Optimisation of electricity energy markets and assessment of CO2 trading on their structure : a stochastic analysis of the greek power sector

Power production was traditionally dominated by monopolies. After a long period of research and organisational advances in international level, electricity markets have been deregulated allowing customers to choose their provider and new producers to compete the former Public Power Companies. Vast changes have been made in the European legal framework but still, the experience gathered is not sufficient to derive safe conclusions regarding the efficiency and reliability of deregulation. Furthermore, emissions' trading progressively becomes a reality in many respects, compliance with Kyoto protocol's targets is a necessity, and stability of the national grid's operation is a constraint of vital importance. Consequently, the production of electricity should not rely solely in conventional energy sources neither in renewable ones but on a mixed structure. Finding this optimal mix is the primary objective of the study. A computational tool has been created, that simulates and optimises the future electricity generation structure based on existing as well as on emerging technologies. The results focus on the Greek Power Sector and indicate a gradual decreasing of anticipated CO2 emissions while the socioeconomic constraints and reliability requirements of the system are met. Policy interventions are pointed out based on the numerical results of the model. (C) 2010 Elsevier Ltd. All rights reserved

FROM MARKET UNCERTAINTY TO POLICY UNCERTAINTY FOR INVESTMENT IN POWER GENERATION: REAL OPTIONS FOR NPP ON ELECTRICITY MARKET

In the electricity sector, market participants must make decisions about capacity choice in a situation of radical uncertainty about future market conditions. Sector is characterized by non-storability and periodic and stochastic demand fluctuations. Capacity determination is a decision for the long term, whereas production is adjusted in the short run. Paper looks on the main contributions in investment planning under uncertainty, in particular in the electricity market for capital intensive investments like NPP. The relationship between market and nonmarket factors (recent UK policy example) in determining investment signals in competitive electricity markets was analysed. Paper analyse the ability of competitive electricity markets to deliver the desired quantity and type of generation capacity and also investigates the variety of market imperfections operating in electricity generation and their impact on long-term dynamics for generation capacity. Paper analyses how price formation influences investment signals. Number of factors (including market power, wholesale price volatility, lack Ž. Tomšić, From market uncertainty to policy uncertainty for investment in power generation: real options for NPP on electricity market, Journal of Energy, vol. 64 (2015) Special Issue, p. 178-197 of liquidity in the wholesale and financial market, policy and regulatory risks etc.) contribute to polluting the price signal and generating sub-optimal behaviour

Deregulation and environmental differentiation in the electric utility industry.

This paper analyzes how economic deregulation impacts firm strategies and environmental quality in the electric utility industry. We find evidence that the deregulation introduced to this historically staid industry has stimulated environmental differentiation. Differentiation is most likely to appear where its point of uniqueness is valued by customers, and we confirm this relationship in our sample. Specifically, utilities that served customers who exhibited higher levels of environmental sensitivity generated more green power. The tendency for firms to differentiate in this way is lessened if they are relatively more dependent on coal-fired generation or relatively more efficient. Thus, there is evidence that firms sort themselves into either differentiation or low-cost strategies as the competitive realities of a deregulated world unfold. Deregulation and the ensuing environmental differentiation illustrate how utilities exploited formerly unmet customer demand for green power. The result has been greater levels of renewable generation and, hence, a cleaner environment.Deregulation; Environmental differentiation; Electric utility; Renewable energy; Productive efficiency;

State-of-the-art research : optimal investment in market-based electric power systems

The purpose of this state-of-the-art research paper is to surveying the literature on investment in market based electric power systems as a background for identifying and discussing some important issues in the optimal design and operation of such systems. A fundamental distinction has to be made between investment in the competitive part of the power system (generation and trading) on the one hand and the natural monopoly part (network infrastructure) on the other. The paper starts with a listing and discussion on market characteristics and properties of electric power and goes on to discussing performance criteria and potential sources of market failure for optimal electric power investment. After the literature survey there is a discussion of conditions under which optimal investment may occur

Market and Economic Modelling of the Intelligent Grid: End of Year Report 2009

The overall goal of Project 2 has been to provide a comprehensive understanding of the impacts of distributed energy (DG) on the Australian Electricity System. The research team at the UQ Energy Economics and Management Group (EEMG) has constructed a variety of sophisticated models to analyse the various impacts of significant increases in DG. These models stress that the spatial configuration of the grid really matters - this has tended to be neglected in economic discussions of the costs of DG relative to conventional, centralized power generation. The modelling also makes it clear that efficient storage systems will often be critical in solving transient stability problems on the grid as we move to the greater provision of renewable DG. We show that DG can help to defer of transmission investments in certain conditions. The existing grid structure was constructed with different priorities in mind and we show that its replacement can come at a prohibitive cost unless the capability of the local grid to accommodate DG is assessed very carefully.Distributed Generation. Energy Economics, Electricity Markets, Renewable Energy

Residential distributed generation : decision support software to evaluate opportunities in the residential market : a thesis submitted in partial fulfilment of the requirement for the degree of Masters of Engineering at Massey University, Palmerston North, New Zealand /

The residential market in New Zealand consumes a significant proportion of our electricity production and is one of the fastest growing sectors. As a vertically integrated generator retailer in the New Zealand electricity industry, Meridian Energy Ltd is concerned at retaining and growing their customer base. They recognise that utilisation of emerging distributed generation [DG] technologies can provide a competitive advantage in the market place. A decision tool was developed to help Meridian identify opportunities within the residential market for applications of DG. The model compares the cost to serve a household's energy needs using a business as usual case with a DG case on an annual basis for a single household or a neighbourhood. A modular approach was used for ease of development and to enable future enhancements. The main modules were: load profile development, DG technology, operation control, costing and a calculation engine. The load profile module estimated space heating/cooling, water heating and other electrical loads for each 30 minute period for 8 representative days of a year based on national end-use statistics and a set of 40 reference profiles. A Gamma distribution was used to simulate diversity between houses. The calculation engine computed the amount of demand that could be met by the DG technologies and hence the residual demand or surplus for export. The pricing module estimated the annual cost including aspects such as: capital cost, fuel cost, maintenance, value of export and cost of import. The technology modules allowed different DG technologies, as well as a range of parameters to be selected. It included renewable energy resource modelling. The performance module allowed different operation control of the heat engine technologies including: base load, electrical peaking, heat peaking, load following (heat-led) and load following(electricity-led). The model was implemented using Microsoft Visual Basic for Applications, in Excel. A series of user-forms were developed to enable the model to be run with a minimum of user input. Three case studies were undertaken. In the first, five technology types were modelled, with the heat pump and Stirling engine looking the most promising. The second case study involved these two technologies in a Christchurch urban area study. A hypothetical network analysis showed the benefit that these technologies could have in reducing peak loading on the network. The third case study examined the sensitivity of the results to the value of specific variables. Load size and capital cost had the strongest influence on NPV