Market behaviour with large amounts of intermittent generation

Green, Richard; Vasilakos, Nicholas

doi:10.1016/j.enpol.2009.07.038

Cited by 192 publications

(139 citation statements)

References 14 publications

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“…First, rising electricity prices and increasing price volatility (Bierbrauer et al, 2007;Valenzuela et al, 2012) will encourage electricity retailers to implement and extend their Demand Response activities. The underlying reason is, as the literature on renewables suggests, that an increase in intermittent wind and solar generation comes at the cost of an increase in the spot-price variance (Chao, 2011;Green and Vasilakos, 2010;Jacobsen and Zvingilaite, 2010;Milstein and Tishler, 2011;Woo et al, 2011). Second, the penetration of Demand Response programs will also increase due to regulatory settings.…”

Section: Policy Implicationsmentioning

confidence: 99%

Measuring the financial impact of demand response for electricity retailers

Feuerriegel

Neumann

2014

Energy Policy

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Due to the integration of intermittent resources of power generation such as wind and solar, the amount of supplied electricity will exhibit unprecedented fluctuations. Electricity retailers can partially meet the challenge of matching demand and volatile supply by shifting power demand according to the fluctuating supply side. The necessary technology infrastructure such as Advanced Metering Infrastructures for this so-called Demand Response (DR) has advanced. However, little is known about the economic dimension and further effort is strongly needed to realistically quantify the financial impact. To succeed in this goal, we derive an optimization problem that minimizes procurement costs of an electricity retailer in order to control Demand Response usage. The evaluation with historic data shows that cost volatility can be reduced by 7.74 %; peak costs drop by 14.35 %; and expenditures of retailers can be significantly decreased by 3.52 %.

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Section: Policy Implicationsmentioning

confidence: 99%

Measuring the financial impact of demand response for electricity retailers

Feuerriegel

Neumann

2014

Energy Policy

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“…However, similar shares of VRE generation in different electricity markets have resulted in contrasting effects on daily price volatility, which will affect the profitability of conventional power plants. Indeed, via a supply-function equilibrium model, Green and Vasilakos (2010) demonstrate that the incorporation of intermittent renewable resources can increase price volatility in the British electricity industry. Such a change in market dynamics will likely lead to an optimal generation mix using more gas-fired plants in the long run (Green and Vasilakos, 2011).…”

Section: Introductionmentioning

confidence: 99%

Does renewable energy generation decrease the volatility of electricity prices? An analysis of Denmark and Germany

Rintamäki¹,

Siddiqui

Salo³

2017

Energy Economics

152

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Although variable renewable energy (VRE) technologies with zero marginal costs decrease electricity prices, the literature is inconclusive about how the resulting shift in the supply curves impacts price volatility. Because the flexibility to respond to high peak and low offpeak prices is crucial for demand-response applications and may compensate for the losses of conventional generators caused by lower average prices, there is a need to understand how the penetration of VRE affects volatility. In this paper, we build distributed lag models with Danish and German data to estimate the impact of VRE generation on electricity price volatility. We find that in Denmark wind power decreases the daily volatility of prices by flattening the hourly price profile, but in Germany it increases the volatility because it has a stronger impact on off-peak prices. Our analysis suggests that access to flexible generation capacity and wind power generation patterns contribute to these differing impacts. Meanwhile, solar power decreases price volatility in Germany. By contrast, the weekly volatility of prices increases in both areas due to the intermittency of VRE. Thus, policy measures for facilitating the integration of VRE should be tailored to such region-specific patterns.

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“…notes 1. Other examples of similar 'compound impact' problems can be found in peak-load estimation (e.g., Thornton et al 2017) and simple models for system planning applications (e.g., load duration curves for the estimation of the optimal generation-type mix: Green and Vasilakos 2010;Bloomfield et al 2016). 2.…”

Section: Discussionmentioning

confidence: 99%

The Nature of Weather and Climate Impacts in the Energy Sector

Brayshaw

2018

Weather &Amp; Climate Services for the Energy Industry

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The power sector's meteorological information needs are diverse and cover many different distinct applications and users. Recognising this diversity, it is important to understand the general nature of how weather and climate influence the energy sector and the implications they have for quantitative impact modelling. Using conceptual examples and illustrations from recent research, this chapter argues that the traditional 'transfer function' approach that is common to many industrial applications of weather and climate science-whereby weather can be directly mapped to an energy impact-is inadequate for many important power system applications (such as price forecasting and system operations and planning). The chapter concludes by arguing that a deeper understanding of how meteorological impacts in the energy sector are modelled is required.

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Market behaviour with large amounts of intermittent generation

Cited by 192 publications

References 14 publications

Measuring the financial impact of demand response for electricity retailers

Measuring the financial impact of demand response for electricity retailers

Does renewable energy generation decrease the volatility of electricity prices? An analysis of Denmark and Germany

The Nature of Weather and Climate Impacts in the Energy Sector

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