scholarly journals Sizing Hydrogen Energy Storage in Consideration of Demand Response in Highly Renewable Generation Power Systems

Energies ◽  
2018 ◽  
Vol 11 (5) ◽  
pp. 1113 ◽  
Author(s):  
Mubbashir Ali ◽  
Jussi Ekström ◽  
Matti Lehtonen
Keyword(s):  
Energy Storage ◽  
Power Systems ◽  
Demand Response ◽  
Hydrogen Energy ◽  
Renewable Generation ◽  
Generation Power

scholarly journals Optimal Coordination of Aggregated Hydro-Storage with Residential Demand Response in Highly Renewable Generation Power System: The Case Study of Finland

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1037 ◽  
Author(s):  
Arslan Bashir ◽  
Matti Lehtonen
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Power System ◽  
Demand Response ◽  
Renewable Energy Sources ◽  
Renewable Generation ◽  
Generation Structure ◽  
Optimal Coordination ◽  
Residential Demand ◽  
Generation Power

Current energy policy-driven targets have led to increasing deployment of renewable energy sources in electrical grids. However, due to the limited flexibility of current power systems, the rapidly growing number of installations of renewable energy systems has resulted in rising levels of generation curtailments. This paper probes the benefits of simultaneously coordinating aggregated hydro-reservoir storage with residential demand response (DR) for mitigating both load and generation curtailments in highly renewable generation power systems. DR services are provided by electric water heaters, thermal storages, electric vehicles, and heating, ventilation and air-conditioning (HVAC) loads. Accordingly, an optimization model is presented to minimize the mismatch between demand and supply in the Finnish power system. The model considers proportions of base-load generation comprising nuclear, and combined heat and power (CHP) plants (both CHP-city and CHP-industry), as well as future penetration scenarios of solar and wind power that are constructed, reflecting the present generation structure in Finland. The findings show that DR coordinated with hydropower is an efficient curtailment mitigation tool given the uncertainty in renewable generation. A comprehensive sensitivity analysis is also carried out to depict how higher penetration can reduce carbon emissions from electricity co-generation in the near future.

scholarly journals Integration of Demand Response and Short-Term Forecasting for the Management of Prosumers’ Demand and Generation

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 11 ◽  
Author(s):  
María Carmen Ruiz-Abellón ◽  
Luis Alfredo Fernández-Jiménez ◽  
Antonio Guillamón ◽  
Alberto Falces ◽  
Ana García-Garre ◽  
...  
Keyword(s):  
Power Systems ◽  
Demand Response ◽  
Time Series Data ◽  
Load Forecasting ◽  
Real Data ◽  
Series Data ◽  
Renewable Generation ◽  
Short Term ◽  
Forecasting Models ◽  
Short Term Forecasting

The development of Short-Term Forecasting Techniques has a great importance for power system scheduling and managing. Therefore, many recent research papers have dealt with the proposal of new forecasting models searching for higher efficiency and accuracy. Several kinds of artificial intelligence (AI) techniques have provided good performance at predicting and their efficiency mainly depends on the characteristics of the time series data under study. Load forecasting has been widely studied in recent decades and models providing mean absolute percentage errors (MAPEs) below 5% have been proposed. On the other hand, short-term generation forecasting models for photovoltaic plants have been more recently developed and the MAPEs are in general still far from those achieved from load forecasting models. The aim of this paper is to propose a methodology that could help power systems or aggregators to make up for the lack of accuracy of the current forecasting methods when predicting renewable energy generation. The proposed methodology is carried out in three consecutive steps: (1) short-term forecasting of energy consumption and renewable generation; (2) classification of daily pattern for the renewable generation data using Dynamic Time Warping; (3) application of Demand Response strategies using Physically Based Load Models. Real data from a small town in Spain were used to illustrate the performance and efficiency of the proposed procedure.

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