scholarly journals Decision-Making Support Methods, Algorithms and Tools for Electricity Market Participants

2020 ◽  
Author(s):  
◽  
Kārlis Baltputnis
Keyword(s):  
Decision Making ◽  
Power Plant ◽  
Electricity Market ◽  
Large Scale ◽  
Demand Forecasting ◽  
Combined Heat And Power ◽  
Market Participants ◽  
Hydropower Plants ◽  
Storage Technologies ◽  
Support Methods

Electricity market participants need to optimize their processes to avoid being outcompeted by other traders. Consequently, decision-making methods, algorithms and tools related to large-scale energy storage technologies (scheduling, sizing) and cascaded hydropower plants (scheduling, hydroelectric set selection), as well as heating demand forecasting, which is a prerequisite for efficient combined heat and power plant participation in an electricity market.

scholarly journals Long-Term Generation Scheduling for Cascade Hydropower Plants Considering Price Correlation between Multiple Markets

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2239
Author(s):  
Bin Luo ◽  
Shumin Miao ◽  
Chuntian Cheng ◽  
Yi Lei ◽  
Gang Chen ◽  
...  
Keyword(s):  
Electricity Market ◽  
Large Scale ◽  
Copula Function ◽  
Market Environment ◽  
Scheduling Model ◽  
Multiple Markets ◽  
Generation Scheduling ◽  
Hydropower Plants ◽  
Proposed Model

The large-scale cascade hydropower plants in southwestern China now challenge a multi-market environment in the new round of electricity market reform. They not only have to supply the load for the local provincial market, but also need to deliver electricity to the central and eastern load centers in external markets, which makes the generation scheduling much more complicated, with a correlated uncertain market environment. Considering the uncertainty of prices and correlation between multiple markets, this paper has proposed a novel optimization model of long-term generation scheduling for cascade hydropower plants in multiple markets to seek for the maximization of overall benefits. The Copula function is introduced to describe the correlation of stochastic prices between multiple markets. The price scenarios that obey the Copula fitting function are then generated and further reduced by using a scenario reduction strategy that combines hierarchical clustering and inconsistent values. The proposed model is applied to perform the long-term generation scheduling for the Wu River cascade hydropower plants and achieves an increase of 106.93 million yuan of annual income compared with the conventional scheduling model, without considering price scenarios, showing better performance in effectiveness and robustness in multiple markets.

scholarly journals Spatial-Economic Potential Analysis of Wind Power Plants in Germany

Wind ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 77-89
Author(s):  
David Hennecke ◽  
Carsten Croonenbroeck
Keyword(s):  
Power Plant ◽  
Wind Power ◽  
Electricity Market ◽  
Regional Planning ◽  
Power Plants ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Levelized Cost Of Electricity ◽  
Potential Analysis ◽  
Federal States

Before a new wind farm can be built, politics and regional planning must approve of the respective area as a suitable site. For this purpose, large-scale potential computations were carried out to identify suitable areas. The calculation of wind power plant potential usually focuses on capturing the highest energy potential. In Germany, due to an energy production reimbursement factor defined in the Renewable Energy Sources Act (“Erneuerbare-Energien-Gesetz”, EEG) in 2017, the influence of energy quantities on the power plant potential varies, economically and spatially. Therefore, in addition to the calculation of energy potentials, it was also necessary to perform a potential analysis in terms of economic efficiency. This allows, on the one hand, an economic review of the areas tendered by the regional planning and, on the other hand, a spatial-economic analysis that expands the parameters in the search for new areas. In this work, (a) potentials with regard to the levelized cost of electricity (LCOE) were calculated by the example of the electricity market in Germany, which were then (b) spatially and statistically processed on the level of the federal states.

scholarly journals Clustering time series applied to energy markets

2019 ◽  
Vol 2 (S1) ◽  
Author(s):  
Cornelia Krome ◽  
Jan Höft ◽  
Volker Sander
Keyword(s):  
Time Series ◽  
Power Plant ◽  
Electricity Market ◽  
Power Plants ◽  
Large Scale ◽  
Energy Systems ◽  
Weather Data ◽  
Virtual Power ◽  
Virtual Power Plant ◽  
Virtual Power Plants

Abstract In Germany and many other countries the energy market has been subject to significant changes. Instead of only a few large-scale producers that serve aggregated consumers, a shift towards regenerative energy sources is taking place. Energy systems are increasingly being made more flexible by decentralised producers and storage facilities, i.e. many consumers are also producers. The aggregation of producers form another type of power plants: a virtual power plant. On the basis of aggregated production and consumption, virtual power plants try to make decisions under the conditions of the electricity market or the grid condition. They are influenced by many different aspects. These include the current feed-in, weather data, or the demands of the consumers. Clearly, a virtual power plant is focusing on developing strategies to influence and optimise these factors. To accomplish this, many data sets can and should be analysed in order to interpret and create forecasts for energy systems. Time series based analytics are therefore of particular interest for virtual power plants. Classifying the different time series according to generators, consumers or customer types simplifies processes. In this way, scalable solutions for forecasts can be found. However, one has to first find the according clusters efficiently. This paper presents a method for determining clusters of time series. Models are adapted and model-based clustered using ARIMA parameters and an individual quality measure. In this way, the analysis of generic time series can be simplified and additional statements can be made with the help of graphical evaluations. To facilitate large scale virtual power plants, the presented clustering workflow is prepared to be applied on big data capable platforms, e.g. time series stored in Apache Cassandra, analysed through an Apache Spark execution framework. The procedure is shown here using the example of the Day-Ahead prices of the electricity market for 2018.

A computational intelligence based approach for optimized operation scheduling of energy plants

2020 ◽  
Vol 68 (2) ◽  
pp. 118-129
Author(s):  
Johannes Mast ◽  
Stefan Rädle ◽  
Joachim Gerlach ◽  
Oliver Bringmann
Keyword(s):  
Simulated Annealing ◽  
Power Plant ◽  
Computational Intelligence ◽  
Electricity Market ◽  
Operating Mode ◽  
Combined Heat And Power ◽  
Operation Planning ◽  
Operation Schedule ◽  
Operation Scheduling ◽  
Energy Plants

AbstractThis paper describes a methodology for optimizing the operation schedule of energy plants, which is exemplarily applied for a combined heat and power plant and a heat pump. The methodology is based on the computational intelligence algorithms Ant Colony Optimization and Simulated Annealing and allows a customized description of the optimization objective. This is demonstrated by several optimization objectives that have been considered, such as the price on the electricity market. The methodology replaces a conventional, guided operating mode of the system with an intelligent, prognostic-based operation planning. In this way, the systems can be operated more economically and/or more sustainably.

scholarly journals Policy Implications of Power Exchanges on Operational Scheduling: Evaluating EUPHEMIA’s Market Products in Case of Greece

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2715 ◽  
Author(s):  
Nikolaos Koltsaklis ◽  
Athanasios Dagoumas
Keyword(s):  
Decision Making ◽  
Electricity Market ◽  
Relevant Literature ◽  
Policy Implications ◽  
Research Centre ◽  
Variable Cost ◽  
Wholesale Market ◽  
Joint Research ◽  
Market Participants ◽  
The Impact

A vital component for the development of a functioning internal electricity market is the adoption by each European member state of the Pan-European Hybrid Electricity Market Integration (EUPHEMIA) for the day-ahead market solution. The consideration of the national power market’s characteristics enables more realistic market design towards the implementation of the so-called “Target Model”. This work considers a series of factors, including the EUPHEMIA order types, their use by market participants, the relative competitiveness of power generators, the impact of interconnected markets, the existence of market players with dominant positions, and the existence of specific regulations such as the minimum average variable cost restriction on offers by producers, as well as the strategy adopted by market participants. The main goal of this paper is to provide a comprehensive analysis on the adoption of EUPHEMIA’s algorithm in case of the Greek wholesale market, based on a relevant research project funded by the Joint Research Centre of the European Commission to support the Hellenic Regulatory Authority of Energy on its decision-making. The paper contributes to the relevant literature on the quantification of the impacts of the EUPHEMIA algorithm in the case of the Greek wholesale market, providing insights on the crucial aspects affecting realistic, market-based decision-making.

scholarly journals Dynamic Modelling and Techno-Economic Assessment of a Compressed Heat Energy Storage System: Application in a 26-MW Wind Farm in Spain

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4739 ◽  
Author(s):  
Violeta Sánchez-Canales ◽  
Jorge Payá ◽  
José M. Corberán ◽  
Abdelrahman H. Hassan
Keyword(s):  
Energy Storage ◽  
Power Plant ◽  
Electricity Market ◽  
Large Scale ◽  
Storage Systems ◽  
Capital Expenditure ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Dynamic Modelling ◽  
Heat Energy

One of the main challenges for a further integration of renewable energy sources in the electricity grid is the development of large-scale energy storage systems to overcome their intermittency. This paper presents the concept named CHEST (Compressed Heat Energy STorage), in which the excess electricity is employed to increase the temperature of a heat source by means of a high-temperature heat pump. This heat is stored in a combination of latent and sensible heat storage systems. Later, the stored heat is used to drive an organic Rankine cycle, and hereby to produce electricity when needed. A novel application of this storage system is presented by exploring its potential integration in the Spanish technical constraints electricity market. A detailed dynamic model of the proposed CHEST system was developed and applied to a case study of a 26-MW wind power plant in Spain. Different capacities of the storage system were assessed for the case under study. The results show that roundtrip efficiencies above 90% can be achieved in all the simulated scenarios and that the CHEST system can provide from 1% to 20% of the total energy contribution of the power plant, depending on its size. The CHEST concept could be economically feasible if its capital expenditure (CAPEX) ranges between 200 and 650 k€/MW.

scholarly journals MOTOR BIOFUEL-POWERED CHP PLANTS—A STEP TOWARDS SUSTAINABLE DEVELOPMENT OF RURAL LITHUANIA

2011 ◽  
Vol 17 (1) ◽  
pp. 189-205 ◽  
Author(s):  
Laurencas Raslavičius ◽  
Anicetas Strakšas
Keyword(s):  
Sustainable Development ◽  
Power Plant ◽  
European Commission ◽  
Rapeseed Oil ◽  
Large Scale ◽  
Power Production ◽  
Combined Heat And Power ◽  
Liquid Fuels ◽  
Small Scale ◽  
Economic Aspects

This paper focuses on the benefits that can be attained from the correct option of small-scale combined heat and power plant (CHP) relative to fuel availability and sphere of application. The analysis serves as a means of highlighting some of the owners of large-scale farms as well as holders of industrial greenhouses that influence the penetration of small-scale cogeneration plants running on bio-based liquid fuels. The identification of the main influencing factors and their weight is the first step towards the implementation of a more coherent strategy, if the EC (European Commission) and national energy authorities wish for new small-scale cogeneration technologies to have a future in the context of sustainable development of rural Lithuania. Against this background, this paper aims at presenting the technical, environmental and economic aspects of the possibilities of utilizing biodiesel, biodiesel-conventional diesel blends and rapeseed oil in combined heat and power production as an issue for further discussions regarding the formative breakthrough attitude towards a possible path of country's sustainable development.

Sign in / Sign up

Export Citation Format

Share Document