Optimum production plans for thermal power plants in the deregulated electricity market

Energy ◽  
2006 ◽  
Vol 31 (10-11) ◽  
pp. 1567-1585 ◽  
Author(s):  
Andrea Lazzaretto ◽  
Cristian Carraretto
Keyword(s):  
Electricity Market ◽  
Power Plants ◽  
Thermal Power ◽  
Thermal Power Plants ◽  
Deregulated Electricity Market ◽  
Production Plans ◽  
Optimum Production

Synthesis of the Algorithm for Control of the Thermal Power Plant Generating Equipment Based on System Dynamics Models

2021 ◽  
Vol 22 (1) ◽  
pp. 20-27
Author(s):  
I. N. Fomin ◽  
T. E. Shulga ◽  
V. A. Ivaschenko
Keyword(s):  
System Dynamics ◽  
Economic System ◽  
Electricity Market ◽  
Power Plants ◽  
Thermal Power ◽  
Thermal Power Plants ◽  
Mathematical Apparatus ◽  
Wholesale Electricity Market ◽  
Generating Equipment ◽  
Technical And Economic Indicators

The article discusses an original solution for designing an algorithm for selecting the most optimal technical and economic indicators for the operation of generating equipment of thermal power plants, taking into account the requirements of the wholesale electricity market, the day-ahead market and the balancing market. To design an algorithm for controlling generating equipment, the activity of a generating company in the wholesale electricity market was considered in terms of system dynamics. The proposed solution made it possible to select and interpret the state variables of the model, build flow diagrams describing the functioning of a technical-economic system, and visualize cause-and-effect relationships in the form of structured functional dependencies. In this work according to the norms of industry legislation and previously conducted scientific research the most important parameters were identified that form the flows of a dynamic technical and economic system, which are optimization criteria in fact. On the basis of this data, a stream stratification of the production processes of generating companies was carried out and a complex of mathematical models of system dynamics was developed to determine and plan the financial efficiency of the operation of thermal power plants and generating companies. The mathematical apparatus and the algorithm of its functioning are developed on the basis of the digraph of cause-and-effect relationships between the investigated technical and economic indicators. On the basis of the graph of interrelationships of system variables, a system of nonlinear differential equations has been built, which makes it possible to determine planned performance indicators when various technical and economic conditions change. The novelty of the proposed approach is the use of new model solutions based on the mathematical apparatus of system dynamics to represent the proposed model in simulation systems, in industry ERP and MES systems, for the development of DDS.

Optimization of Thermal Power Plants Operation in the German De-Regulated Electricity Market Using Dynamic Programming

2012 ◽  
Author(s):  
G. Scarabello ◽  
S. Rech ◽  
A. Lazzaretto ◽  
A. Christidis ◽  
G. Tsatsaronis
Keyword(s):  
Electricity Market ◽  
Power Plants ◽  
Thermal Power ◽  
Optimal Operation ◽  
Renewable Energies ◽  
Combined Cycle ◽  
Mixed Integer ◽  
Programming Approach ◽  
Thermal Power Plants ◽  
Spot Prices

The prospect of clean electrical energy generation has recently driven to massive investments on renewable energies, which in turn has affected operation and profits of existing traditional thermal power plants. In this work several coal-fired and combined cycle power units are simulated under design and off-design conditions to adequately represent the behavior of all modern thermal units included in the German power system. A dynamic optimization problem is then solved to estimate the short-run profits obtained by these units using the spot prices of the German electricity market (EEX) in years 2007–2010. The optimization model is developed using a Mixed Integer Linear Programming approach to take the on-off status into account and reduce computational effort. New market scenarios with increasing renewable shares (and consequently different spot prices) are finally simulated to analyze the consequences of a larger capacity of renewable energies on the optimal operation of traditional thermal power plants.

Solar thermal power plants for the Spanish electricity market

2007 ◽  
Vol 5 (3) ◽  
pp. 261 ◽  
Author(s):  
M. Eck ◽  
F. Rueda ◽  
S. Kronshage ◽  
C. Schillings ◽  
F. Trieb ◽  
...  
Keyword(s):  
Electricity Market ◽  
Power Plants ◽  
Thermal Power ◽  
Solar Thermal ◽  
Thermal Power Plants ◽  
Solar Thermal Power

Price forecast valuation for the NYISO electricity market

Kybernetes ◽  
2015 ◽  
Vol 44 (4) ◽  
pp. 490-504
Author(s):  
Pawel Kalczynski ◽  
Dawit Zerom
Keyword(s):  
Electricity Markets ◽  
Electricity Market ◽  
Power Plants ◽  
Thermal Power ◽  
Electricity Price ◽  
Thermal Power Plants ◽  
Content Type ◽  
Price Forecast ◽  
Statistical Measures ◽  
Forecast Models

Purpose – Following the deregulation of electricity markets in the USA, independent power producers operate as for-profit entities. Their profit depends on the price of electricity and an accurate forecast is critical in making bidding decisions on the electricity and reserve markets or engaging in bilateral contracts. Competing price forecasts have their accuracy expressed in statistical terms but producers need to determine the long-term value of using a given forecast. The purpose of this paper is to address this issue by presenting a method of electricity price forecast valuation which compares forecast models using financial rather than statistical measures. Design/methodology/approach – The objectives of this paper are achieved by mathematical modeling of thermal power plants and price forecast information available to market participants and simulating the operation of a thermal power plant using various price forecasts and perfect information (as a baseline). The operating profit calculated over a long period was used for ranking forecast models. Findings – The framework can be used to estimate the value of a new price forecast as well as to determine if potential gains from developing or acquiring a new forecast will justify the expenses. The results show that an improvement in terms of statistical forecast accuracy measures does not guarantee increased profit. Practical implications – This paper presents a new method for comparing electricity price forecast models. It can be adapted to various types of thermal power plants that operate on liberalized electricity markets and utilize price-based dynamic economic dispatch models. Originality/value – This paper presents a simulation-based valuation framework for short-term electricity price. The approach described in this paper can be utilized by independent power producers for different types of generators, operating on deregulated electricity markets.

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