Negative Electricity Prices Research Articles

Space solar power project and a theoretically performable solar energy policy with some proposed improvement measures for energy transition in the future

ABSTRACT For the renewable energies (REs), solar power generation is currently the most common. Some countries are currently competing to develop Space Solar Power (SSP) projects, hoping to take the lead in this race to obtain energy from space with high conversion efficiency. In Taiwan, the SSP generation project is expected to cost US$4 billion in research and development in the next five years, and subsequent costs will be astronomical. From an energy management perspective, these proposed improvement measures will be powerful to improve the effectiveness of generating electricity for the SSP system and the solar panels on the ground, so that obtained energy from them can be integrated into an integrated energy (IE), as well as corresponding recycling measures and a reliable energy storage system (ESS) are used. This ESS can store much solar energy to avoid the phenomenon of duck curve and negative electricity prices. Therefore, combing with the concept of the IE, there is a theoretically performable solar energy policy for energy transition in the future. However, in Taiwan, such energy transition using the REs concerns must be considered not only in terms of energy availability at an affordable price, but also from a political and social perspective.

Dynamic optimal allocation of energy storage systems integrated within photovoltaic based on a dual timescale dynamics model

Energy storage systems (ESSs) operate as independent market participants and collaborate with photovoltaic (PV) generation units to enhance the flexible power supply capabilities of PV units. However, the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully understood. This study introduces a dual-timescale dynamics model that integrates a spot market clearing (SMC) model into a system dynamics (SD) model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems (IESSs) with that of an ESS integrated within a PV (PV-ESS). Furthermore, this study aims to ascertain the optimal allocation of the PV-ESS. First, SD and SMC models were set up. Second, the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem, a dual-timescale model was constructed. Finally, a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS allocation. Additionally, negative electricity prices were considered during clearing processes. The simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS, helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

P2M systems based on proton-conducting solid oxide cells: Future prospects and costs of renewable methanol production

As consequence of the transition towards sustainable energy sources, the future production of liquid energy carriers (e.g. methanol) via H2 supply pathways utilizing water electrolyzers (power-to-liquid) will most likely be based on fluctuating grid electricity or islanded renewable inputs. As a result, these production processes are subject to fluctuating operating conditions and varying production capacities, ultimately leading to uncertainties with respect to their process economics and profitability. Therefore, the impact of different electricity supply-side scenarios (static grid and intermittent grid or renewable supply) on the production economics of power-to-liquid processes needs to be assessed thoroughly for the upcoming decades. Methanol is considered as an essential base chemical which is widely known for its versatility and broad potential use contexts in future chemical industries and energy storage applications. Methanol production pathways powered by renewable electricity sources, also known as power-to-methanol processes, are characterized by low specific life-cycle emissions and are therefore of paramount interest. One possible renewable process chain features proton-conducting high temperature electrolyzers combined with a direct hydrogenation of CO2. In this paper, a techno-economic forecast study of this process chain is presented and specific production costs of renewable methanol under different electricity supply scenarios are determined and discussed for the years 2030 and 2050. The studies showed that flexible grid-supported scenarios through direct spot-market participation and renewable scenarios based on wind onshore production enable the largest production cost reduction potential in the upcoming decades. Minimum production costs of 740 € t−1MeOH (2030) and 415 € t−1MeOH (2050) are determined for a flexible operation of the system with spot-market participation, benefitting from times of low or even negative electricity prices. Among the renewable production scenarios, islanded power-to-methanol systems coupled to wind onshore plants were identified as the most beneficial configuration with ascertained production costs as low as 820 € t−1MeOH and 353 € t−1MeOH by 2030 and 2050, respectively.

Risk‐Constrained Optimal Scheduling in Water Distribution Systems Toward Real‐Time Pricing Electricity Market

AbstractIn recent years, as a result of emerging renewable energy markets, several developed regions have already launched Real‐Time Pricing (RTP) strategies for electricity markets. Establishing optimal pump operation for water companies in RTP electricity markets presents a challenging problem. In a RTP market, both positive and negative electricity prices are possible. These negative prices create economically attractive opportunities for Water Distribution System (WDS) to dispatch their energy consumption. On the other hand, excessively high prices may put WDS at risk of supply disruptions and reduced service levels. However, the continuous development of wind power and photovoltaics results in more volatile and unpredictable fluctuations in the price of renewable energy. The risk arising from uncertainty in electricity prices can lead to a significant increase in actual costs. To address this issue, this paper develops an a posteriori random forest (AP‐RF) approach to forecast the probability density function of electricity prices for the next day and provide a risk‐constrained pump scheduling method toward RTP electricity market. The experimental results demonstrate that the developed method effectively addresses the issue of increased costs caused by inaccurate electricity price forecasting.

Negative electricity prices as a signal for lacking flexibility? On the effects of demand flexibility on electricity prices

PurposeThe purpose of this paper is to examine how active consumers, i.e. consumers that can inter-temporally shift their load, can influence electricity prices. As demonstrated in this paper, inter-temporal load shifting can induce negative electricity prices, a recurring phenomenon on power exchanges.Design/methodology/approachThe paper presents a novel electricity-market model assuming a nodal-pricing, energy-only spot market with active consumers. This study formulates an economic equilibrium problem as a linear program and uses an established six-node case study to compare equilibrium prices of a model with inflexible demand to a model with flexible demand of active consumers.FindingsThis study illustrates that temporal coupling of hourly market clearing through load shifting of active consumers can cause negative electricity prices that are not observed in a model with ceteris paribus inflexible demand. In such situations, where compared to the case of inflexible demand more flexibility is available in the system, negative electricity prices signal lower total system costs. These negative prices result from the use of demand flexibility, which, however, cannot be fully exploited due to limited transmission capacities, respectively, loop-flow restrictions.Originality/valueLiterature indicates that negative electricity prices result from lacking flexibility. The results illustrate that active consumers and their additional flexibility can lead to negative electricity prices in temporally coupled markets, which in general contributes to increased system efficiency as well as increased use of renewable energy sources. These findings extend existing research in both the area of energy flexibility and causes for negative electricity prices. Therefore, policymakers should be aware of such (temporal coupling) effects and, e.g. continue to allow negative electricity prices in the future that can serve as investment signals for active consumers.

Negative price spiral caused by renewables? Electricity price prediction on the German market for 2030

Logistic regression models were built and used to show the influence of energy sources, fuel, emission prices and time variables on low and negative price events. The models were tuned and validated with data from 2019 to 2021. The results show that volatile generation of wind and solar power raises the likelihood of low and negative electricity prices. Flexible power sources such as gas power plants, as well as high grid load and conventional generation, relate to higher, more stable market prices. Higher CO2 allowance prices also reduce the likelihood of negative prices, as flexible gas power plants with lower CO2 emissions compared to inflexible coal power plants are more flexible. The biggest influence of the Covid-19-pandemic was on the grid load in 2020 and 2021, which dropped heavily and lowered the electricity price on the market. The prediction analysis shows that in 2030 more low and negative price events will occur if the power supply does not become more flexible. Gas power plants, especially gas turbine peaker plants, help to reduce low prices in the future.

Shaping photovoltaic array output to align with changing wholesale electricity price profiles

Large-scale deployment of solar photovoltaics (PV) contributes to the occurrence of depressed—and sometimes negative—electricity prices during daylight hours as PV displaces higher-cost generators in the merit-order dispatch stack. These changes in electricity price provide an opportunity to increase the wholesale energy revenue of PV generators through temporal shaping of PV output. Here, we explore the impact of three output-shaping strategies on PV wholesale energy revenue and capacity factor: utilization of 1-axis tracking, curtailment during negative-price hours, and modification of fixed-tilt array orientation. Utility-scale PV arrays are modeled at more than 10,000 pricing nodes across six United States electricity markets over the 2010–2017 time period. Large changes in revenue-optimized output profiles are observed for the California system, where solar capacity penetration has increased from ∼2% of peak load in 2010 to ∼28% of peak load in 2017, and the wholesale revenue benefits of temporal output shaping are increasing with time. On the California real-time market in 2017, compared to capacity-factor-optimized fixed-tilt arrays with must-run operation, curtailment increases revenues by 9%, curtailment in conjunction with fixed-tilt orientation optimization increases revenues by 20%, 1-axis tracking without curtailment increases revenues by 32%, and 1-axis tracking with curtailment increases revenues by 42% for the median node. Median optimal fixed-tilt azimuths for PV on the real-time market in California have increased from 192° in 2010 to 235° (i.e. 55° west of south) in 2017. Among the markets and years studied, the California market in 2017 demonstrates the largest potential benefit from temporal output shaping. These results highlight mechanisms for mitigating some of the decline in PV wholesale value at high solar penetrations, and illustrate the importance of adapting PV installation and dispatch strategies to changing power system conditions.

Bitcoin Mining to Reduce the Renewable Curtailment: A Case Study of CAISO

High energy intensity is an enduring problem for the cryptocurrencies, especially for those based on Proof-of-Work like Bitcoin. Energy demand not only comprises the largest share of the operation cost of Bitcoin mining, but also poses a considerable hindrance to the climate agenda. The present paper explores how renewable energy generation can be availed to address these challenges. The need to curtail excess production of renewable energy to maintain the balance between supply and demand and thereby avoid negative electricity prices opens possibilities for deploying renewables to meet bitcoin energy demand. Situating the Bitcoin mining machines at the generation side of solar and wind is an attractive solution to mitigate both the curtailment problem and the energy intensity problem. Here we present a case study on the California Independent System Operator (CAISO), analyzing the profitability of such a solution. Using 2018 historical data, our simulation reveals that the CAISO system will earn 5.6~48.1 million dollars net profit by selling Bitcoin without holding it. These mining machines will also absorb 50.8%~79.9% of the curtailed energy. The probability making a profit in terms of volatile bitcoin price and mining difficulty is positively correlated with the capacity factor of the mining machines. However, there is a tradeoff between the curtailment usage rate and the capacity factor of the machines. To consume more curtailed energy, the system will need to deploy more mining machines and become more sensitive to the volatility of the bitcoin price and hash rate.

Managing Wind‐Based Electricity Generation in the Presence of Storage and Transmission Capacity

We investigate the management of a merchant wind energy farm co‐located with a grid‐level storage facility and connected to a market through a transmission line. We formulate this problem as a Markov decision process (MDP) with stochastic wind speed and electricity prices. Consistent with most deregulated electricity markets, our model allows these prices to be negative. As this feature makes it difficult to characterize any optimal policy of our MDP, we show the optimality of a stage‐ and partial‐state‐dependent‐threshold policy when prices can only be positive. We extend this structure when prices can also be negative to develop heuristic one (H1) that approximately solves a stochastic dynamic program. We then simplify H1 to obtain heuristic two (H2) that relies on a price‐dependent‐threshold policy and derivative‐free deterministic optimization embedded within a Monte Carlo simulation of the random processes of our MDP. We conduct an extensive and data‐calibrated numerical study to assess the performance of these heuristics and variants of known ones against the optimal policy, as well as to quantify the effect of negative prices on the value added by and environmental benefit of storage. We find that (i) H1 computes an optimal policy and on average is about 17 times faster to execute than directly obtaining an optimal policy; (ii) H2 has a near optimal policy (with a 2.86% average optimality gap), exhibits a two orders of magnitude average speed advantage over H1, and outperforms the remaining considered heuristics; (iii) storage brings in more value but its environmental benefit falls as negative electricity prices occur more frequently in our model.

Bitcoin Mining to Reduce the Renewable Curtailment: A Case Study of Caiso

High energy intensity is an enduring problem for the cryptocurrencies, especially for those based on Proof-of-Work like Bitcoin. Energy demand not only comprises the largest share of the operation cost of Bitcoin mining, but also poses a considerable hindrance to the climate agenda. The present paper explores how renewable energy generation can be availed to address these challenges. The need to curtail excess production of renewable energy to maintain the balance between supply and demand and thereby avoid negative electricity prices opens possibilities for deploying renewables to meet bitcoin energy demand. Situating the Bitcoin mining machines at the generation side of solar and wind is an attractive solution to mitigate both the curtailment problem and the energy intensity problem. Here we present a case study on the California Independent System Operator (CAISO), analyzing the profitability of such a solution. Using 2018 historical data, our simulation reveals that the CAISO system will earn 5.6~48.1 million dollars net profit by selling Bitcoin without holding it. These mining machines will also absorb 50.8%~79.9% of the curtailed energy. The probability making a profit in terms of volatile bitcoin price and mining difficulty is positively correlated with the capacity factor of the mining machines. However, there is a tradeoff between the curtailment usage rate and the capacity factor of the machines. To consume more curtailed energy, the system will need to deploy more mining machines and become more sensitive to the volatility of the bitcoin price and hash rate.

Cogeneration of power and methanol based on a conventional power plant in Germany

Abstract The global increase in electricity production by wind and photovoltaic plants poses challenges for local electricity grids as well as for electricity markets. These renewable energy sources rely heavily on current weather conditions, by that producing electricity in a fluctuating manner. This results in temporary electricity surpluses causing temporarily low or even negative electricity prices. Additionally, a stable operation of the electricity grid must be maintained even locally. To solve these problems, the intelligent coupling of the electricity, gas and heat sectors could be a promising approach. So called “Power-To-X” concepts such as Power-to-Heat (P2H) or Power-to-Fuel (P2F) cover technologies that aim to convert electrical energy into material energy storages, synthetic fuels and energy-intensive chemical raw products. For conventional power plants, the production of methanol is currently the most discussed option in Germany. In this paper a techno-economic analysis of the implementation of a Power-to-Methanol plant (P2MeOH) into a conventional power plant is presented. This study is based on real power generation data of the real hard coal-fired power plant “Westphalia E” in Germany in 2017. It takes into account parameters such as P2MeOH invest costs, costs for carbon dioxide emission as well as electricity, methanol and oxygen market prices. The required mass and energy flows for the techno-economic analysis are calculated by a custom implemented thermodynamic model. This study shows that an additional revenue could be generated under current market situations and that this possible revenue sums up to 5.2 million € per year. In ecological regards, around 150,000 tons CO2 could be saved per year. The calculated P2MeOH invest costs amount to 137.5 million €. Additionally, it could be obtained that by far most costs are caused by the electrolyser. As further technical progress in that field is expected, this could lead to higher economic benefits in the future.

Risk premia in the German day-ahead electricity market revisited: The impact of negative prices

This paper replicates the study by Viehmann (2011) that investigated risk premia in the German day-ahead electricity market from October 2005 to September 2008. While estimated sizes of risk premia can be replicated, this paper does not reproduce respective standard errors, leading to remarkable differences between the reported significance levels. An extension with data of preceding years points to further differences with respect to size and statistical significance. In addition, this paper analyzes the impact of negative prices on risk premia. Negative electricity prices were introduced in 2008 at the European Power Exchange (EPEX), and in 2013 at the Energy Exchange Austria (EXAA). The results of an econometric analysis suggest that the introduction of negative prices has led to a decrease in risk premia when compared to the period of a positive price regime.

Economic assessment of virtual power plants in the German energy market — A scenario-based and model-supported analysis

The energy transition (“Energiewende”) in Germany will result in a substantial transformation of the energy supply system. Virtual power plants are expected to be important components of the new intelligent energy infrastructure. They aggregate beside different types of distributed generation units also active consumers and storage technologies in order to integrate these in a profit-maximising, system-stabilising, and sustainable way. The assessment of the economic performance of virtual power plants requires a scenario-based and model-supported analysis. In this relation, future energy market conditions are simulated using the scenario methodology. Starting from the year 2015, three scenarios have been identified that illustrate alternative energy developments in Germany by 2030. Based on these scenarios, the additional revenues potential of the modeled virtual power plant is identified when compared to an independent and non-market-oriented operation mode of distributed energy resources. According to the model results, revenues of the VPP can increase by 11% up to 30% in the analyzed scenarios in 2030 due to the market-oriented operation mode. Nevertheless, the amount and composition vary depending on technology-specific subsidies, temporary nature of power demand and price structures in the energy market. Fluctuating renewable energies are expected to benefit from the market-oriented operation mode in the virtual power plant, especially through the EEG direct marketing. The selective and regulated shutdown of renewable energies in times of negative electricity prices may lead to further cost savings. The utilization of temporary price fluctuations in the spot market and the demand-oriented provision of control power offer high additional revenue potential for flexible controllable technologies such as battery storage, biomethane as well as combined heat and power units. Finally, the determination of the long-term profitability of a virtual power plant still requires a full-scale cost–benefit analysis. For this holistic approach, the model results provide a reliable scientific basis.

Market integration of renewable energies through direct marketing - lessons learned from the German market premium scheme

Increasing the market and system integration of renewable energy sources (RES) is regarded as key to reducing the costs of RES support and transforming the electricity system. In several EU countries, feed-in premium schemes have been implemented to better align RES production with electricity prices and to enhance the efficiency of RES marketing by increasing direct participation of producers in electricity markets. This paper examines the lessons learned from the German market premium scheme, which was introduced in the Renewable Energy Sources Act 2012 as an optional alternative to feed-in tariffs. The 2014 reform of that law has made direct marketing mandatory except for small RES plants, thus establishing the sliding market premium as the new primary instrument of RES support. Combining a qualitative economic analysis with insights from sociological research on direct marketing and simulation results from agent-based modelling, we evaluate how well the optional market premium has performed in setting incentives for demand-oriented RES production and efficient marketing of RES electricity. Furthermore, we examine what efficiency gains can be realistically expected from the changes implemented in 2014, and discuss whether the direct marketing model adopted in Germany is a promising approach for improving the market integration of RES. We find that direct marketing has made a positive contribution to the marketing efficiency of dispatchable RES; for intermittent RES, it provides few structural changes compared to marketing through transmission system operators. The benefits of a greater demand-orientation of RES feed-in remain limited when considering the extent to which load shifting is incentivised. For intermittent RES in particular, incentives for demand-oriented feed-in are only effective in times of negative electricity prices when voluntary curtailment is encouraged. For the further development of mechanisms to support greater market proximity, differentiating between the various RES according to their ability to respond to electricity price signals can prove advantageous. Also, objectives such as improving security of supply and reducing the costs of transforming the electricity system cannot be reached through RES market integration efforts alone but require an adaptation of electricity market conditions to the requirements of RES.

Can negative electricity prices encourage inefficient electrical energy storage devices?

This paper explores whether negative electricity prices can change the rationale that efficient energy storage devices are more economical for arbitrage in electricity markets. An established model algorithm to determine the maximum available arbitrage revenue and optimum schedule of electrical energy storage (EES) operation is used to simulate storage with a time-series of electricity prices which includes some negative prices. Our results suggest that at any likely frequency of negative electricity prices, inefficient EES is not encouraged, and can only be encouraged for EES devices with very low energy capacity to power ratios.

Electricity by intermittent sources: An analysis based on the German situation 2012

The 2012 data of the German load, the on- and offshore and the photo-voltaic energy production are used and scaled to the limit of supplying the annual demand (100% case). The reference mix of the renewable energy (RE) forms is selected such that the remaining back-up energy is minimised. For the 100% case, the RE power installation has to be about 3 times the present peak load. The back-up system can be reduced by 12% in this case. The surplus energy corresponds to 26% of the demand. The back-up system and more so the grid must be able to cope with large power excursions. All components of the electricity supply system operate at low capacity factors. Large-scale storage can hardly be motivated by the effort to further reduce CO2 emission. Demand-side management will intensify the present periods of high economic activities. Its rigorous implementation will expand the economic activities into the weekends. On the basis of a simple criterion, the increase of periods with negative electricity prices in Germany is assessed. It will be difficult with RE to meet the low CO2 emission factors which characterise those European Countries which produce electricity mostly by nuclear and hydro power.

Price determination in the wholesale electricity markets

Price determination is one of the most complex issues facing business managers and decision makers. Electricity is a major input for almost every product and service sold in the market and its consumption represents a significant expense for retail consumers and industries. Nowadays, in many industrialised countries, many complex bidding mechanisms are used to determine the wholesale electricity prices. At the retail level, prices are determined, most of the times, by the regulatory agencies. This case-study presents the complexities of price determination at the wholesale electricity markets and explains the challenges business executives are facing in developing short and long term winning strategies. The unique case of negative electricity prices and their use as a sound short run business strategy is also explained and justified.