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R&D NESTER PRESENTS “RENEWABLE ENERGY DISPATCH TOOLS” PROJECT IN BEIJING

On December 15th 2016, in the headquarter of CEPRI (Chinese Electric Power Research Institute) in Beijing, China, R&D Nester presented results of the project entitled Renewable Energy Dispatch Tool to a panel of experts from CEPRI and several universities in China.

This project was develop by R&D Nester, a research and development center owned by REN (Portuguese TSO) and State Grid of China.

The work of the last 3 years, which includes several deliverables and tools with reports, was presented and discussed.

The main goal of the project is to deploy new and improve existing tools to be used by the system operators to manage high level of intermittent renewable energy such wind and solar.

The project is split in six tasks:

Task 1: Improve the accuracy of the wind power forecast tool including off-shore, by increasing the amount of forecasted power, better dynamic combination of forecasts with real time data from the SCADA, advance methods for extreme wind condition.

Task 2: Dimensioning the amount of additional reserves needed due to the forecast error, based on stochastic data.

Task 3: Technical criteria for curtailment of renewable generation.

Task 4: Implement a solar power forecast tool taking advantage of having solar radiation sensors installed at TSO substations spread in the country. Use of sky cameras for assessing cloud index.

Task 5 & 6: Assess and demonstrate the technical capability of renewable generation to provide frequency and voltage control.


R&D Nester also addressed the several articles that were published as a result of the work performed, namely:

  • "Ensemble-Based Estimation of Wind Power Forecast Uncertainty", EEM15 - 12ª Conferência Internacional do Mercado Europeu da Energia, May/2015,
  • "Improvements in wind power forecast", IO15 - XVII Congresso da APDIO, Sep/2015,
  • "Wind power forecast uncertainty using dynamic combination of predictions", DEMSEE 2015, Sep/2015,
  • "Wind power forecast uncertainty using dynamic combination of predictions", Periodica Polytechnica Electrical Engineering and Computer Science, 59(3), pp. 78-83, Aug/2015,
  • "Probabilistic dimensioning of tertiary control reserve driven by the intermittency of renewable generation in Portugal", Cigré Session 46, Paris, Aug/2016.


The work performed gives a strong contribution to the risk management of further integration of renewable energy in the electric system, and provides practical tools for Network and System Operators.

Some of the achieved results are already in real operation.


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