scholarly journals The Long-Term Impact of the Electorate on the Swiss Electricity Market Transition

2021 ◽  
pp. 137-158
Author(s):  
Raphael Klein ◽  
Matthias Finger
Keyword(s):  
Gas Turbine ◽  
Electricity Market ◽  
Power Plants ◽  
Carbon Tax ◽  
Policy Instruments ◽  
Environmentally Conscious ◽  
Policy Actors ◽  
Demand Growth ◽  
Technology Advancement ◽  
Long Term Impact

AbstractThe Swiss government, through its Energy Strategy 2050, is engaged on a path to transition Switzerland to become a carbon-neutral country by the year 2050. In this chapter, we look at the impact that the electorate can have on this transition and on the Swiss electricity market. This is done using hybrid agent-based modelling. We model the Swiss electricity market and we add to this a model of the policy-making process. This allows us to study which policy instruments are more likely to be implemented depending on the Swiss electricity market progression and on the policy actors’ interests. The results have shown that the electorate has a limited impact on the policy chosen and on the electricity market. Overall, an environmentally conscious electorate leads policy actors to select the carbon tax as a policy more often. This, however, has the adverse effect to increase the electricity price and increase import dependency in winter. In high demand growth scenarios, the carbon tax policy is not sufficient to stem the construction of gas turbine power plants. We also show that because the electricity model does not consider an extended demand response option or technology advancement, the knowledge gained from this model is limited. This drives the behaviour of the model into scenarios which are unlikely to happen, such as a large increase of the gas turbine power plants. Overall, we conclude that, in their current form, even with an environmentally conscious electorate, the electricity market conditions do not allow Switzerland to reach its emissions targets.

A New Algorithm for Scheduling Condition-Based Maintenance of Gas Turbines

2015 ◽  
Author(s):  
Yavuz Yılmaz ◽  
Rainer Kurz ◽  
Ayşe Özmen ◽  
Gerhard-Wilhelm Weber
Keyword(s):  
Gas Turbine ◽  
Electricity Markets ◽  
Electricity Market ◽  
Gas Turbines ◽  
Power Plants ◽  
High Efficiency ◽  
Meteorological Data ◽  
Heat Rate ◽  
Extended Period ◽  
Complex Data

In developed electricity markets, the deregulation boosted competition among companies participating in the electricity market. Therefore, the enhanced reliability and availability of gas turbine systems is an industry obligation. Not only providing the available power with minimum operation and maintenance costs, but also guaranteeing high efficiency are additional requisites and efficiency loss of the power plants leads to a loss of money for the electricity generation companies. Multivariate Adaptive Regression Spline (MARS) is a modern methodology of statistical learning, data mining and estimation theory that is significant in both regression and classification is a form of flexible non-parametric regression analysis capable of modeling complex data. In this study, single shaft, 6MW class industrial gas turbines located at various sites have been monitored. The performance monitoring of a gas turbine consisted of hourly measurements of various input variables over an extended period of time. Using such measurements, predictive models for gas turbine heat rate and the gas turbine axial compressor discharge pressure values have been generated. The measured values have been compared with the values obtained as a result of the MARS models. The MARS-based models are obtained with the combination of gas turbine performance input and target variables and the complementary meteorological data. The results are presented, discussed, and conclusions are drawn for modern energy and cost efficient gas turbine and power plant maintenance management as the outcomes of this study.

Economic analysis of a small combined cycle gas turbine power plant in the Italian electricity market

2020 ◽  
pp. 095765092097605
Author(s):  
Dominique Adolfo ◽  
Carlo Carcasci
Keyword(s):  
Gas Turbine ◽  
Electricity Market ◽  
Energy Demand ◽  
Alternative Energy ◽  
Power Plants ◽  
Operation Mode ◽  
Market Price ◽  
Optimal Solution ◽  
Energy System ◽  
Combined Cycle

Despite the availability of new alternative energy sources, growing worldwide energy demand and emissions targets lead power plants to work optimizing performances. In this new scenario in which renewable energies are increasingly taking the field, it is also important to produce energy at a low price. Moreover, the variability of the energy market price complicates the analysis. Comparison between the produced energy cost and the market price is necessary to get a return on investment. In this context, the paper investigates the implications of using a gas turbine in an energy system estimating the plant layout and the number of working hours that guarantees a better profit. The analysis focuses on the study of the start-up and shutdown operation mode to find the optimal solution strategy in the Italian electricity market.

Reliability Index of Wind-Solar Hybrid Power Plants using the Expected Energy Not Supplied Method

2019 ◽  
Vol 8 (4) ◽  
pp. 9449-9456
Keyword(s):  
Power Plant ◽  
Power Systems ◽  
Electricity Market ◽  
Reliability Index ◽  
Power Plants ◽  
Initial Conditions ◽  
Hybrid Plant ◽  
Total Power ◽  
Hybrid Power ◽  
Hybrid Power Plant

This paper proposes the reliability index of wind-solar hybrid power plants using the expected energy not supplied method. The location of this research is wind-solar hybrid power plants Pantai Baru, Bantul, Special Region of Yogyakarta, Indonesia. The method to determine the reliability of the power plant is the expected energy not supplied (EENS) method. This analysis used hybrid plant operational data in 2018. The results of the analysis have been done on the Pantai Baru hybrid power plant about reliability for electric power systems with EENS. The results of this study can be concluded that based on the load duration curve, loads have a load more than the operating kW of the system that is 99 kW. In contrast, the total power contained in the Pantai Baru hybrid power plant is 90 kW. This fact makes the system forced to release the load. The reliability index of the power system in the initial conditions, it produces an EENS value in 2018, resulting in a total value of 2,512% or 449 kW. The EENS value still does not meet the standards set by the National Electricity Market (NEM), which is <0.002% per year. Based on this data, it can be said that the reliability of the New Coast hybrid power generation system in 2018 is in the unreliable category.

scholarly journals Analyzing Trade in Continuous Intra-Day Electricity Market: An Agent-Based Modeling Approach

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3860
Author(s):  
Priyanka Shinde ◽  
Ioannis Boukas ◽  
David Radu ◽  
Miguel Manuel de Manuel de Villena ◽  
Mikael Amelin
Keyword(s):  
Renewable Energy ◽  
Electricity Market ◽  
Power Plants ◽  
Renewable Energy Sources ◽  
Thermal Power ◽  
Agent Based Modeling ◽  
Market Liquidity ◽  
Energy Sources ◽  
Modeling Framework ◽  
Agent Based

In recent years, the vast penetration of renewable energy sources has introduced a large degree of uncertainty into the power system, thus leading to increased trading activity in the continuous intra-day electricity market. In this paper, we propose an agent-based modeling framework to analyze the behavior and the interactions between renewable energy sources, consumers and thermal power plants in the European Continuous Intra-day (CID) market. Additionally, we propose a novel adaptive trading strategy that can be used by the agents that participate in CID market. The agents learn how to adapt their behavior according to the arrival of new information and how to react to changing market conditions by updating their willingness to trade. A comparative analysis was performed to study the behavior of agents when they adopt the proposed strategy as opposed to other benchmark strategies. The effects of unexpected outages and information asymmetry on the market evolution and the market liquidity were also investigated.

scholarly journals Household electricity demand, the intrinsic flexibility index and UK wholesale electricity market prices

2020 ◽  
Author(s):  
Jacopo Torriti
Keyword(s):  
Electricity Market ◽  
Power Plants ◽  
Electricity Demand ◽  
Market Prices ◽  
Vast Number ◽  
Spot Prices ◽  
Time Use Survey ◽  
Wholesale Electricity Market ◽  
The Uk ◽  
Flexibility Index

AbstractDuring peak electricity demand periods, prices in wholesale markets can be up to nine times higher than during off-peak periods. This is because if a vast number of users is consuming electricity at the same time, power plants with higher greenhouse gas emissions and higher system costs are typically activated. In the UK, the residential sector is responsible for about one third of overall electricity demand and up to 60% of peak demand. This paper presents an analysis of the 2014–2015 Office for National Statistics National Time Use Survey with a view to derive an intrinsic flexibility index based on timing of residential electricity demand. It analyses how the intrinsic flexibility varies compared with wholesale electricity market prices. Findings show that spot prices and intrinsic flexibility to shift activities vary harmoniously throughout the day. Reflections are also drawn on the application of this research to work on demand side flexibility.

scholarly journals Decentralized Prosumer-Centric P2P Electricity Market Coordination with Grid Security

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4665
Author(s):  
Duarte Kazacos Winter ◽  
Rahul Khatri ◽  
Michael Schmidt
Keyword(s):  
Electricity Markets ◽  
Electricity Market ◽  
Power Flow ◽  
Power Plants ◽  
Optimal Power Flow ◽  
Free Market ◽  
Economic Value ◽  
New Paradigm ◽  
Grid Security ◽  
Virtual Power Plants

The increasing number of prosumers and the accompanying greater use of decentralised energy resources (DERs) bring new opportunities and challenges for the traditional electricity systems and the electricity markets. Microgrids, virtual power plants (VPPs), peer-to-peer (P2P) trading and federated power plants (FPPs) propose different schemes for prosumer coordination and have the potential of becoming the new paradigm of electricity market and power system operation. This paper proposes a P2P trading scheme for energy communities that negotiates power flows between participating prosumers with insufficient renewable power supply and prosumers with surplus supply in such a way that the community welfare is maximized while avoiding critical grid conditions. For this purpose, the proposed scheme is based on an Optimal Power Flow (OPF) problem with a Multi-Bilateral Economic Dispatch (MBED) formulation as an objective function. The solution is realized in a fully decentralized manner on the basis of the Relaxed Consensus + Innovations (RCI) algorithm. Network security is ensured by a tariff-based system organized by a network agent that makes use of product differentiation capabilities of the RCI algorithm. It is found that the proposed mechanism accurately finds and prevents hazardous network operations, such as over-voltage in grid buses, while successfully providing economic value to prosumers’ renewable generation within the scope of a P2P, free market.

Thermoeconomic optimization of combined cycle gas turbine power plants using genetic algorithms

2003 ◽  
Vol 23 (17) ◽  
pp. 2169-2182 ◽  
Author(s):  
Manuel Valdés ◽  
Ma Dolores Durán ◽  
Antonio Rovira
Keyword(s):  
Genetic Algorithms ◽  
Gas Turbine ◽  
Power Plants ◽  
Combined Cycle
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