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This paper explores the sensitivity of electricity prices in energy-only markets with large amounts of wind and solar power. After electricity prices have fallen in many energy-only markets in recent years, the topic has been discussed in many studies with different approaches. The approach in this paper is to perform extensive electricity market simulations. The study is based on the North European...
This paper analyses how strongly EU energy policies have driven electricity wholesale prices. Especially, it investigates whether the activities of the Energy Union directed to increasing competition in the electricity system, creating an internal market without barriers for electricity flows, supplying sustainable and secure electricity, has led to a decline in electricity prices. Therefore, renewable...
This chapter models long-term electricity forward prices with variables that influence the price of electricity. Long-term modelling requires consideration of expected changes in the demand and supply structure. The model combines high-resolution information on fuel costs from financial markets and low-resolution information on the demand/supply structure of the electricity market. We model the latter...
This paper aims to give the variations of electricity price by considering the effect of wind energy integrated into the system and also the system variations such as load demand, outages and congestion. The electricity market is cleared by using a two stage stochastic optimization model in which first stage represents the scheduled case and the second stage represents the deviations from the scheduled...
High performance grid computing is a key enabler of large scale collaborative computational science. With the promise of exascale computing, high performance grid systems are expected to incur electricity bills that grow super-linearly over time. In order to achieve cost effectiveness in these systems, it is essential for the scheduling algorithms to exploit electricity price variations, both in space...
In this paper we suggest the use of robust STAR (Smooth Transition AutoRegressive) processes to model and forecast electricity prices observed on deregulated markets. The robustness of the model is achieved by extending to time series the M-type estimator based on the polynomial weighting function first introduced for independent multivariate data. The robust M-STAR estimator can be considered as...
In this paper we suggest the use of robust GM-SETAR (Self Exciting Threshold AutoRegressive) processes to model and forecast electricity prices observed on deregulated markets. The robustness of the model is achieved by extending to time series the generalized M-type (GM) estimator first introduced for independent multivariate data. As it has been shown in a very recent paper [1], the polynomial weighting...
It is expected that in the near future the number of Plug-in Electric Vehicles (PEV) could increase significantly due to their low pollution emissions, high fuel economy, and mitigation of security issues related to oil technical and economic management. Many works have dealt with the impact of PEV on the power and distribution grids, and on other particular aspects, but very few perform more general...
Load forecasting is highly important for power system operation and planning. Demand response, as a valuable feature in smart grid, is growing dramatically as an effective demand management method. However, traditional load forecasting tools have limitations to reflect demand response customer behaviors into load predictions. The energy consumption by demand response customers is mostly guided by...
This paper proposes an optimization model based on a centralized dispatch to analyze the impact of plug-in electric vehicles (PEV) penetration on the Spanish electricity demand and price. Different charging strategies, from the plug-and-charge strategy to the smartest vehicle-to-grid (V2G) capabilities, have been simulated and compared with the non PEV scenario, under different penetration values...
We develop a bottom-up, midterm model for the Nord Pool system price. Models for consumption, generation and exchange are combined using a market equilibrium approach. Scenarios for the most influential stochastic factors are created using statistical models. Forecasted price scenarios yield an indication on the expected future system price, and the uncertainty in future prices. Compared to stochastic...
The demand for electrical power is not constant. There are certain times of the day where the demand levels are much higher than the rest of the day. The demand can often exceed the generation capacity and when that happens, the utility companies can either shed loads or buy additional electrical energy from wholesale electricity markets to close the gap between demand and supply. These markets clear...
This paper uses a market equilibrium model to calculate how the mix of generating capacity would change if large amounts of intermittent renewables are built in Great Britain, and what this means for operating patterns and the distribution of prices over time. The model is calibrated to 2020 data for wind and demand (from Green and Vasilakos, Energy Policy, 2010) with costs from Mott MacDonald's 2010...
In liberalized electricity markets participants are obliged to schedule their electricity plans in advance because in a power system, equilibrium of production and consumption must be kept at all times. In order for power system to function, market participants forecast their plans trying to minimize their load forecasting error. Deviations from their realized energy through sale and purchase of balancing...
Smart grid support for demand response provides strategies for an electricity service provider to shed loads during peak usage periods with minimal consumer inconvenience. Direct load control is a strategy for doing this in which consumers enroll appliances such as electric water heaters, air conditioners, and battery vehicles in a program to respond to load shed instructions in exchange for a discount...
With the deepening reform to power industries, power systems are going to gradually open the demand side and the power consumers have to face the changes of their role in the market, and make a preliminary long-term forecasting for the electricity prices. In order to consider the relations between the spot market and the long-term contract market, this paper builds a multi-electricity price grey model...
In this paper, we define the portfolio of a generation company as the coordination of a set of generation units, which differ in production cost, capacity, and geographical location. A portfolio allows a generation company to coordinate its generators to bid strategically to earn profit more than what can be achieved without coordination. In a constrained transmission network, for example, a generation...
In this paper the volatility structure of electricity prices in the Italian zonal market is analyzed. Volatility should be a primary concern for investors and operators on energy markets because it is related to investment uncertainty and power plant management. Even if volatility of electricity prices received extensive attention in the past, the relationship with traded and demanded electricity...
An agent-based model is applied to model the German electricity wholesale market with its four major German utility companies. The model is utilized to assess base and peak power spot prices for scenarios implying doubling or tripling wind generation capacity in Germany. Furthermore, the effect of 8 million Plug-In Hybrid Electric Vehicles (PHEVs), incorporating different charging/discharging patterns,...
In order to meet the 20-20-20 European energy policy commitments Spain should continue increasing the amount of electricity production from renewable energy sources (RES) along this decade. This paper analyzes the impact of the future RES deployment on the Spanish power system. Six scenarios are defined by setting different RES installed capacity targets and considering the uncertainty in fuel prices...
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