Modeling study on flexible load's demand response potentials for providing ancillary services at the substation level

Abstract

Demand Response (DR) is an important component for the establishment of smart electricity grids. It can decrease the system peaks through load shedding or shifting and optimize the utilization of the existing grid assets, which delays the need for costly upgrades. DR can also enable the integration of intermittent and distributed energy resources (DER) into the existing electricity grid. Fast DR from aggregated flexible loads can provide ancillary services (AS) to absorb grid disruptions and may replace the expensive fast-ramping reserve generation units. This study presents a methodology for load aggregation based on the prioritization of loads according to their flexibility. Different flexible load types are categorized as Thermostatically Controlled Loads (TCL), Urgent Non-TCL, Non-urgent Non-TCL, and Battery-based Loads. Models based on their physical behaviour are developed and simulations performed to apply the proposed aggregation and control algorithm. Results show that the loads during peak hours can be shed off without rebound demand spikes after the DR event commonly seen in other types of DR programs. The algorithm also automatically adjusts the power demand according to the output of the distributed renewable generation, mitigating disruptions due to variations of the DER output. Additionally, the algorithm is able to adjust the load demand dynamically according to the fluctuations of electricity price.

Scheduling of Battery Energy Storage and Demand Response Resource in Balancing Ancillary Service

“…It shall be noted that in various markets such as California electricity market, the period of estimation for future demand and generation in regulation ancillary service is usually 5-min interval [9]. 1 ;…”

“…Moreover, the smart controlling devices give the chance to market operator the control of consumption in real-time It shall be noted that participation of DR and BES in balancing ancillary service has been presented in various technical references. In [1] the impact of DR on the flexibility of grid in the substation level is analyzed. The strategy of DR participation in frequency reserve service is represented in [2].…”

Electricity Market Assessment in Wind Energy Integrated Power Systems with the Potential of Flexibility: A Boundary Condition Approach

“…According Demand response resources can provide ancillary services to absorb net-load disruptions and may replace the expensive fastramping reserve generation units [27]. In many papers, DRPs are mainly categorized into two main groups [28,29], price- by interruptible loads has been investigated in [30].…”

“…The capacities of ramp-up and -down capability of demands are limited by their maximum ramp-rates in (24)-(25), respectively. System requirements for ramp-up and -down are met in (26)-(27) considering slack variables, respectively. Finally, the non-negativity of ramp-up and -down slack variables is seen in(28).…”

Online Area Load Modeling in Power Systems Using Enhanced Reinforcement Learning

“…The static load features of the area loads seen from a single boundary bus can be represented by a ZIP load (a combination of constant-impedance, constant-current and constant-power load) model [3] or by an exponential model [4]. A number of researchers has proposed static load models for area loads in distribution networks [5,6]. In reality, to ensure a reliable supply of power, electricity is delivered from external power supply networks to area loads through multiple lines simultaneously.…”