Distributed Demand Response Management for a Virtually Connected Community With Solar Power

Abstract

With the high proliferation of solar power, curtailments and higher capacity reserves are required for a reliable power system operation. However, system operators can tap into demand flexibility to maintain reliability affordably. Temperature-controlled loads (TCL) have higher flexibility in demand response due to their frequency of operation, power rating, and tolerance in the desired operating region. In this study, a TCL demand flexibility quantification is presented using temperature measurements and consumer preferences, and predictions of TCL demand flexibility and solar power generation are used to improve demand response (DR) reliability. The utility can leverage predictions to issue DR requests considering resource adequacy and operational costs. Consumers are formed as a virtually connected community, and an aggregator facilitates the utility in providing situational intelligence and distributing DR requests among consumers. A distributed DR management framework is proposed based on demand flexibility to (a) simplify the optimization and (b) improve optimality. Typical results show power consumption reduction during peak reduction and emergency DR requests and power consumption with low variability during capacity firming requests compared to individual thermostat controls. Two indices to measure DR reliability and consumer comfort are defined, and results are presented for different DR requests. INDEX TERMS demand flexibility, distributed demand response, DR reliability, solar PV power, temperature-controlled loads, virtually connected community.

Economic Model for Coordinating Large-Scale Energy Storage Power Plant With Demand Response Management Options in Smart Grid Energy Management

“…is the amount of shiftable demand at the time t and 𝜎 is the percentage of the shiftable load. 𝑃 !,) 2 is the demand real power of the substation in each distribution smart grid at node n and the time t, and 𝐷 ! (" is the new demand changed at the time t in the demand response program.…”

“…In the above relation, (𝑃 !,) 2 ) is equal to the active load in the nth node of the smart grid at time t. (𝑃 !,) 23 ) is equal to the real power of DGs in the nth node of the smart grid at time t. (𝑝 !,/K ) and (𝑝 !,K/ ) are equal to real power flow on line ij and ji, respectively. In ( 14) the capacity limit of each distribution grid line is shown.…”

“…This figure ensures that the proposed model for the demand response management problem works properly. Figure (2) shows each case's energy storage plant charge and discharge status in 33-bus system. In this figure, the negative area is related to charging, and the positive area is related to energy storage plant discharge.…”

“…Economically, demand response management, along with other intelligent technologies such as distributed generation resources and energy storage systems, will increase network efficiency and reduce energy purchase costs [1]. Independent system operators (ISO) can use the flexibility of demand response management programs to maintain reliability cost-effectively [2]. Utilizing demandside flexibility through aggregators is a new move that distribution system operators are interested in, leading to power balance in the primary substation or voltage regulation in the secondary substations [3].…”

Adaptive distributed demand side management with weighted dimension reduction for energy resource management in smart grid

“…In most cases, in previous researches, this topic was generally discussed. That is, from the point of view of the structure of calculations for the management of energy resources and DR, the centralized method is mostly used [7,8], or fully distributed computing methods are used [9,10]. Smart grid cyber-security cannot be provided by the fully distributed methods [11].…”