The Impact of Bidding Rules on Electricity Markets With Intermittent Renewables

Sisternes, Fernando J. de; Webster, Mort; Pérez-Arriaga, Ignacio J.

doi:10.1109/tpwrs.2014.2355775

Cited by 27 publications

(18 citation statements)

References 6 publications

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“…Combining a capacity expansion formulation with detailed operational constraints and operating reserve requirements enables our study to reflect the impact of the variability and uncertainty of renewable resources on the operation of thermal units, operating reserve requirements, and on capacity expansion decisions, and ultimately the value of energy storage in decarbonizing the electricity sector. These aspects are critical in the analysis of low carbon emissions power systems [13] [24].…”

Section: Generation Capacity Expansion Modelmentioning

confidence: 99%

“…In our analysis we made extensions to the Investment Model for Renewable Electricity Systems (IMRES) [24], an advanced generation capacity expansion model that considers unit commitment constraints for individual power plants, system-wide reliability requirements, and individual power plant investment decisions. The model selects the cost-minimizing set of investments in electricity generation capacity to reliably meet the electricity demand in a future year, subject to a CO 2 emissions limit.…”

Section: Introductionmentioning

confidence: 99%

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The value of energy storage in decarbonizing the electricity sector

2016

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Electrical energy storage could play an important role in decarbonizing the electricity sector by offering a new, carbon-free source of operational flexibility, improving the utilization of generation assets, and facilitating the integration of variable renewable energy sources. Yet, the future cost of energy storage technologies is uncertain, and the value that they can bring to the system depends on multiple factors. Moreover, the marginal value of storage diminishes as more energy storage capacity is deployed. To explore the potential value of energy storage in deep decarbonization of the electricity sector, we assess the impact of increasing levels of energy storage capacity on both power system operations and investments in generation capacity using a generation capacity expansion model with detailed unit commitment constraints. In a case study of a system with load and renewable resource characteristics from the U.S. state of Texas, we find that energy storage delivers value by increasing the cost-effective penetration of renewable energy, reducing total investments in nuclear power and gas-fired peaking units, and improving the utilization of all installed capacity. However, we find that the value delivered by energy storage with a 2-hour storage capacity only exceeds current technology costs under strict emissions limits, implying that substantial cost reductions in battery storage are needed to justify large-scale deployment. In contrast, storage resources with a 10-hour storage capacity deliver value consistent with the current cost of pumped hydroelectric storage. In general, while energy storage appears essential to enable decarbonization strategies dependent on very high shares of wind and solar energy, storage is not a requisite if a diverse mix of flexible, low-carbon power sources is employed, including flexible nuclear power.

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Section: Generation Capacity Expansion Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The value of energy storage in decarbonizing the electricity sector

2016

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“…We arbitrarily select an ATQ for the case study, being the exhaustive search for an optimal set of weeks (ES). The approach is explained and tested in several papers from the literature [3,8,9]. With the input data series being demand (D), wind (W), and PV (PV), we initially calculate the residual loads for each hour h as…”

Section: Aggregation Technique: Exhaustive Search (Es)mentioning

confidence: 99%

Finding a Portfolio of Near-Optimal Aggregated Solutions to Capacity Expansion Energy System Models

Buchholz

Gamst

Pisinger

2020

SN Oper. Res. Forum

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Energy system models are frequently being influenced by simplifications, assumption errors, uncertainties, incompleteness, and soft constraints which are challenging to model in a good way. In capacity expansion modeling, also the long time horizon and the high shares of renewable energies feed into the uncertainties. Consequently, a single optimal solution might not provide enough information to stand alone. Contrarily, a portfolio of different solutions, all being within an acceptance span of the system costs, would create more valuable decision support tool. This idea is known from the literature where a near-optimal solution space typically is explored by introducing integer cuts that iteratively cut off solutions as they are found. Generalizing this idea, we suggest an approach that explores the near-optimal solution space by iteratively finding new solutions which are as different as possible from earlier solutions with respect to investment decisions. Our method deviates from the literature since it maximizes the difference of the found solutions rather than finding k similar solutions. An advantage of this approach is that the resulting portfolio holds high diversity which creates a better basis for good decision-making. Moreover, it overcomes a potential struggle of getting symmetric solutions and it strengthens the robustness arguments of the different investment decisions. Furthermore, we suggest to search for alternative solutions in an aggregated solution space whereas the original solution space typically has been used for the search in previous work. We hereby exploit the speedup achieved through aggregation to find more solutions, and we observe that these solutions might indicate must have investments of the non-aggregated problem. The suggested approach is tested on a case study for three different limitations on the system costs. Results show that our approach by far outperforms the approach known from the literature when the neighborhood size exceeds 0.7%. Furthermore, using our approach, a portfolio of eight solutions with

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“…More generally, considering the way electricity markets may be impacted by renewables, De Sisternes et al [11] describe an elegant market modeling setup allowing to analyze the impact of bidding rules and regulatory uncertainty on revenues and consumer costs, even for complex market setups in terms of bidding rules. Their proposal framework then allows them to look at transitory regimes where market setups and generation mix are not adapted to the share of renewables in the system, which is likely to be the case for nearly all electricity markets worldwide.…”

Section: Contributions From This Special Sectionmentioning

confidence: 99%

Foreword for the Special Section on Wind and Solar Energy: Uncovering and Accommodating Their Impacts on Electricity Markets

O’Malley

2015

IEEE Trans. Power Syst.

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The Impact of Bidding Rules on Electricity Markets With Intermittent Renewables

Cited by 27 publications

References 6 publications

The value of energy storage in decarbonizing the electricity sector

The value of energy storage in decarbonizing the electricity sector

Finding a Portfolio of Near-Optimal Aggregated Solutions to Capacity Expansion Energy System Models

Foreword for the Special Section on Wind and Solar Energy: Uncovering and Accommodating Their Impacts on Electricity Markets

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