scholarly journals Impact of Flow Based Market Coupling on the European Electricity Markets

2021 ◽  
Author(s):  
Rafael Finck
Keyword(s):  
Electricity Markets ◽  
Electricity Market ◽  
Western Europe ◽  
Energy System ◽  
Core Region ◽  
Market Prices ◽  
Coupling Constraints ◽  
Net Export ◽  
The Impact ◽  
Market Coupling

AbstractFlow Based Market Coupling is the target model for determining exchange capacities in the internal European Electricity Market. It has been in operation in Central Western Europe since 2015 and is scheduled to be extended to the wider Core region in the near future. Exchange capacities have a significant impact on market prices, exchanges and the energy mix, thus also determining the CO$${}_{2}$$ 2 footprint of electricity generation in the system. Stakeholders therefore need to develop an understanding for the impact of Flow Based Market Coupling and the parameter choice, like the minimum exchange capacities introduced in 2020, on the market outcome. This article presents a framework to model Flow Based Market Coupling and analyse the impact of different levels of regulatory induced minimum trading capacities as well as the effect of the extension towards the Core region. Electricity prices, exchange positions and the number and nature of binding constraints in the market results under different market coupling scenarios are investigated. The results show that increased level of minimum trading capacities in CWE market coupling decrease the German net export position by up to 7 TW h or 23%, while French exports increase by up to 10 TW h or 9%. The different transfer capacity in the scenarios induce a price difference of up to 13%. Increased exchange capacities allow for more base load generation with the corresponding effects for the CO$${}_{2}$$ 2 emissions of the system. The nature of coupling constraints is highly dynamic and dependent on the system state, which makes the suitability of static NTC values in energy system scenarios questionable.

scholarly journals Considerations Regarding the Negative Prices on the Electricity Market

Proceedings ◽  
2020 ◽  
Vol 63 (1) ◽  
pp. 26
Author(s):  
Pavel Atănăsoae ◽  
Radu Dumitru Pentiuc ◽  
Eugen Hopulele
Keyword(s):  
Renewable Energy ◽  
Electricity Markets ◽  
Electricity Market ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Electricity Prices ◽  
Market Areas ◽  
The Impact ◽  
Market Coupling

Increasing of intermittent production from renewable energy sources significantly affects the distribution of electricity prices. In this paper, we analyze the impact of renewable energy sources on the formation of electricity prices on the Day-Ahead Market (DAM). The case of the 4M Market Coupling Project is analyzed: Czech-Slovak-Hungarian-Romanian market areas. As a result of the coupling of electricity markets and the increasing share of renewable energy sources, different situations have been identified in which prices are very volatile.

scholarly journals Changing the Day-Ahead Gate Closure to Wind Power Integration: A Simulation-Based Study

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2765 ◽  
Author(s):  
Hugo Algarvio ◽  
António Couto ◽  
Fernando Lopes ◽  
Ana Estanqueiro
Keyword(s):  
Wind Power ◽  
Electricity Markets ◽  
Electricity Market ◽  
Energy System ◽  
Market Outcomes ◽  
Time Operation ◽  
Wind Power Forecast ◽  
Simulation Based ◽  
Real Time Operation ◽  
The Impact

Currently, in most European electricity markets, power bids are based on forecasts performed 12 to 36 hours ahead. Actual wind power forecast systems still lead to large errors, which may strongly impact electricity market outcomes. Accordingly, this article analyzes the impact of the wind power forecast uncertainty and the change of the day-ahead market gate closure on both the market-clearing prices and the outcomes of the balancing market. To this end, it presents a simulation-based study conducted with the help of an agent-based tool, called MATREM. The results support the following conclusion: a change in the gate closure to a time closer to real-time operation is beneficial to market participants and the energy system generally.

scholarly journals A Hybrid Energy System Workflow for Energy Portfolio Optimization

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4392
Author(s):  
Jia Zhou ◽  
Hany Abdel-Khalik ◽  
Paul Talbot ◽  
Cristian Rabiti
Keyword(s):  
Time Series ◽  
Gaussian Process ◽  
Electricity Market ◽  
Process Model ◽  
Net Present Value ◽  
Historical Data ◽  
Energy System ◽  
Initial Guess ◽  
Reduced Order ◽  
The Impact

This manuscript develops a workflow, driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System. The goal is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, gas, wind and solar). A stochastic-based optimizer is employed, based on Gaussian Process Modeling, which requires numerous samples for its training. Each sample represents a time series describing the demand, load, or other operational and economic profiles for various types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads a limited set of historical data, such as demand and load data from past years. Numerous data analysis methods are employed to construct the reduced order models, including, for example, the Auto Regressive Moving Average, Fourier series decomposition, and the peak detection algorithm. All these algorithms are designed to detrend the data and extract features that can be employed to generate synthetic time histories that preserve the statistical properties of the original limited historical data. The optimization cost function is based on an economic model that assesses the effective cost of energy based on two figures of merit: the specific cash flow stream for each energy producer and the total Net Present Value. An initial guess for the optimal capacities is obtained using the screening curve method. The results of the Gaussian Process model-based optimization are assessed using an exhaustive Monte Carlo search, with the results indicating reasonable optimization results. The workflow has been implemented inside the Idaho National Laboratory’s Risk Analysis and Virtual Environment (RAVEN) framework. The main contribution of this study addresses several challenges in the current optimization methods of the energy portfolios in IES: First, the feasibility of generating the synthetic time series of the periodic peak data; Second, the computational burden of the conventional stochastic optimization of the energy portfolio, associated with the need for repeated executions of system models; Third, the inadequacies of previous studies in terms of the comparisons of the impact of the economic parameters. The proposed workflow can provide a scientifically defendable strategy to support decision-making in the electricity market and to help energy distributors develop a better understanding of the performance of integrated energy systems.

scholarly journals Investment Incentives in Competitive Electricity Markets

2018 ◽  
Vol 8 (10) ◽  
pp. 1978 ◽  
Author(s):  
Jaber Valinejad ◽  
Taghi Barforoshi ◽  
Mousa Marzband ◽  
Edris Pouresmaeil ◽  
Radu Godina ◽  
...  
Keyword(s):  
Electricity Markets ◽  
Electricity Market ◽  
Planning Horizon ◽  
Optimization Method ◽  
Design Criterion ◽  
Mixed Integer ◽  
Investment Incentives ◽  
Mixed Integer Linear Program ◽  
Interconnected Power System ◽  
The Impact

This paper presents the analysis of a novel framework of study and the impact of different market design criterion for the generation expansion planning (GEP) in competitive electricity market incentives, under variable uncertainties in a single year horizon. As investment incentives conventionally consist of firm contracts and capacity payments, in this study, the electricity generation investment problem is considered from a strategic generation company (GENCO) ′ s perspective, modelled as a bi-level optimization method. The first-level includes decision steps related to investment incentives to maximize the total profit in the planning horizon. The second-level includes optimization steps focusing on maximizing social welfare when the electricity market is regulated for the current horizon. In addition, variable uncertainties, on offering and investment, are modelled using set of different scenarios. The bi-level optimization problem is then converted to a single-level problem and then represented as a mixed integer linear program (MILP) after linearization. The efficiency of the proposed framework is assessed on the MAZANDARAN regional electric company (MREC) transmission network, integral to IRAN interconnected power system for both elastic and inelastic demands. Simulations show the significance of optimizing the firm contract and the capacity payment that encourages the generation investment for peak technology and improves long-term stability of electricity markets.

scholarly journals Operational Planning and Bidding for District Heating Systems with Uncertain Renewable Energy Production

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3310 ◽  
Author(s):  
Ignacio Blanco ◽  
Daniela Guericke ◽  
Anders Andersen ◽  
Henrik Madsen
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Power System ◽  
Electricity Markets ◽  
Electricity Market ◽  
Renewable Energy Sources ◽  
District Heating ◽  
Operational Planning ◽  
Solution Approach ◽  
The Impact

In countries with an extended use of district heating (DH), the integrated operation of DH and power systems can increase the flexibility of the power system, achieving a higher integration of renewable energy sources (RES). DH operators can not only provide flexibility to the power system by acting on the electricity market, but also profit from the situation to lower the overall system cost. However, the operational planning and bidding includes several uncertain components at the time of planning: electricity prices as well as heat and power production from RES. In this publication, we propose a planning method based on stochastic programming that supports DH operators by scheduling the production and creating bids for the day-ahead and balancing electricity markets. We apply our solution approach to a real case study in Denmark and perform an extensive analysis of the production and trading behavior of the DH system. The analysis provides insights on system costs, how DH system can provide regulating power, and the impact of RES on the planning.

Measuring the Benefits of Greater Spatial Granularity in Short-Term Pricing in Wholesale Electricity Markets

2011 ◽  
Vol 101 (3) ◽  
pp. 247-252 ◽  
Author(s):  
Frank A Wolak
Keyword(s):  
Natural Gas ◽  
Electricity Markets ◽  
Electricity Market ◽  
Short Term ◽  
Locational Marginal Pricing ◽  
Marginal Pricing ◽  
Before And After ◽  
Natural Gas Prices ◽  
The Impact ◽  
Generation Unit

Hourly generation unit-level output levels, detailed information on the technological characteristics of generation units, and daily delivered natural gas prices to all generation units for the California wholesale electricity market before and after the implementation of locational marginal pricing are used to measure the impact of introducing greater spatial granularity in short-term energy pricing. The average hourly number of generation unit starts increases, but both the total hourly energy consumed and total hourly operating costs for all natural gas-fired generation units fall by more than 2 percent after the implementation of locational marginal pricing.

scholarly journals North–south polarization of European electricity consumption under future warming

2017 ◽  
Vol 114 (38) ◽  
pp. E7910-E7918 ◽  
Author(s):  
Leonie Wenz ◽  
Anders Levermann ◽  
Maximilian Auffhammer
Keyword(s):  
Climate Change ◽  
Dose Response ◽  
Electricity Market ◽  
Western Europe ◽  
Peak Load ◽  
Electricity Consumption ◽  
Total Consumption ◽  
Electric Sector ◽  
Future Warming ◽  
The Impact

There is growing empirical evidence that anthropogenic climate change will substantially affect the electric sector. Impacts will stem both from the supply side—through the mitigation of greenhouse gases—and from the demand side—through adaptive responses to a changing environment. Here we provide evidence of a polarization of both peak load and overall electricity consumption under future warming for the world’s third-largest electricity market—the 35 countries of Europe. We statistically estimate country-level dose–response functions between daily peak/total electricity load and ambient temperature for the period 2006–2012. After removing the impact of nontemperature confounders and normalizing the residual load data for each country, we estimate a common dose–response function, which we use to compute national electricity loads for temperatures that lie outside each country’s currently observed temperature range. To this end, we impose end-of-century climate on today’s European economies following three different greenhouse-gas concentration trajectories, ranging from ambitious climate-change mitigation—in line with the Paris agreement—to unabated climate change. We find significant increases in average daily peak load and overall electricity consumption in southern and western Europe (∼3 to ∼7% for Portugal and Spain) and significant decreases in northern Europe (∼−6 to ∼−2% for Sweden and Norway). While the projected effect on European total consumption is nearly zero, the significant polarization and seasonal shifts in peak demand and consumption have important ramifications for the location of costly peak-generating capacity, transmission infrastructure, and the design of energy-efficiency policy and storage capacity.

scholarly journals Demand Side Management using Grid-Tied Photovoltaic Energy System

2019 ◽  
Vol 9 (1) ◽  
pp. 4190-4194 ◽  
Keyword(s):  
Energy Management ◽  
Electricity Market ◽  
Low Cost ◽  
Cost Savings ◽  
Energy System ◽  
Electrical Network ◽  
Solar Pv ◽  
Pv System ◽  
Great Cost ◽  
The Impact

This paper investigates the impact of investments in DSM technologies in Palestinian electricity market in order to solve the problem of supply shortages in electrical network, especially in peak demand periods. Renewable hybrid system, which can explore solar PV source at low cost, is a popular choice for this purpose nowadays, optimal energy management solutions can be obtained with great cost savings and active control performance. This paper analyzes the performance and feasibility of implementation DSM system in Palestinian distribution network, using on-grid PV system and energy management system.

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