Abstracts
Keynote: Enabling Innovation in Energy with MathWorks Technology
Development and innovation have significantly increased across the many engineering disciplines in the energy sector, placing an increased emphasis on adopting software tools that effectively support the pace and scope of this development and innovation. To fully meet the many challenges of this drive in innovation, organisations will require new approaches for the design, operation, and analysis of products and systems under the backbone of technical, economic, environmental, and regulatory considerations. MathWorks products enable users to effectively analyse large operational data sets, evaluate energy resources, develop systems for power generation and distribution, forecast electrical load, model energy markets, assess trading risk, and create products that consume less energy and are environmentally friendly.
Electricity Load and Price Forecasting with MATLAB
This session demonstrates how to build a short-term load (or price) forecasting system with MATLAB. Accurate load forecasts are critical for utility and system operator planning and operation. The load forecast influences a number of decisions, including which generators to commit for a given period, and broadly affects wholesale electricity market prices. Load forecasting algorithms typically also feature prominently in hybrid models for electricity prices, some of the most accurate class of approaches for modelling electricity markets. The electricity price forecast is used widely by market participants in many trading and risk management applications.
Assessing the Impact of Innovative Electric Grid Technologies Using Modelling and Simulation
Effectively characterising and assessing the behaviour of innovative technologies is becoming increasingly important for system operators, generation companies, transmission companies, and distribution companies. For example, the emerging technologies of the Smart Grid have placed renewed importance on effective methods to evaluate system operation, stability, capacity, and unbalanced characteristics at the distribution level. At the transmission level, non-dispatchable generation, such as wind farms, offsets dispatchable generation and can lower confidence levels on congestion calculations. In this session, we discuss the roles that modelling and simulation play in meeting the operational, reliability, security, and economic challenges that innovation naturally brings to system operation. As technical and economic operation are not mutually exclusive, both are considered through an example case study, allowing direct observation of the interaction between the two.
Energy Trading and Risk Management with MATLAB
Can you evolve and optimise your analytics in response to rapidly changing market conditions? Can you easily share your analysis with partners and colleagues? MATLAB can streamline the development of energy trading and risk management applications from inception to deployment. This session presents a demonstration of computing cash-flow-at-risk and expected profit from operating a portfolio of gas-fired plants.
During this presentation we will show a workflow that demonstrates how you can use one common analysis environment, MATLAB, to:
- Import data from multiple data sources (e.g., CSV, Excel, Oracle, SQL Server)
- Analyse that data, including statistical and other mathematical analysis, graphical visualisations, and finance-specific modelling
- Share this analysis with coworkers, management, clients, and others
Highlights shown specific to this case study include:
- Modelling and simulating natural gas prices, temperature, and electricity prices
- Calculating optimal dispatch
- Computing cash-flow-at-risk for a portfolio of gas-fired power plants
- Deploying an energy trading application as an Excel add-in
This presentation is for practitioners in energy trading whose focus is quantitative analysis, modelling, risk management, or deal valuation.
Investigating Dynamic Performance of Solar and Wind Farms
Graham Dudgeon and Bradley Horton
Ensuring both economic operation and quality of supply is becoming increasingly important for wind turbine and photovoltaic power systems. This presentation demonstrates how modelling and simulation enable effective investigation of the dynamic performance and power management of typical grid-connected renewable systems. Model abstraction techniques to improve simulation speed, including the use of average-value power-electronic converters, are also considered. Further speed advantage can be realised through the use of parallel computing, which can return the results of multiple scenarios in a time-effective manner.