Peerapat Vithayasrichareon

Impact of Electric Vehicles and Solar PV on Future Generation Portfolio Investment

This study assesses the impact of electric vehicle (EV) uptake and large-scale photovoltaic (PV) investment on the economics of future electricity-generation portfolios. A Monte-Carlo-based portfolio modeling tool was used to assess the expected overall industry cost, associated cost uncertainty, and CO2 emissions of future generation portfolios, where both EVs and PV generation have achieved major deployment. The Australian National Electricity Market (NEM) was used as a case study under uncertain future fuel and carbon prices, electricity demand, and plant capital costs. Two EV charging scenarios were considered: 1)unmanaged charging which commences immediately as the EVs arrive at suitable charging infrastructure and 2)managed charging where EV charging loads are managed so that they better align with PV output. Results show that there are potentially valuable synergies between PV generation and EV charging demand in minimizing future electricity industry costs, cost uncertainties, and emissions, particularly when EV charging loads can be managed. The value of PV generation and managed EV charging is greater for higher EV fleet size and moderate carbon prices.

Electricity generation portfolio evaluation for highly uncertain and carbon constrained future electricity industries

This paper proposes a stochastic model based on Monte-Carlo simulation to assess the expected costs and risks of different generation portfolios for electricity industries in an increasingly uncertain and carbon constrained world. The approach can incorporate uncertain carbon and fossil-fuel prices of virtually any probability distributions, as well as possible correlations between them. The tool provides expected overall costs and their associated probability distribution for any possible generation portfolio mix. The model is applied to a case study of an electricity industry with coal, CCGT and OCGT generation options that faces uncertain future carbon and fuel prices. Lognormal distributions are used to model fuel and carbon prices uncertainty. Results from the case study highlight some important issues including the potentially significant interactions between carbon and gas prices on portfolio performance. The proposed model enables the tradeoffs between expected system generation cost, associated cost uncertainty and CO2 emissions among generation portfolios to be identified.

Generation portfolio analysis for low-carbon future electricity industries with high wind power penetrations

This paper employs a Monte Carlo based decision-support tool to assess the expected overall generation costs and risks of different thermal plant portfolios with high wind power penetrations. In particular, we present a case study of an electricity industry with Coal, CCGT, OCGT and Wind generation options that faces uncertain future fuel prices, carbon pricing, demand, and plant capital costs. The tool uses half-hourly demand and wind generation data from South Eastern Australia, and Australian estimates of new-build thermal plant costs. It incorporates a Monte-Carlo extension to standard optimal generation mix methods combined with risk weighting techniques from portfolio theory. The implications of different wind penetration levels on the expected costs and risks, and associated emissions of different thermal plant portfolios are explored. Results from the case study highlight the potentially complex interactions between high levels of intermittent generation and the costs, risks and emissions of future electricity industries with different portfolios of Coal and Gas-fired plants.

Impact of electric vehicles and solar PV on future generation portfolio investment

This study assesses the impact of electric vehicle (EV) uptake and large-scale photovoltaic (PV) investment on the economics of future electricity-generation portfolios. A Monte-Carlo based portfolio modeling tool was used to assess the expected overall industry cost, associated cost uncertainty, and CO2 emissions of future generation portfolios, where both EVs and PV generation have achieved major deployment. The Australian National Electricity Market (NEM) was used as a case study under uncertain future fuel and carbon prices, electricity demand, and plant capital costs. Two EV charging scenarios were considered: 1) unmanaged charging which commences immediately as the EVs arrive at suitable charging infrastructure and 2) managed charging where EV charging loads are managed so that they better align with PV output. Results show that there are potentially valuable synergies between PV generation and EV charging demand in minimizing future electricity industry costs, cost uncertainties, and emissions, particularly when EV charging loads can be managed. The value of PV generation and managed EV charging is greater for higher EV fleet size and moderate carbon prices.

Impacts of generation-cycling costs on future electricity generation portfolio investment

This paper assesses the impacts of incorporating short-term generation dispatch into long-term generation portfolio planning frameworks. A case study of a power system with coal, combined cycle gas turbine (CCGT), open cycle gas turbine (OCGT) and wind generation options highlights that incorporating operational criteria into the long-term generation investment and planning analysis can have operating, economic and emissions implications for the different generation portfolios. The extent of the impacts depends on a number of factors including dispatch strategies, carbon price and the mix of technologies within the portfolio. As variable generation within power systems increases and carbon pricing begins to change the merit order, such short-term operational considerations will become more significant for generation investment and planning.

Electricity Generation Portfolio Analysis for Coal, Gas and Nuclear Plant under Future Uncertainties

High and volatile fossil fuel prices, growing concerns over energy security and the risk of climate change have all contributed to revived interest in nuclear power around the world. This is particularly the case in fast developing ASEAN countries. However, there is still considerable uncertainty about the prospects of nuclear power in terms of its economic viability and associated risks given a highly uncertain future energy industry context. This paper employs a stochastic tool based on the Monte Carlo simulation technique to assess the expected generation costs and risk profiles of different electricity generation portfolios of coal, Combined Cycle Gas Turbine (CCGT), and nuclear plants. The tool explicitly incorporates uncertain future fuel and carbon price, and plant capital costs into the analysis. Results from the model enable tradeoffs between expected system generation cost, associated risks and CO2 emissions among generation portfolios to be identified. In this paper the economics of nuclear power in relation to coal and CCGT are evaluated for different portfolio mixes under a number of scenarios of future fuel and carbon prices in the context of the ASEAN region. Results highlight the important role that a carbon price is likely to play in making nuclear power an economic option.

Impact of high variable renewable generation on future market prices and generator revenue

This study assesses the potential impact of high renewable generation on the spot electricity prices, generator revenue and profits in an energy-only electricity market. In particular, it presents modelling outcomes for the Australian National Electricity Market (NEM) with a range of possible renewable penetrations in 2030. It is assumed that the current reliability standard is maintained and participants deploy short run marginal cost bidding. The study found that increasing the share of wind and PV generation would likely result in lower average spot prices and subsequently revenue and profit of generators. The revenue impact on large-scale PV was found to be very severe and could lead to insufficient revenue to cover the costs, particularly at higher renewable penetrations. Changes in market mechanisms, such as increasing the Market Price, may be required to ensure revenue sufficiency and long-term resource adequacy in an energy-only market with high renewables.

Sustainability Challenges for Electricity Industries in ASEAN Newly Industrializing Countries

The region of the Association of Southeast Asian Nations (ASEAN) is one of the fastest developing regions in the world. Strong economic and social development have contributed to rapid growth in electricity consumption within this region, which whilst representing significant societal progress has potentially growing adverse environmental impacts. This study evaluates some key challenges in the electricity industries of five ASEAN newly industrializing countries: Indonesia, Thailand, Malaysia, the Philippines and Vietnam. The framework for this study is the 3A’s energy sustainability objectives: Accessibility, Availability and Acceptability introduced by the World Energy Council. The key sustainability challenges in these countries are generally attributable to satisfying rapid demand growth; enhancing security of electricity supply; and mitigating the increase in CO2 emissions as a result of electricity consumption. We assess the status of the electricity industries in these countries against a range of performance indicators for these challenges. Our study highlights some of the key issues facing governments, the electricity industry and investors, and the need for new decision support tools to guide electricity sector development.

Monte-Carlo based assessments for future generation investment — A case study of Thailand

This paper uses a novel generation investment and planning decision support tool to assess the potential costs of different possible future generation portfolios in Thailand in 2030. These costs are estimated given Thailands existing generation portfolio and presently uncertain future fossil fuel prices, carbon pricing policies, national electricity demand, and plant capital costs. The tool incorporates a Monte Carlo extension to conventional optimal generation mix methods combined with portfolio-based analysis techniques to determine expected industry generation costs, associated cost uncertainties, and CO2 emissions. The case study results show that a future carbon price can play a vital role in reducing industry-wide emissions as well as determining the economic viability of different generation technologies. More generally, the results highlight the value of the tool in facilitating multiple criteria generation investment decision making involving costs, risks, and emissions.