Power Retailer Air-Conditioning Load Aggregation Operation Control Method and Demand Response

Abstract

Thermostatically controlled loads (TCLs) have become a major tool for the demand response (DR) program when air conditioners cause peak loads in a day during the winter or summer. To solve the problem of a direct load control with TCL usually affecting user comfort and hardly considering responsiveness, a power retailer airconditioning load aggregation operation control and demand response method was proposed in this research. From the perspective of a power retailer, a compensation mechanism for TCL was constructed, which was composed of a basic incentive program and an additional incentive program. The basic incentive program aimed to encourage users with a low response degree to increase the response capacity in order to participate in DR. An auxiliary service market control strategy based on a new compensation mechanism of the electricity retailer was detailed, which fully considered the enthusiasm of the user in mobilizing the response and reducing the load reduction fluctuation when using the state-queuing (SQ) model. Case studies were provided to verify the effectiveness of the proposed method. Compared with other compensation schemes, the simulation results showed that the compensation mechanism provided in this research was more reasonable, and it could smooth the load and reduce fluctuations. The compensation distribution among the user groups could effectively control the uniform distribution in the user groups in the temperature range, and it could mobilize users at different temperatures to participate in DR.

Optimal Allocation Method of Residential Air-Conditioners: Trade-Off Solutions Between Economic Costs and Aggregation Reliability

“…There may be an inestimable aggregation deviation. Reference [18] designs a new incentive mechanism composed of the basic and additional compensation program, and participants who respond actively are rewarded with more bonuses. The aggregation reliability may be improved.…”

“…Here, the Big-M method is used for linearization [32]. In (18), the user participation ratio β k is a continuous variable and σ s is a 0-1 variable. Therefore, a sufficiently large positive value M is introduced to transform the user incentive cost into (34):…”

A Decision Model for an Electricity Retailer With Energy Storage and Virtual Bidding Under Daily and Hourly CVaR Assessment

“…Self-production of energy was considered in [8]- [11], [15]- [18], and [26] while energy storage system and virtual bidding were only considered in [11] and [27], respectively. The determination of the retailer's optimal power bidding curves in the electricity market was considered in [8]- [14], [18], [20], [22], and [28]- [31]. Among all existing risk management tools for scenariobased decision-making models under uncertainty, CVaR has received increased attention in decision-making models for different electricity market participants such as generation companies, large consumers, and retailers [5].…”

Power Tracking Control of Heterogeneous Populations of Thermostatically Controlled Loads With Partially Measured States

“…Note that the same form of PDE-based models can also be derived by assuming that the dynamics of individual TCLs are described by deterministic systems while considering population heterogeneity [21]- [23]. Compared with finite-dimensional state-space models, such as state-bins [24]- [28] or state queues [29]- [31], the PDE paradigm provides a more generic framework VOLUME 11, 2023 for modeling the aggregate dynamics of TCL populations, which allows handling nonlinearity, time-varying operational conditions, and parametric uncertainties with often very simple control algorithms. However, the PDE control system design procedure generally involves more complex mathematical analysis and is more challenging.…”