paper-with-me

홈 › Papers

Localized Load Reduction Market Development Considering Network Constraints

2023-12-05 · Mohammad Panahazari, Minoo Mohebbifar, Vahid Nazari Farsani, Mahmoud-Reza Haghifam

With the development of the smart grid concept and the increasing expansion of advanced communication and measurement equipment, consumers can actively participate in the power system operation. The intelligent use of these facilities greatly helps the power system entities to achieve their objectives more efficiently and less expensively. As a beneficial facility, the market mechanism has proven to be a solution to various power system challenges. Furthermore, distributed and localized solutions have shown to be helpful in both reducing operation costs and accelerating the execution of the programs. In a generation shortage condition, to prevent unwanted load curtailment and wholesale market price spikes, utilities can get consumers' help to reduce the load in return for payments. This paper proposes a localized load reduction market model in the distribution system, in which consumers bid for their participation rate at the corresponding prices. Then, a market optimization problem will be solved by considering the technical constraints of the network through the use of Genetic Algorithm (GA). The paper then shows that utilizing the proposed model reduces operation costs.

📄 PDF Abstract BibTeX arXiv:2312.03089

Code (1)

panahazari/HDTV 공식 구현

Similar Papers 제목 키워드 기반

Network-Aware Electric Vehicle Coordination for Vehicle-to-Anything Value Stacking Considering Uncertainties

2023-04-05 · Canchen Jiang, Ariel Liebman, Hao Wang

The increased adoption of electric vehicles (EVs) has led to the development of vehicle-to-anything (V2X) technologies, including vehicle-to-home (V2H), vehicle-to-grid (V2G), and energy trading of EVs in the local grid.…

energy trading

Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-term Utility Demand Forecasting in Electricity Wholesale Markets

2022-06-23 · Chenghao Huang, Weilong Chen, Shengrong Bu, Yanru Zhang

Short-term load forecasting (STLF) plays a significant role in the operation of electricity trading markets. Considering the growing concern of data privacy, federated learning (FL) is increasingly adopted to train STLF …

Deep Reinforcement LearningDemand ForecastingDimensionality ReductionFederated Learning+1

Construction of neural networks for realization of localized deep learning

2018-03-09 · Charles K. Chui, Shao-Bo Lin, Ding-Xuan Zhou

The subject of deep learning has recently attracted users of machine learning from various disciplines, including: medical diagnosis and bioinformatics, financial market analysis and online advertisement, speech and hand…

Deep LearningDimensionality ReductionHandwriting RecognitionMedical Diagnosis+3

Pricing Mechanisms versus Non-Pricing Mechanisms for Demand Side Management in Microgrids

2025-01-17 · Cassia Nunes Almeida, Arun Narayanan, Hafiz Majid Hussain, Pedro H. J. Nardelli

In this paper, we compare pricing and non-pricing mechanisms for implementing demand-side management (DSM) mechanisms in a neighborhood in Helsinki, Finland. We compare load steering based on peak load-reduction using th…

Management

A case study : Influence of Dimension Reduction on regression trees-based Algorithms -Predicting Aeronautics Loads of a Derivative Aircraft

2018-11-16 · Fournier Edouard ENAC, Grihon Stéphane IMT, Klein Thierry IMT

In aircraft industry, market needs evolve quickly in a high competitiveness context. This requires adapting a given aircraft model in minimum time considering for example an increase of range or the number of passengers …

Dimensionality ReductionMath