Building and investigating generators' bidding strategies in an electricity market

In a deregulated electricity market environment, Generation Companies (GENCOs) compete with each other in the market through spot energy trading, bilateral contracts and other financial instruments. For a GENCO, risk management is among the most important tasks. At the same time, how to maximise its profit in the electricity market is the primary objective of its operations and strategic planning. Therefore, to achieve the best risk-return trade-off, a GENCO needs to determine how to allocate its assets. This problem is also called portfolio optimization. This dissertation presents advanced techniques for generator strategic bidding, portfolio optimization, risk assessment, and a framework for system adequacy optimisation and control in an electricity market environment. Most of the generator bidding related problems can be regarded as complex optimisation problems. In this dissertation, detailed discussions of optimisation methods are given and a number of approaches are proposed based on heuristic global optimisation algorithms for optimisation purposes. The increased level of uncertainty in an electricity market can result in higher risk for market participants, especially GENCOs, and contribute significantly to the drivers for appropriate bidding and risk management tasks for GENCOs in the market. Accordingly, how to build an optimal bidding strategy considering market uncertainty is a fundamental task for GENCOs. A framework of optimal bidding strategy is developed out of this research. To further enhance the effectiveness of the optimal bidding framework; a Support Vector Machine (SVM) based method is developed to handle the incomplete information of other generators in the market, and therefore form a reliable basis for a particular GENCO to build an optimal bidding strategy. A portfolio optimisation model is proposed to maximise the return and minimise the risk of a GENCO by optimally allocating the GENCO's assets among different markets, namely spot market and financial market. A new market pnce forecasting framework is given In this dissertation as an indispensable part of the overall research topic. It further enhances the bidding and portfolio selection methods by providing more reliable market price information and therefore concludes a rather comprehensive package for GENCO risk management in a market environment. A detailed risk assessment method is presented to further the price modelling work and cover the associated risk management practices in an electricity market. In addition to the issues stemmed from the individual GENCO, issues from an electricity market should also be considered in order to draw a whole picture of a GENCO's risk management. In summary, the contributions of this thesis include: 1) a framework of GENCO strategic bidding considering market uncertainty and incomplete information from rivals; 2) a portfolio optimisation model achieving best risk-return trade-off; 3) a FIA based MCP forecasting method; and 4) a risk assessment method and portfolio evaluation framework quantifying market risk exposure; through out the research, real market data and structure from the Australian NEM are used to validate the methods. This research has led to a number of publications in book chapters, journals and refereed conference proceedings

Are Canadian pension plans disadvantaged by the current structure of portfolio regulation?

We investigate the performance of Canadian pension funds relative to those from the UK and US, in the light of the ongoing quantitative asset restrictions that still apply in Canada, compared with the purer prudent person approach in the UK and US. We find that although Canadian funds often obtain better combinations of return and risk, returns are often less than could be obtained given financial market conditions, as shown by dummy portfolios split evenly between bonds and equities, or diversified into real estate, as well as mean-variance optimal portfolios. In contrast, UK and US funds typically outperform such benchmarks. Combined with criticisms of specific Canadian regulations in the light of finance theory and empirical evidence, the paper makes a case for removal of residual quantitative restrictions in Canada, and their replacement by sole prudent person regulations

Using the Mathcad Solver to Teach Portfolio Optimisation

This paper introduces a Mathcad program for teaching optimisation. The program, which involves a portfolio of equity shares, is less code oriented than GAMS and reinforces mathematical notation to a greater extent than the Excel solver. Also, the program adjusts automatically for alternative portfolios (other than the one presented) without the need for further programming. Thus, students can concentrate on examining alternative portfolios with little need to change parameters consistently.

Asset liability management using stochastic programming

This chapter sets out to explain an important financial planning model called asset liability management (ALM); in particular, it discusses why in practice, optimum planning models are used. The ability to build an integrated approach that combines liability models with that of asset allocation decisions has proved to be desirable and more efficient in that it can lead to better ALM decisions. The role of uncertainty and quantification of risk in these planning models is considered

Pension fund investment and regulation - a macro study

Pension fund assets have been accumulated rapidly during the past decades, and it is evident that this trend will continue. An immediate problem arising from the rapid accumulation of such a large volume of assets across countries is how to invest them. Pension funds differ from other institutional investors, e.g. mutual funds, in that their investment horizons are relatively long, typically 30-40 years. In addition, they are pooled assets to support people’s retirement lives. The authorities have a policy concern about their investment performance, because otherwise, the shortfalls will have to be met by the nation state (Clark and Hu 2005a). In this paper, we seek to address this issue from the macro perspective. By using a unique dataset covering 39 countries (17 EMEs and 22 OECD) and based on the classic mean-variance optimisation approach, first we find a negative impact of international portfolio investment restrictions on pension fund returns and risk, and this issue is particularly serious for EMEs. Following a shift from the QAR to the PPR, the average risk is expected to fall by 27% for EMEs pension funds, while the figure is 10% for OECD pension funds. Second, there is evidence that if higher portfolio returns are wanted, higher proportion should be invested in equities and foreign assets. Third, our results show that pension funds should value the diversification benefit arising from property investment (Booth 2002)

Software tools for stochastic programming: A Stochastic Programming Integrated Environment (SPInE)

SP models combine the paradigm of dynamic linear programming with modelling of random parameters, providing optimal decisions which hedge against future uncertainties. Advances in hardware as well as software techniques and solution methods have made SP a viable optimisation tool. We identify a growing need for modelling systems which support the creation and investigation of SP problems. Our SPInE system integrates a number of components which include a flexible modelling tool (based on stochastic extensions of the algebraic modelling languages AMPL and MPL), stochastic solvers, as well as special purpose scenario generators and database tools. We introduce an asset/liability management model and illustrate how SPInE can be used to create and process this model as a multistage SP application