Modelling and forecasting fossil fuels, CO2 and electricity prices and their volatilities

García‐Martos, Carolina; Rodríguez, Julio; Sánchez, Marı́a Jesús

doi:10.1016/j.apenergy.2012.03.046

Cited by 127 publications

(57 citation statements)

References 39 publications

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“…so that z g , p z = z,p z , where the sense of all the components of the vectors z,p z , z g , p z , is completely identical to that of the corresponding components of the vectorsỹ,p y , y g , p y , respectively, and the corresponding components of the vectors from (4) satisfy the system of constraints that is completely identical to system (2) and is assumed to be compatible. Here, π z j , j ∈ 1, n have the meaning similar to that of π y i , i ∈ 1, m. Finally, let s z j be the hourly price that utility company j pays the transmission company for a unit volume of electric energy transmitted to this untility company j during the 24 h period of time, and let˜ z = ( z , .…”

Section: Utility Companiesmentioning

confidence: 99%

“…, 0), where˜ z is the vector of the same dimension asz with all non-zero components equalling 1, where z ∈ R 24 + is the vector with all the components equalling 1. With the use of this notation, the goal function of utility company j, j ∈ 1, n can be written as so that u g , p u = ũ,p u , where the sense of the components of the vectors u,p u , u g , p u is completely identical to that of the corresponding components of the vectorsỹ,p y , y g , p y , respectively, and the corresponding components of the vectors from (6) satisfy the system of constraints that is completely identical to system (2) and is assumed to be compatible. Here, π u k , k ∈ 1, r have the same meaning that do π y i , i ∈ 1, m and π z j , j ∈ 1, n. Finally, let s u k be the hourly price that group of advanced customers k pays the transmission company for a unit volume of electric energy transmitted to this group of advanced customers during the 24 h period of time, and let˜ u = ( u , .…”

Section: Utility Companiesmentioning

confidence: 99%

“…Unstable world prices on fossil fuels [1,2], which are used for generating electric energy at many power stations, an uncertain customer demand for electricity during different day, evening, and night hours [3], a rapidly growing deployment of renewable sources of energy, especially those of wind and solar energy, for obtaining electricity [4][5][6], and the uncertainty caused by the liberalization of laws governing the operation of the electrical grid [7,8] represent only a few major factors that should be taken into consideration in choosing directions of keeping the grid responsive to public needs, as well as to those of both private and public sectors of the country's economy in general.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A game-theoretic approach to optimizing the scale of incorporating renewable sources of energy and electricity storing systems in a regional electrical grid

Belenky

2015

Energy Syst

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The problem of developing a decision support system for estimating a) the scale of incorporating available renewable sources of energy (such as solar and wind energy) in a part of a country's electrical grid (called a regional electrical grid further in this paper), and b) the scale of storing electricity in this (regional) electrical grid to make these renewable sources of electric power competitive with traditional power generators (such as fossil-fuel and nuclear ones) and to reduce the cost of acquiring electricity from all the electric power generating facilities in the grid is considered. In the framework of this system, renewable sources of energy are viewed as electricity generating facilities under both existing and expected electricity prices, and the uncertainty of energy supply from them and the uncertainty of the grid customer demand for electricity during every 24 h are taken into account. A mathematical model underlying the system allows one to study the interaction of all the grid elements as a game with a finite (more than three) number of players on a polyhedron of connected player strategies (i.e., strategies that cannot be chosen by the players independently of each other) in a finite-dimensional space. It is shown that solving both parts of the problem under consideration is reducible to finding Nash equilibrium points in this game.

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Section: Utility Companiesmentioning

confidence: 99%

Section: Utility Companiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A game-theoretic approach to optimizing the scale of incorporating renewable sources of energy and electricity storing systems in a regional electrical grid

Belenky

2015

Energy Syst

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“…There are a large family of different models in this category that can deal with many special cases including seasonality, nonstationary, and non-homogeneity of variances (see e.g. [15,16]). The major drawback of such models is that the future values are typically forecasted based upon the past and present values of cooling and electricity load demands without considering any exogenous factors in the model.…”

Section: Background Studymentioning

confidence: 99%

Modeling and forecasting of cooling and electricity load demand

et al. 2014

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h i g h l i g h t sWe propose a model for forecasting cooling and electricity load demand. The model takes the advantage of both time series and regression methods. The model is able to accurately forecast the load demands of the CCHP system. a r t i c l e i n f o t r a c tThe objective of this paper is to extend a statistical approach to effectively provide look-ahead forecasts for cooling and electricity demand load. Our proposed model is a generalized form of a Cochrane-Orcutt estimation technique that combines a multiple linear regression model and a seasonal autoregressive moving average model. The proposed model is adaptive so that it updates forecast values every time that new information on cooling and electricity load is received. Therefore, the model can simultaneously take advantage of two statistical methods, time series, and linear regression in an adaptive way. The effectiveness of the proposed forecast model is shown through a use case. The example utilizes the proposed approach for economic dispatching of a combined cooling, heating and power (CCHP) plant at the University of California, Irvine. The results reveal the effectiveness of the proposed forecast model.

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“…Based on the stochastic LCOE theory developed in our previous work [12,14], the system LCOE theory will be then extended towards a "stochastic system LCOE theory", in order to include investment risk assessment into the analysis. In this regard, one should consider that economic and financial risk in the electric energy sector is mainly due to the high volatility of fossil fuels and CO 2 market prices [15]. Annual variability of the intermittent source is not considered in this study as a further source of uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Optimal Integration of Intermittent Renewables: A System LCOE Stochastic Approach

Lucheroni

Mari

2018

Energies

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Abstract:We propose a system level approach to value the impact on costs of the integration of intermittent renewable generation in a power system, based on expected breakeven cost and breakeven cost risk. To do this, we carefully reconsider the definition of Levelized Cost of Electricity (LCOE) when extended to non-dispatchable generation, by examining extra costs and gains originated by the costly management of random power injections. We are thus lead to define a 'system LCOE' as a system dependent LCOE that takes properly into account intermittent generation. In order to include breakeven cost risk we further extend this deterministic approach to a stochastic setting, by introducing a 'stochastic system LCOE'. This extension allows us to discuss the optimal integration of intermittent renewables from a broad, system level point of view. This paper thus aims to provide power producers and policy makers with a new methodological scheme, still based on the LCOE but which updates this valuation technique to current energy system configurations characterized by a large share of non-dispatchable production. Quantifying and optimizing the impact of intermittent renewables integration on power system costs, risk and CO 2 emissions, the proposed methodology can be used as powerful tool of analysis for assessing environmental and energy policies.

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Modelling and forecasting fossil fuels, CO2 and electricity prices and their volatilities

Cited by 127 publications

References 39 publications

A game-theoretic approach to optimizing the scale of incorporating renewable sources of energy and electricity storing systems in a regional electrical grid

A game-theoretic approach to optimizing the scale of incorporating renewable sources of energy and electricity storing systems in a regional electrical grid

Modeling and forecasting of cooling and electricity load demand

Optimal Integration of Intermittent Renewables: A System LCOE Stochastic Approach

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