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This paper describes very short-term wind prediction for power generation, utilizing a case study from Tasmania, Australia. Windpower presently is the fastest growing power generation sector in the world. However, windpower is intermittent. To be able to trade efficiently, make the best use of transmission line capability, and address concerns with system frequency in a re-regulated system, accurate very short-term forecasts are essential. The research introduces a novel approach—the application of an adaptive neuro-fuzzy inference system to forecasting a wind time series. Over the very short-term forecast interval, both windspeed and wind direction are important parameters. To be able to be gain the most from a forecast on this time scale, the turbines must be directed toward on oncoming wind. For this reason, this paper forecasts wind vectors, rather than windspeed or power output. [ABSTRACT FROM AUTHOR]

In this paper, a property rights model for electric transmission is proposed and its properties analyzed. The proposed rights, called "border flow rights," support financial hedging of transmission risk and merchant transmission expansion through associated financial rights, called "contracts for differences of differences." These financial rights allow for forward trading of both energy and transmission by a unified exchange, avoiding the bifurcation in current markets between decentralized long-term energy trading and centralized long-term transmission trading. Such long-term trading can help to support the financing of both generation and transmission assets. We consider incentive properties of such a right in the absence of lumpiness, economies of scale, and market power. [ABSTRACT FROM AUTHOR]

Calculation of wind power capacity values for risk assessment of power system adequacy has attracted great attention in the literature. And the most popular approach has been the Effective Load Carrying Capability (ELCC) method which allows for the consideration of key factors such as wind capacity factor, forced outage rates (F.O.R) of conventional power stations, system reliability targets, and the correlation between wind availability and system load. However, comparatively little attention has been paid to analysing the effects of other factors such as the number of wind farms and wind installed capacity, the length of historic time series data on demand and wind resources. This paper provides an in-depth analysis of how these factors influence the calculation of capacity value for the Australian National Electricity Market (NEM) power system using metered half-hourly wind and load data for 2006 to 2013. The analysis incorporates the periods with extreme risk events. Our results show that capacity values depend greatly on the design of the simulation model used, and highlight the importance of capturing wind and load data points relating to extremely high demand periods. We compare our NEM-wide estimates to recent estimates for the State of South Australia. [ABSTRACT FROM AUTHOR]

Abstract: Given the recent increasing public focus on climate change issues, there is a need for robust, sustainable and climate friendly power transmission and distribution systems that are intelligent, reliable, and green. Current power systems create environmental impacts as well as contributing to global warming due to their utilization of fossil fuels, especially coal, as carbon dioxide is emitted into the atmosphere. In contrast to fossil fuels, renewable energy is starting to be used as the panacea for solving climate change or global warming problems. This paper describes a feasibility study undertaken to investigate the potentialities of renewable energy including the prospective locations in Australia for renewable energy generation, in particular solar and wind energy. Initially, a hybrid model has been developed to investigate the prospects of wind energy for typical Australian region considering production cost, cost of energy, emission production and contribution from renewable energy using the Hybrid Optimization Model for Electric Renewable (HOMER), a computer model developed by the USA’s National Renewable Energy Laboratory (NREL). This model also explores suitable places around Australia for wind energy generation using statistical analysis. Subsequently, the usefulness of solar energy in the Australian context and suitable locations for solar energy generation are also investigated using a similar hybrid model. Finally, the model has been developed to investigate the prospects of renewable energy in particular wind and solar energy including specific locations in Australia that would be suitable for both wind and solar energy generation. From simulation analysis it is clearly observed that Australia has enormous potentialities for substantially increased use of renewable energy; a large penetration of renewable energy sources into the national power system would reduce CO2 emissions significantly, contributing to the reduction of global warming. [Copyright &y& Elsevier]