Share Of Variable Renewable Energy Research Articles

Exploring wind curtailment effects and economic implications in the growing variable renewable energy penetration

Several countries continue to invest in variable renewable energy (VRE) sources to replace fossil fuels and achieve a nationally determined contribution. Consequently, as the share of VRE generation in each country's power grid increases, its curtailment also increases. Current studies on VRE curtailment are based on a comparative analysis of statistical data collected from different countries. However, only a few studies present detailed results based on historical curtailment data collected from individual wind farms. This study analyzes the curtailment data collected for three wind farms over four years. The duration, curtailed output, and cost per curtailment were determined to be 200 min, 38 MWh, and $3.02k, respectively. Finally, the curtailment loss to wind farms caused by the increasing share of VRE generation in the power grid was estimated. The curtailed output and curtailment cost are estimated to increase by 1.3 GWh and $107.6k, respectively, when the share of VRE in the power grid increases by 1%. These findings can aid in identifying the curtailment experienced by wind farm operators and subsequent potential economic losses. Moreover, they can form the basis for establishing an efficient curtailment cost compensation system.

Offshore wind power around the Iberian Peninsula: variability, complementarity and added value for the power system

The advances in floating offshore wind energy are opening deep sea areas, like the coastal waters of Iberian Peninsula (IP), for the installation of wind farms. The integration of this new energy source in a semi-closed power system with an already high share of variable renewable energies would be facilitated if the potential contribution of offshore wind energy shows reduced variability and limited seasonal variations, as the power demand in IP shows two maxima in winter and summer. The aims of this study are the analysis of temporal variability and spatial complementarity of the potential installation sites, and the identification of an optimal combination of installation areas that minimizes the temporal variability of the aggregated offshore contribution. In order to better capture the marked mesoscale features of winds around the IP, wind data from a very high resolution reanalysis (COSMO-REA6) are used. The analysis considers allowed areas for installation, delimited by the maritime spatial planning. Northern coast areas are characterized by high capacity factors (CFs) and high seasonality, while the lower CFs at the western and southern coasts are compensated by a limited seasonality. Pairwise correlation between the potential areas shows outstanding results, with several negative correlation values within a synoptic scale region, in contrast to other mid-latitude regions like the North Sea or the Eastern USA coast. An optimal aggregation of areas includes at least one area at each of the four main Iberian coasts. A strong reduction of hourly variability is obtained through the resulting combinations, and the seasonality of the aggregated CF is clearly below the values for other offshore areas. Therefore, offshore wind energy can indeed offer an added value for the Iberian power system beyond the high resource amount, reducing the need for storage or backup plants.

Influence of bioenergy and transmission expansion on electrical energy storage requirements in a gradually decarbonized European power system

With the ongoing energy transition in Europe, the share of variable renewable energies (VRE) in the power system increases steadily and different flexibility options gain importance. This work investigates the deployment of supply side flexibility options in the future European power system by energy system modelling focusing on classic power storage technologies, hydrogen storage, generation by biomass and grid expansion. While investigating different flexibility availability scenarios, for the first time the competition of long-term flexibility options is investigated across a broad decarbonization spectrum. In all scenarios, an increasing need for additional flexibility options is found for moderate decarbonization levels with VRE shares higher than 50%. From there on, the deployment of power storages grows nonlinearly, and eventually features a remarkable leap when approaching a zero-emission system, which is mainly driven by hydrogen storage investments. This also comes along with a leap in the total system costs. When the expansion of biomass capacities is available, biomass partly takes over the function of hydrogen as a long-term flexibility option. When enabling grid expansion, additional transmission capacities lead to a stronger integration of wind generation, while (especially short-term) storage requirements for higher decarbonization levels decrease. Both the additional investments into biomass generation and transmission grid result in up to 4% lower total system costs, yet, without completely displacing any other flexibility option. We conclude that the interaction of multiply flexibility options will lead to a cost minimal power system.

Temporally detailed modeling and analysis of global net zero energy systems focusing on variable renewable energy

This study newly develops a recursive-dynamic global energy model with an hourly temporal resolution for electricity and hydrogen balances, aiming to assess the role of variable renewable energy (VRE) in a carbon-neutral world. This model, formulated as a large-scale linear programming model (with 500 million each of variables and constraints), calculates the energy supply for 100 regions by 2050. The detailed temporal resolution enables the model to incorporate the variable output of VRE and system integration options, such as batteries, water electrolysis, curtailment, and the flexible charging of battery electric vehicles. Optimization results suggest that combing various technical options suitable for local energy situations is critical to reducing global CO2 emissions cost-effectively. Not only VRE but also CCS-equipped gas-fired and biomass-fired power plants largely contribute to decarbonizing power supply. The share of VRE in global power generation in 2050 is estimated to be 57% in a cost-effective case. The results also imply economic challenges for an energy system based on 100% renewable energy. For example, the average mitigation cost in 2050 is 69USD/tCO2 in the cost-effective case, while it increases to 139USD/tCO2 in the 100% renewable case. The robustness of this argument is tested by sensitivity analyses.

Statistical Downscaling to Improve the Subseasonal Predictions of Energy-Relevant Surface Variables

Abstract Owing to the increasing share of variable renewable energies in the electricity mix, the European energy sector is becoming more weather sensitive. In this regard, skillful subseasonal predictions of essential climate variables can provide considerable socioeconomic benefits to the energy sector. The aim of this study is therefore to improve the European subseasonal predictions of 100-m wind speed and 2-m temperature, which we achieve through statistical downscaling. We employ redundancy analysis (RDA) to estimate spatial patterns of variability from large-scale fields that allow for the best prediction of surface fields. We compare explanatory powers between the patterns obtained using RDA against those derived using principal component analysis (PCA), when used as predictors in multilinear regression models to predict surface fields, and show that the explanatory power of the former is superior to that of the latter. Subsequently, we employ the estimated relationship between RDA patterns and surface fields to produce statistical probabilistic predictions of gridded surface fields using dynamical ensemble predictions of RDA patterns. We finally demonstrate how a simple combination of dynamical and statistical predictions of surface fields significantly improves the accuracy of subseasonal predictions of both variables over a large part of Europe. We attribute the improved accuracy of these combined predictions to improvements in reliability and resolution.

Introducing a new wind speed complementarity model

Minimizing the residual load is essential in countries with a high share of variable renewable energies (VRE). Optimally, new wind turbine sites provide high resource availability and the potential for smoothing the temporal course of the residual load. Current high spatial resolution wind atlases are limited to the ability to find high capacity factor (CF) sites but do not provide CF during periods of high residual load. Thus, we derive a new high-spatiotemporal resolution wind speed model for adjusting wind turbine site selection to residual load. The model (WiCoMo) is developed at six-hourly temporal resolution and 25 m × 25 spatial resolution up to 200 m height from 1991 to 2018 in the study area of Germany. Residual load-weighted and adjusted CF in 2015–2018 is mapped using the new model and considering the national residual load. Besides, complementarity between CF and VRE is evaluated. According to the standard CF, there is a northwest-southeast CF gradient. Relying on the residual load adjusted CF site suitability in southern Germany increases compared to the rest of the country. The introduced model may be a valuable tool for adapting wind resource assessment in Germany on the increasing role of VRE in the electricity mix.

Profitability and the use of flexible CO2 capture and storage (CCS) in the transition to decarbonized electricity systems

• Fossil power with CCS will need to operate flexibly to ensure grid stability. • The profitability potential of flexible CCS is assessed in four national markets. • We show how a fraction of power plants can be profitable in each market. • This suggests a possible role for existing fossil plants in grid decarbonization. As the share of variable renewable energy (VRE) generation in a system increases, services such dispatchable “firm power” will be vital to ensure system reliability. Fossil power plants with CO 2 capture and storage (CCS) can be a source of firm power, but they must be operated in a flexible manner to support grid stability. This paper considers the use of CCS to pivot the role of at least some existing fossil plants towards providing firm power in decarbonized grids. We present an analysis of the profitability potential of CCS-equipped power plants in electricity markets in US, UK, Australia and China. Conventional wisdom holds that CCS must be operated in a baseload manner to be economically viable; we demonstrate that the flexibly-operated power plants with CCS are not generally profitable today, but can become profitable in cases with a proper combination of market incentives and cost reductions in capture technology; we highlight the possibility of retrofitting older plants with mostly depreciated capital for operation a “second life” peaker mode to retain investment flexibility during an energy system transition as an intriguing option requiring further study. Flexible operation offers less value in China's electricity markets due to more rigid pricing structures, but a plausible path towards profitable CCS-firm power exists for lower cost power plants in some regions of the country. The results presented here imply a strong potential for the profitable operation of CCS retrofitted to amortized assets, acting in a market-compatible way in synergy with greater integration of renewable energy to the power grid, whilst contributing to overall grid stability. As price volatility is likely to increase with increased penetration of VRE, the trend of these results are likely to become more pronounced with the passage of time.

Assessing the integration effect of inter-regional transmission on variable power generation under renewable energy consumption policy in China

Integrating a high share of variable renewable energy into multi-region power systems is essential and requires an interconnected transmission grid to coordinate regional power system operations. This paper proposes a multi-region power system optimization model to evaluate the role of interconnection in China's power sector for economic benefit, variable renewable energy power generation and allocation, transmission line efficiency and carbon emission transfer in the context of renewable energy consumption policy. The results show that inter-regional power transmission coupled with flexibility technology can facilitate renewable power generation and delivery. The renewable energy consumption policy would intensify this effect, although it leads to a slight drop in economic efficiency. Improving the compatibility of transmission network with variable power is crucial because wind and solar power are expected to make up 60% of the total inter-regional power transmission, particularly the share in the outward transmission lines from the northwest region reaching 91%. Renewable energy integration policy targets in northwest, north, Inner-Mongolia and northeast regions can be improved to 37.5%, 31.5%, 35.3%, and 36.9%, respectively.

An incentive profit-sharing mechanism for welfare transfer in balancing market integration

Due to the rising share of variable renewable energy, balancing market integration (BMI) has been advocated as a promising solution to achieve flexible resource sharing among different regions and enhance the flexibility of the overall power system. However, BMI can result in welfare transfers among regions, which may correspondingly give rise to resistance to integration. Therefore, an incentive mechanism to facilitate flexible resource sharing under BMI is designed in this paper. We first analyse the sources of the benefits of BMI and compare the influence of different market regulation approaches on the welfare transfer effect via a graphical method. Then, based on the Coase theorem, we design an incentive profit-sharing mechanism that is able to optimize the allocation of flexible resources and eliminate welfare transfers among regions to some extent to reduce possible resistance to integration. Case studies based on the three-region system and a realistic northwest power grid in China show that the balancing cost of multi-region systems can be respectively reduced up to 31% and 25%, and the utilization of flexible units can be increased by over 30% by BMI. Finally, corresponding policy implications for BMI are put forward; the proposed mechanism also provides a useful reference and insight for dealing with welfare transfers in interregional trading.

Capacity optimization of pumped storage hydropower and its impact on an integrated conventional hydropower plant operation

The energy sector contributes to around 60% of total greenhouse gas emissions. To limit climate change, the world is going through an energy transition to clean and affordable energy, therefore the share of variable renewable energy is increasing day by day. Power systems require significant flexibility to operate reliably. Pumped storage hydropower allows load balancing and stable integration of intermittent renewable energy in the electrical grid. All energy storage technologies, including pumped storage hydropower, are considered a net negative contributor to the grid since they draw more energy than they deliver. This paper uniquely investigates the true potential of pumped storage hydropower and its optimum operation along with existing conventional hydropower. It considers power, energy production, and utilization for both installations to determine an equilibrium condition for a net positive energy balance. The case study of the 300 MW Balakot conventional hydropower plant in Khyber Pakhtunkhwa, Pakistan indicates that the pumped storage hydropower sites, where additional water streams reach the upper storage reservoir, can reduce pumping energy consumption by up to 166 GWh/year. Accordingly, a pumped storage hydropower facility is proposed at Paras, Pakistan, modeled, and optimized in an integrated manner with the Balakot conventional hydropower plant for a net positive annual energy generation and profitability. The integrated power and energy modeling and capacity optimization of the hydropower complex highlight the importance of suitable site selection for pumped storage hydropower near existing conventional hydropower reservoirs. Value-added contribution of this configuration is that it can enhance annual energy generation from integrated conventional hydropower, reduce the upfront capital cost of the project by 10–15%, squeeze the project implementation schedule and result in a smaller carbon footprint to meet the ultimate objective of limiting climate change. Additionally, it unlocks huge untapped pumped storage hydropower potential besides existing conventional hydropower. Furthermore, the study guides the scientific and engineering organizations on optimum capacity utilization without impeding energy generation from conventional hydropower facilities.

Wind data introduce error in time-series reduction for capacity expansion modelling

Shares of renewable energy are rapidly increasing in many countries due to emissions policies and declining prices. Investment planning for future renewable deployment often relies on optimization models. Memory usage and solving time restrict these models, leading to tradeoffs in the treatment of temporal complexity, spatial complexity, and physical representation. A common approach is to reduce the temporal complexity of models. Reducing temporal complexity is often achieved by using time-series aggregating and modelling representative periods instead of a complete time series. But the impacts of such approaches are still poorly understood, especially for very low emissions systems with high shares of variable renewable energies. In this paper, the impacts of using time-series aggregation methods on optimal system design are investigated. It is found that the negative impact of time-series aggregation increases for lower emissions. It is also identified that modelling wind time-series data with representative days introduces this negative impact primarily and that representing wind time-series data with representative days decreases the reliability of supply defined as unserved load (0.05%–18.0%), introduces a bias in installed capacity (−31.15% to +12.2%), and underestimates total system cost (2.5%–44.9%). These effects are largest in cases with the strongest emission constraints. When designing low emissions systems with a high share of variable renewable energies, it is recommended not to use time-series aggregation to create representative days for wind power output. This paper contributes an Open Source analysis framework containing time-series aggregation and capacity expansion that should be applied when testing future time-series aggregation methods to reduce the identified negative impacts.

Improvements to Modern Portfolio Theory based models applied to electricity systems

With the increase of the share of variable renewable energies in electricity systems, many studies were developed in order to determine their optimal technological and spatial mix. Modern Portfolio Theory (MPT) has been frequently applied in this context. However, some crucial aspects, important in energy planning, are not addressed by these analyses. We, therefore, propose several improvements and evaluate how each change in formulation impacts results. More specifically, we use generation cost instead of installed capacity as one of the objectives; we consider the correlation between demand and generation profiles; and we limit shortage risks via the inclusion of a CVaR measure. These modifications are presented in a formal model which is also applied to the case of Brazil. We found that, after including our proposed modifications, the resulting efficient frontier differs strongly from the one obtained in the original formulation. The main difference is that the new efficient frontier has a much shorter range of acceptable standard deviation values. Therefore, many of the portfolios obtained from the traditional formulation have a much higher probability of under-production, especially portfolios located at regions with standard deviation either too low or too high. Furthermore, we show that diversification plays an important role in smoothing output from portfolios of variable renewable sources.

Flexibility of Epichlorohydrin Production—Increasing Profitability by Demand Response for Electricity and Balancing Market

The increasing share of variable renewable energies in the power grid is an incentive to explore demand response strategies. Chlor-alkali processes are high potential candidates, according to previous publications. Within Germany’s chemical industry, chlorine production accounts for approximately 20% of electricity use and could play a significant role in power grid stabilisation on the consumer end. This study focuses on the feasibility of load flexibilisation in epichlorohydrin plants, with the second biggest estimated demand response potential for chlorine-based products in Germany. A plant model with allyl chloride storage was created based on real data and literature values. Results from this model, spot market and balancing power prices, and future electricity market scenarios were used in a mixed-integer linear optimisation. We find that benefits from demand response can be generated as soon as additional power and storage volume is provided. The composition of provided types of balancing power bids follows the price trend on the market. Additionally, the computation time could be lowered significantly by running the scenarios in parallel. The results encourage a practical validation of the flexibility of epichlorohydrin production.

C-E (curtailment – Energy share) map: An objective and quantitative measure to evaluate wind and solar curtailment

As the share of VRE (variable renewable energy) has grown rapidly, curtailment issues have arisen worldwide. This paper evaluates and compares curtailment situations in selected countries using an objective and quantitative evaluation tool named the “C-E map” (curtailment-energy share map). The C-E map is a correlation map between curtailment ratios that mean curtailed wind (or solar) energy per available energy and energy shares of wind (or solar). The C-E map can draw a historical trend curve in a given country/area, as an at-a-glance tool to enable historical and/or international comparison. The C-E map also can classify the given countries/areas into several categories, according to the current levels of curtailment ratio and historical trends. The C-E map helps institutional and objective understanding of curtailment for non-experts including policy makers.

Power System Transition with Multiple Flexibility Resources: A Data-Driven Approach

Power systems are transitioning toward having high shares of variable renewable energy (VRE) with the help of flexibility resources. However, multiple flexibility resources on the generation, storage and demand sides introduce multiple technical and economic uncertainties, making the transition hard to predict. Moreover, the benefit of these resources in the transition is unclear. To fill these gaps, this paper proposes a data-driven approach to explore the transition to a high VRE share-oriented power system with multiple flexibility resources. This approach generates a wealth of possible transition paths under multiple uncertainties and then uses them to quantitatively analyze the transition. Specifically, the proposed method includes principal component analysis-based path visualization, multiple index-based transition milestone identification, cluster and distance calculation-based key influential factor identification, marginal index-based flexibility resource benefit comparison and Pareto frontier-based path recommendation. Case studies based on the Northwest China power system, which involves wind, photovoltaics and concentrated solar plants, validate the effectiveness of the proposed approach and further indicate that flexibility resources increase rapidly with the growth of the VRE share. Of the multiple flexibility resources, storage contributes the most. Key influential factors include the capital cost of VRE and storage along with coal price. These factors should be the focus in a low-cost and low-carbon transition.

Facing the high share of variable renewable energy in the power system: Flexibility and stability requirements

Power systems with a high share of variable renewable energy (VRE) represent a challenge to system operators because of the increased flexibility requirements and stability. This study analyses the performance of a real power grid with a high penetration of VRE (mainly wind and solar photovoltaic). A rule-based power model is developed to simulate the power system behaviour. One European country was selected (Spain), with limited international interconnections and well-established decarbonisation scenarios by national and European organisations. Flexibility requirements in the future power system were found through power plants' flexibility and stability constraints (i.e., inertia) and the expected changes in grid interconnection. The model results indicate that the ambitious targets for grid decarbonisation are not realistic because of these requirements. Considering the share of VRE for a sustainable transition (ST) scenario in 2030 (33% power generation) and in 2040 (35%), CO2-equivalent emissions will be reduced up to 157 and 159 kg CO2/MWh, respectively, which is well above Paris targets. Furthermore, no scenario allows meeting the expected environmental targets. Therefore, in power systems with more than 39% VRE, the results suggest that new technologies should be considered with emissions below ∼113 kgCO2/MWh, a maximum cost of ∼134 €/MWh, and an inertia constant above 5 s.

Analysis of effective measures for power fluctuation mitigation of geographically distributed wind and solar power

Establishing sustainable and economical pathways for the deployment of variable renewable energy (VRE) is essential for reducing greenhouse gas emissions and increasing energy security. However, due to VRE power output fluctuations, high shares of VRE are associated with increases in surplus power generation, which increases the cost of power supply. This paper examines the effects of power fluctuation mitigation measures on the integration of high shares of VRE in power supply systems. The paper takes a systematic approach to evaluate the effects of the geographical distribution of VRE locations, the increase in transmission capacity, and the introduction of large-scale battery storage while increasing the VRE share. The methodology used in this analysis is a linear programming-based power supply mix model which was developed to optimize installed capacities and operation patterns of a power supply system with geographically distributed VRE locations by minimizing the total cost of power supply. The developed methodology is applied to the power supply system of Hokkaido, Japan, as a case study. The results demonstrate that VRE shares of up to 40 % can be achieved by geographically distributing the VRE locations with no increase in the total cost of the power supply. This is because the geographical distribution of VRE locations suppresses the increase in surplus power generation. Further, achieving 40 % to 60 % VRE shares only requires an increase in the power transmission capacity. However, for higher VRE shares from 60 % to 80 %, a combination of the geographical distribution of VRE locations, transmission capacity increase, and the introduction of power storage are required to effectively minimize the amount of surplus power generated.

Mitigation of Short-Term Fluctuations in Wind Power Output in a Balancing Area on the Road Toward 100% Renewable Energy

The rapid growth of the share of variable renewable energy (VRE) may make it difficult to operate power systems incorporating these sources, due to fluctuations in VRE output. In this paper, we focus on the short-term fluctuations (STFs) in wind power total outputs in several balancing areas (BAs) in Japan. We propose five methods to mitigate STFs, utilizing innate functions of wind turbines that use neither battery systems nor any other additional systems or equipment. In addition, the methods suggested do not require predictions of the wind power output. The efficiency of the method was measured based on the relationship between the mitigation of STFs and associated energy loss. Historical wind power output data from three BAs in Japan (the Hokkaido, Tohoku, and Kyushu BAs) were used to conduct numerical simulations. One of the proposed methods effectively mitigated STFs in the total wind power output. The proposed approach is applicable to solar power and will help overcome challenges on the road toward 100% renewable energy.

A robust risk assessment method for energy planning scenarios on smart islands under the demand uncertainty

Energy systems with a high share of variable renewable energy are more vulnerable to sudden changes in the system operation. This is especially emphasized on small systems such as energy systems on geographical islands. Because of these reasons, there is a need for quantifying the risk of energy scenarios of such systems. This paper presents a novel robust risk assessment method under demand uncertainty for energy planning scenarios for the islands. The method uses graph theory for the representation of power system topology. The Poisson distribution is used for calculating the probability of power system element failure. The robust modelling approach is applied by the introduction of auxiliary variables and compared to the deterministic model results. Four energy planning scenarios for Unije island are modelled and subjugated to several power system outages resulting in a risk vector calculated as the product of probability vector and damage matrix. The study also presents a zero-import risk energy planning scenario for Unije island that is achieved for a system of 0.5 MW photovoltaic plant and 3.55 MWh battery storage system.

The Economics of Variable Renewable Energy and Electricity Storage

The transformation of the electricity sector is a central element of the transition to a decarbonized economy. Conventional generators powered by fossil fuels have to be replaced by variable renewable energy (VRE) sources in combination with electricity storage and other options for providing temporal flexibility. We discuss the market dynamics of increasing VRE penetration and its integration in the electricity system. We describe the merit-order effect (the decline of wholesale electricity prices as VRE penetration increases) and the cannibalization effect (the decline of VRE value as its penetration increases). We further review the role of electricity storage and other flexibility options for integrating variable renewables and how storage can contribute to mitigating the two mentioned effects. We also use a stylized open-source model to provide some graphical intuition on these issues. While relatively high shares of VRE are achievable with moderate amounts of electricity storage, the role of long-duration storage increases as the VRE share approaches 100%.