Investigating the Impacts of Different Price-Based Demand Response Programs on Home Load Management

Rastegar, Mohammad; Fotuhi‐Firuzabad, Mahmud; Choi, Jaeseok

doi:10.5370/jeet.2014.9.3.1125

Cited by 10 publications

(3 citation statements)

References 13 publications

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“…RTP-based DR implementation requires fully deployed smart metering infrastructures. Nevertheless, even with the required hardware implementations, residential consumers are still hesitant to embrace RTP due to the lack of ability in responding to real-time price fluctuations [79]. Level-based pricing is offered in IBR programs.…”

Section: Price-based Demand Responsementioning

confidence: 99%

Futuristic Sustainable Energy Management in Smart Environments: A Review of Peak Load Shaving and Demand Response Strategies, Challenges, and Opportunities

2020

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The emergence of the Internet of Things (IoT) notion pioneered the implementation of various smart environments. Smart environments intelligibly accommodate inhabitants’ requirements. With rapid resource shrinkage, energy management has recently become an essential concern for all smart environments. Energy management aims to assure ecosystem sustainability, while benefiting both consumers and utility providers. Although energy management emerged as a solution that addresses challenges that arise with increasing energy demand and resource deterioration, further evolution and expansion are hindered due to technological, economical, and social barriers. This review aggregates energy management approaches in smart environments and extensively reviews a variety of recent literature reports on peak load shaving and demand response. Significant benefits and challenges of these energy management strategies were identified through the literature survey. Finally, a critical discussion summarizing trends and opportunities is given as a thread for future research.

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Section: Price-based Demand Responsementioning

confidence: 99%

Futuristic Sustainable Energy Management in Smart Environments: A Review of Peak Load Shaving and Demand Response Strategies, Challenges, and Opportunities

2020

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“…This scheme has an effect on electric charge saving. Detailed description about DM using the ESS is represented in [23,24]. When the ESS1 reaches the lower limit (13.4s), the ESS1 stops discharging and the grid power is injected.…”

Section: Case Studymentioning

confidence: 99%

Complementary Power Control of the Bipolar-type Low Voltage DC Distribution System

Byeon¹,

Hwang²,

Kim³

et al. 2015

Journal of Electrical Engineering and Technology

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-In this paper, a new power control strategy for the bipolar-type low voltage direct current (LVDC) distribution system is being proposed. The dc distribution system is considered as an innovative system according to the increase of dc loads and dc output type distribution energy resources (DERs) such as photovoltaic (PV) systems and energy storage systems (ESS). Since the dc distribution system has many advantages such as feasible connection of DERs, reduction of conversion losses between dc output sources and loads, no reactive power issues, it is very suitable solution for new type buildings and residences interfaced with DERs and ESSs. In the bipolar-type, if it has each grid-interfaced converter, both sides (upper, lower-side) can be operated individually or collectively. A complementary power control strategy using two ESSs in both sides for effective and reliable operation is proposed in this paper. Detailed power control methods of the host controller and local controllers are described. To verify the performances of the proposed control strategy, simulation analysis using PSCAD/EMTDC is being performed where the results show that the proposed strategy provides efficient operations and can be applied to the bipolar-type dc distribution system.

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“…It is a basic type, where the rates of load per unit consumption vary in different time blocks. The rates during peaks are high and during off-peak periods are low [8]. Critical peak pricing rates consist of a pre-specified high load usage price imposed on Time of Use rates.…”

Section: Introductionmentioning

confidence: 99%

Demand Response Unit Commitment Problem Solution for Maximizing Generating Companies’ Profit

2017

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Over the recent years there has been an immense growth in load consumption due to which, Load Management (LM) has become more significant. Energy providers around the world apply different load management concepts and techniques to improve the load profile. In order to reduce the stress over the load management, Demand Response Unit Commitment (DRUC), a new concept, has been implemented in this paper. The main feature of this concept is that both the energy providers and consumers must participate in order to get mutual benefits hence maximizing each of their profits. In this paper we discuss the time-based Demand Response Program since there is no penalty observed in this program. When the Demand Response was combined with Unit Commitment and compiled it was observed that a satisfactory solution resulted, which is proved to be mutually beneficial for both Generating Companies (GENCOs) and their customers. Here, we have used a Cat Swarm Optimization (CSO) technique to find the solution for the DRUC problem. The results are obtained using CSO technique for UC problem with and without DR program. This is compared with the results obtained using other conventional methods. The test system considered for the study is IEEE39 bus system.

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Investigating the Impacts of Different Price-Based Demand Response Programs on Home Load Management

Cited by 10 publications

References 13 publications

Futuristic Sustainable Energy Management in Smart Environments: A Review of Peak Load Shaving and Demand Response Strategies, Challenges, and Opportunities

Futuristic Sustainable Energy Management in Smart Environments: A Review of Peak Load Shaving and Demand Response Strategies, Challenges, and Opportunities

Complementary Power Control of the Bipolar-type Low Voltage DC Distribution System

Demand Response Unit Commitment Problem Solution for Maximizing Generating Companies’ Profit

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