Abstract
This article proposes a DR program characterized by a novel compensation scheme. The proposed scheme recognizes the different characteristics of curtailment, such as the total length of curtailments within a window of time, or the number of separate curtailment events (i.e., curtailment startup), and compensates the end-user accordingly. The proposed compensation scheme features a piece-wise reward function comprised of two intervals. DR participants receive a onetime reward upfront when they enroll in the DR program and accept a set of predefined curtailment aspects. Curtailment aspects in excess of the agreed quantities are rewarded at a linear rate. This design is tailored to appeal to residential DR participants, and aims to secure sufficient flexibility at minimum cost. The parameters of the smart contract are optimized such that the system's social welfare is maximized. The optimization problem is modeled as a mixed-integer linear program. Consequently, this article updates the unit-commitment (UC) formulation with the commitment aspects of DR units. The proposed extension to the UC problem considers the critical aspects of DR participation, such as: the total length of interruptions within a window, the frequency of interruptions within a time-window irrespective of their length, and the net energy deviation from the original load profile. Deployment of the smart DR contract in the unit dispatch problem requires translating DR participants' characteristics to their equivalent aspects in conventional thermal generators, such as minimum up time, minimum down-time, start-up and shutdown costs. The obtained results demonstrate significant improvement in social welfare, notable reduction of curtailed renewable energy and reduction in extreme ramping events of conventional generators.
Highlights
T HE HIGH penetration of variable Renewable Energy Sources (RES) in modern power systems increases the requirements for operating reserves, load-following reserve in particular [1]
An ad-hoc payment is made by the operator to the Demand Response (DR)-agent, which is directly proportional to the excess amount of services: Q(·) = Q(·) − Q(·)
It is clear that higher wind penetration leads to larger and more frequent curtailment events
Summary
T HE HIGH penetration of variable Renewable Energy Sources (RES) in modern power systems increases the requirements for operating reserves, load-following reserve in particular [1]. The majority of research on DR programs focuses on optimizing DR bidding, derive the response of DR units to certain incentives under different program designs, and characterization of loads’ random behavior These studies consider only the size of curtailment by consumers. Different types of reserve have different deployment time frames (i.e., regulation, contingency, flexibility, energy, and capacity), and a load providing this reserve service must meet certain physical requirements such as: response time delay, response length, ramping duration, activation frequency [4]. Sheddability indicates the size of load which can be shed considering the load’s physical limits These three criteria fail to represent aspects such the length of curtailment events and how often can the load be interrupted.
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