract between the system operator and users, after the airconditioning load responds to the scheduling instruction, the system operator needs to pay a certain fee to compensate the load according to the actual response of the load. e responsive deviation of IACs aggregator will affect the final clearing expenses; the uncertainty of the payment cost should be considered by the scheduler. e payment cost Cpay of lth IACs aggregator at tth scheduling period consists of two parts: one is compensation fee paid to users according to the actual response; the other is the penalty fee caused by the responsive uncertainty of the aggregator, which is revenue for schedulers, as expressed in
Summary
Increasing renewable energy generation [1, 2] and load [3] have led to difficulty in power dispatch, maintenance, and safe operation. Inverter air conditioners are rarely incorporated into the day-ahead scheduling of power system as a kind of schedulable load or response-demand resource, where the control strategy, controllable duration, and uncertainty should be all considered in it. In the literature, the feasibility and technologies of inverter air conditioners to provide demand-response service have been fully studied, the economic evaluation and load-scheduling methodology are still lack of consideration, especially when the uncertainty is regarded as a kind of risk cost for the scheduler. To address the above problems, this paper proposes a risk evaluation-based generation-load collaborative scheduling optimization model, where the objective function is to minimize the scheduling cost of power system and the solution is subject to the operational reliability of power system. To evaluate the DR potential of IACs, IACs should update and report their operational status to the aggregator every scheduling period
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