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A review on demand response based ancillary services offered by industries

Ghasemi Ahmad, Gerami Nilufar

Journal of Power Technologies

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2024

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Vol. 104, nr 1

32--55

EN

Industrial power consumers have a considerable share of the global power demand; as a result, effective solutions have to be adopted to optimize the industrial power consumption. Demand response Programs (DRPs) provide such solutions. These programs are growingly studied as the industrial power consumption has increased and the implementation costs of the new technologies have decreased in recent years. DRP implementation reduces the dependency on the expensive energy storage technologies and flexible backup power sources. It seems that, DRP is not widely used in industry, yet its benefits are not practically exploited. The present work reviews the implementation of DRPs in industry and introduces the opportunities of industries for offering ancillary services to the market. Then, the industries which highly suit the specific kind of industrial DRPs are introduced and their processes are analyzed from the DRP point of view. Next, the DRP projects are continentally categorized and the advancements of different countries in specific kind of industrial DRPs are noted. Finally, the discussions and conclusion are presented.

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The application of the fuzzy rule-based Bayesian algorithm to determine which residential appliances can be considered for the demand response program

Kapler Piotr

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2023

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Vol. 71, nr 4

art. no. e146106

EN

This paper proposes the usage of the fuzzy rule-based Bayesian algorithm to determine which residential appliances can be considered for the Demand Response program. In contrast with other related studies, this research recognizes both randomness and fuzziness in appliance usage. Moreover, the input data for usage prediction consists of nodal price values (which represent the actual power system conditions), appliance operation time, and time of day. The case study of residential power consumer behavior modeling was implemented to show the functionality of the proposed methodology. The results of applying the suggested algorithm are presented as colored 3D control surfaces. In addition, the performance of the model was verified using R squared coefficient and root mean square error. The conducted studies show that the proposed approach can be used to predict when the selected appliances can be used under specific circumstances. Research of this type may be useful for evaluation of the demand response programs and support residential load forecasting.

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Challenges of Implementing Demand Side Management in Developing Countries

Goyal Govind Rai, Vadhera Shelly

Journal of Power Technologies

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2020

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Vol. 100, nr 1

43--58

EN

The energy crisis along with increasing per capita energy consumption of cities and nations poses a worldwide challenge. Smart grid technology facilitates the shift to more sustainable technologies such as microgrids, distributed generation, demand side management, and advanced metering infrastructure. This paper is mainly focused on demand side management (DSM); conventional and recent models of demand side management found in the literature are discussed. Implementation and practices of demand side management at various locations in India are also unveiled. With 16 pilot smart grid projects underway in India, there is a need to report on how smart grid technologies are living up to their potential. It is also essential to identify and discuss related challenges and the issues in the implementation of DSM. This paper focuses on analyzing global best practices in DSM and their implementation to fulﬁll the estimated potential, particularly in the residential, industrial and agriculture sectors.

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The new adaptive Under Frequency Load Shedding technique in an automated Distribution Network considering demand response programs

Mokari-Bolhasan A., Taghizadegan-Kalantari N.

Journal of Power Technologies

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2018

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Vol. 98, nr 1

127--138

EN

Under Frequency Load Shedding (UFLS) is an important protection scheme to maintain the frequency of a Distribution Network (DN) consisting of Distributed Generations (DGs) exposed to power deficit. The different location and amount of load curtailments based on different parameters are acquired from the available literature. In this paper, an optimal adaptive UFLS method with the advent of two main modules has been proposed. The proposed method provides a revised Rate of Change of Load (ROCOFL) index related to bus voltage and load power consumption (ROCOFLpv). Using a wide area measurement system, Demand Response (DR) technology aimed at shedding fewer loads is emerging against a background of the smart grid. In addition, smart appliances can provide a real-time data packet in which frequency, the rate of change of frequency, voltage magnitude and breaker status are measured. The proposed method is implemented in five different load schemes considering DR programs. Comparative analyses are illustrated in this paper to assert the efficiency of implementing DR programs in which cost function and amounts of shedding loads are decreased. The results demonstrate that DR programs cannot be used for a big power unbalance in an islanded micro grid. The unintentional delay time imposed by DR and the small inertia existing in an islanded distribution network restrict the use of DR programs.