Institution of incentive-based demand response programs and prospective policy assessments for a subsidized electricity market

Alasseri, Rajeev; Rao, T. J.; Sreekanth, K. J.

doi:10.1016/j.rser.2019.109490

Cited by 40 publications

(14 citation statements)

References 59 publications

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“…As an essential element of an intelligent grid, users participating in the electricity market-oriented DR enables heterogeneous end users can acquire tailor-made utilities by coordinating interactions with utilities (Sharifi et al, 2019). Thence, demand-response programs play an important role in influencing the energy consumption of end users (Alasseri et al, 2020). Utilities offer demand-side response services to improve customer satisfaction, and the amount of electricity customers demand influences demand response policies.…”

Section: Literature Reviewmentioning

confidence: 99%

5G Wireless Networks in the Future Renewable Energy Systems

et al. 2021

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This paper focuses on the strategies that employ the fifth generation (5G) wireless networks in the optimal management of demand-side response in the future energy systems with the high penetration of renewable energy sources (RES). It also provides a comparison between advantages and challenges of 5G networks in demand-response renewable energy grids. Large-scale renewable energy integration always leads to a mismatch between generation and load demand in the short run due to the intermittency. It is often envisioned that 5G wireless networks that were recently launched and would most likely be fully deployed worldwide by 2035 would bring many technological and economic benefits for a plethora of the future high-renewables grids featuring electric transport and heating as well as prosumers generating renewable energy and trading it back to the grid (for example, in the vehicle-to-grid (V2G) framework) and among themselves using peer-to-peer (P2P) networks. Our paper offers a comprehensive analysis of 5G architecture with the perspectives of optimal management of demand-side response in the smart grids of the future. We show that the effective deployment of faster and more reliable wireless networks would allow faster data transfers and processing, including peer-to-peer (P2P) energy trade market, Internet of Vehicles (IoV) market, or faster smart metering, and thence open the path for the full-fledged Internet of Energy (IoE). Moreover, we show that 5G wireless networks might become in the future sustainable energy systems paving the road to even more advanced technologies and the new generations of networks. In addition, we demonstrate that for the effective management of energy demand-side response with a high share of renewables, certain forms of governments funding and incentives might be needed. These are required to strengthen the support of RES and helping to shift to the green economy.

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Section: Literature Reviewmentioning

confidence: 99%

5G Wireless Networks in the Future Renewable Energy Systems

et al. 2021

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“…In [15], it was highlighted that consumers are sensitive to cost savings and more than 80% of them have considered the possibility of using automatic controls for some domestic appliances schedule. Thus, it is necessary to explore new business models [16,17] to find the equilibrium between a profitable operation for utilities as well as for individual prosumages. The virtual aggregation of spare storages which have been installed in private households could be profitable with the appropriate feed-in tariff according to [18].…”

Section: Introductionmentioning

confidence: 99%

Intent Profile Strategy for Virtual Power Plant Participation in Simultaneous Energy Markets With Dynamic Storage Management

et al. 2022

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The emergence of distributed energy resources in the electricity system involves new scenarios in which domestic consumers can be aggregated in virtual power plants to participate in energy markets. In this paper, a reconfigurable hierarchical multi-time scale framework is developed by combining the concepts of dynamic storage virtualization and intent profiling with model predictive control. The combined implementation of these concepts allows the simultaneous weighted participation in different energy markets, not only according to some aggregators' criteria, but also to several risk factors. In a first stage, the framework optimizes the strategy for bidding in day-ahead market whereas the second one consists of a control stage to mitigate deviations and potential penalties. The smart management of individual storage virtualization enables the participation in the demand-response program, which improves the forecasted economical profit related to the day-ahead participation. The changes in the schedule are performed considering new potential penalties. The framework is reconfigurable at every sample time at control stage. This enables to make dynamic participations depending on node availability or system peaks. The proposed case studies cover day-ahead and demand-response participations, but the framework is open to other multi-service configurations. The results have been assessed with satisfactory conclusions.

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“…Energy management systems have been proposed for optimal DR scheduling in South Africa [40], while scenario modeling has been used to guide industrial DR in Nigeria [41]. Surveys were used to assess customer willingness to participate in DR in Kuwait, which has a subsidized electricity market [42]. In India, the regulations and political economy of the electricity market have been studied for a DR introduction [43], and dynamic pricing has been studied specifically in the context of solar micro-grids [44].…”

Section: Introductionmentioning

confidence: 99%