1,721,058 research outputs found
Ex-ante market power evaluation and mitigation in day-ahead electricity market considering market maturity levels
No full textMarket power is detrimental to the fair operation of the spot market, thus many market power evaluation and mitigation approaches have been put forward. However, due to the market maturity levels and the approaches themselves, excessive/deficient mitigation or high computational burden for a more accurate evaluation in practice are not rare. Therefore, in this paper, we propose a combined market power evaluation and mitigation framework, based on the emerging electricity day-ahead markets, in which the market power mitigation can be achieved ex-ante to the market clearing and can be flexibly adopted according to the market maturity levels during the development of the markets. More specifically, an ex-ante Customized Market Operation (CMO) indicator is first proposed to evaluate the market power of individual generators. Secondly, based on the CMO and the maturity of the market levels, an optimal CMO threshold is derived through the Best and Worst Method (BWM)-Entropy approach to mitigate the market power via limiting individual generators’ offer coefficients. Finally, the proposed CMO-BWM-Entropy approach is applied to the Chinese electricity markets under different maturity levels. Our results indicate that the accuracy of market power mitigation, quantified by the Lerner index, is 10 times higher than other existing ex-ante market power mitigation approaches, and the computational efficiency is 50 times faster than the compared ones
Remote Hardware-In-the-Loop Measurement System for Electrolyser Characterization
Full text linkThe installation of facilities replicating the real-world condition is often required for carrying out meaningful tests on new devices and for collecting data with the aim to create realistic device model. However, these facilities require huge investments, as well as areas where they can be properly installed. In this paper, we present a test infrastruc- ture exploiting the concept of Remote Power Hardware-In-the-Loop (RPHIL), applied for characterizing the performances of a 8kW Pro- ton Exchange Membrane (PEM) electrolyser installed at the Hanze University of Applied Sciences in Groningen (The Netherlands). The electrolyser is subjected to dierent test conditions imposed both lo- cally and remotely. The results show that this measurement procedure is eective and can open new perspectives in the way to share and exploit the existing research infrastructure in Europe
Predictive methods of electricity price: An application to the Italian electricity market
Full text linkPrice forecasting is a crucial element for the members of the electricity markets and business decision making to maximize their profits. The electricity prices have an impact on the behavior of market participants, and thus, predicting prices for generation companies, and consumers is essential for both the short-term profits in the Day-Ahead, Intra-Day and Ancillary markets, and the long-term benefits in the future planning, investment, and risk management. Therefore, participants in the electricity market need to accurately and effectively predict the price signal to manage market risk. In this paper, different forecasting models have been compared, and the most promising ones have been employed to forecast the short term Italian electricity market clearing price for achieving forecasting accuracy. In particular, simulations are performed for four principal regression methods, including Support Vector Machine, Gaussian Processes Regression, Regression Trees, and Multi-Layer Perceptron. The performance of predicted models is compared through several performance metrics, including MAE, RMSE, R, and the total number of percentage error anomalies. The results indicate the SVM is the best choice for forecasting the electricity market price on the Italian case study
An extended metric for the analysis of power-network vulnerability: The line electrical centrality
No full textPower networks are highly vulnerable to deliberate attacks. Whilst power-network design usually considers the protection of the system against network-component failure, it does not consider the protection against deliberated attacks. The inclusion of deliberated-attack analyses with traditional power-system methods may results in computational-intensive models. However, the introduction of complex-network methods in the analysis of power systems will support vulnerability studies by reducing their computational burden. Extended topological metrics, which endows topological metrics with electrical considerations, have resulted to give satisfactory results with lower computational requirements. This paper proposes a new extended metric to rank lines according to the impact that line failures have on power networks. The proposed metric is based on the idea of betweenness centrality and it considers parameters related to demand, generation and transmission lines. This paper confirms the accuracy of the proposed metric with two test cases
Multi-Agent Models for Consumer Choice and Retailer Strategies in the Competitive Electricity Market
No full textThe demand elasticity impacts on the strategic bidding behavior of the electricity producers
No full textThe impacts of price responsiveness on strategic equilibrium in competitive electricity markets
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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