Variable Renewables Research Articles

Impacts of electric carsharing on a power sector with variable renewables

Impacts of electric carsharing on a power sector with variable renewables

Novel Recuperated Power Cycles for Cost-Effective Integration of Variable Renewable Energy

The ongoing transition to energy systems with high shares of variable renewables motivates the development of novel thermal power cycles that operate economically at low capacity factors to accommodate wind and solar intermittency. This study presents two recuperated power cycles with low capital costs for this market segment: (1) the near-isothermal hydrogen turbine (NIHT) concept, capable of achieving combined cycle efficiencies without a bottoming cycle through fuel combustion in the expansion path, and (2) the intercooled recuperated water-injected (IRWI) power cycle that employs conventional combustion technology at an efficiency cost of only 4% points. The economic assessment carried out in this work reveals that the proposed cycles increasingly outperform combined cycle benchmarks with and without CO2 capture as the plant capacity factor reduces below 50%. When the cost of fuel storage and delivery by pipelines is included in the evaluation, however, plants fired by hydrogen lose competitiveness relative to natural gas-fired plants due to the high fuel delivery costs caused by the low volumetric energy density of hydrogen. This important but uncertain cost component could erode the business case for future hydrogen-fired power plants, in which case the IRWI concept powered by natural gas emerges as a promising solution.

Power system benefits of simultaneous domestic transport and heating demand flexibility in Great Britain’s energy transition

The increasing share of variable renewables in power generation leads to a shortage of affordable and carbon neutral options for grid balancing. This research assesses the potential of demand flexibility in Great Britain to fill this gap using a novel linear optimisation model PyPSA-FES, designed to simulate optimistic and pessimistic transition pathways in National Grid ESO Future Energy Scenarios. PyPSA-FES models the future power system in Great Britain at high spatiotemporal resolution and integrates demand flexibility from both smart charging electric vehicles and thermal storage-coupled heat pumps. The model then optimises the trade-off between reinforcing the grid to align charging and heating profiles with renewable generation versus expanding dispatchable generation capacity. The results show that from 2030, under optimistic transition assumptions, domestic demand flexibility can enable an additional 20–30 TWh of renewable generation annually and reduce dispatchable generation and distribution network capacity by approximately 20 GW each, resulting in a total cost reduction of around £5bn yearly. However, our experiments suggest that half of the total system cost reduction is already achieved by only 25% of electric vehicles alone. Further, the findings indicate that once smart electric vehicle charging reaches this 25% penetration rate in households, minimal benefits are observed for implementing smart 12-hour thermal storages for heating flexibility at the national level. Additionally, smart heating benefits decrease by 90% across all metrics when only pre-heating (without thermal storages) is considered. Spatially, demand flexibility is often considered to alleviate the need for north–south transmission grid expansion. While neither confirmed nor opposed here, the results show a more nuanced dynamic where generation capacities are moved closer to demand centres, enhancing connectivity within UK sub-regions through around 1000 GWkm of additional transmission capacity.

Siting Analysis of a Solar-Nuclear-Desalination Integrated Energy System

Nuclear power is typically deployed as a baseload generator. Increased penetration of variable renewables motivates combining nuclear and renewable technologies into Integrated Energy Systems (IES) to improve dispatchability, component synergies and, through cogeneration, address multiple markets. However, combining multiple energy resources heavily depends on the proper selection of each system’s location and design limitations. In this paper, co-siting options for IES that couple nuclear and concentrating solar power (CSP) with thermal desalination are investigated. A comprehensive siting analysis is performed that utilizes global information survey data to determine possible co-siting options for nuclear and solar thermal generation in the United States. Viable co-siting options are distributed across the Southwestern U.S., with the greatest concentration of siting options in the southern Great Plains, although siting with higher solar direct normal irradiance is possible in other states such as Arizona and New Mexico. Brackish water desalination is also attractive across the southwest U.S. due to high water stress, but for brackish water desalination reverse osmosis (an electricity driven process) is most cost- and energy-efficient, which does not require co-siting with the thermal generator. The most attractive state for nuclear and thermal desalination (which is more attractive when using seawater) is Texas, although other areas may become attractive as water stress increases over the coming decades. Co-siting of all CSP and thermal desalination is challenging as attractive CSP sites are not coastal.

The impact of national policies on Europe-wide power system transition towards net-zero 2050

This research aims to investigate the potential impact of national policies on the attainment of Europe's goal of achieving net-zero greenhouse gas emissions by 2050. Specifically, it analyses the effects of policies on the power sector, by evaluating capacity expansion portfolios, import reliance, and costs by 2050. A linear programming model, the IESA-EUPS, is utilized to optimize the expansion and operation of the power system, considering 28 nodes and hourly temporal resolution. The study includes five scenarios from 2020 to 2050, with varying levels of biomass and nuclear penetration based on existing member state policies. Results show that by 2050, changes mainly occur in the interplay between firm capacities and cross-border transmission levels. Limiting biomass can significantly increase nuclear energy generation, while enforcing all policies leads to a 40 % rise in cross-border transmission by 2050, due to imbalances between countries. Some member states, such as Spain and Finland, are less affected, whereas others are heavily reliant on firm nuclear capacities. Western European countries with strict biomass and nuclear restrictions may see a boost in nuclear installations in countries allowing it. Member states without both nuclear and biomass may rely more on variable renewables, resulting in surplus electricity and increased LCOE.

Flexibility provision in the Swiss integrated power, hydrogen, and methane infrastructure

The renewable energy transition hinges on balancing energy supply and demand across seasons. This paper investigates the potential flexibility of Switzerland’s integrated power, hydrogen, and methane infrastructure to balance temporal mismatches while complying with national energy policies for sustainability and security. It develops an optimization method for energy system expansion and operation planning, filling crucial research gaps by (1) explicitly modeling power and gas transmission networks to guide technology placement and pinpoint network expansions, and (2) incorporating flexibility in power demand via shedding and shifting and in hydrogen and methane demands via price elasticity. The findings suggest that a 6.7-fold capacity expansion of variable renewables (i.e., photovoltaic, wind, run-of-river) by 2050 offsets nuclear phase-out and demand growth. The winter power gap is filled by power imports, hydropower generation, and gas turbines fueled by cost-effective hydrogen or methane imports. However, fuel embargoes escalate winter hydrogen and methane prices, reducing demand by 3.8%–10.4% and increasing domestic fuel production from biomass and excess renewable power in summer. To bridge the seasonal hydrogen and methane supply–demand gaps, up to 1.9 terawatt-hours of gas cavern storage is deployed in geologically viable locations, while costly tank storage plays a minor role. Power-to-gas requirements and power trade restrictions necessitate further renewable expansion, including 8.0 to 9.5 gigawatts of wind installations.

Measuring the Dunkelflaute: how (not) to analyze variable renewable energy shortage

Abstract As variable renewable energy sources increasingly gain importance in global energy systems, there is a growing interest in understanding periods of variable renewable energy shortage ("Dunkelflauten''). Defining, quantifying, and comparing such shortage events across different renewable generation technologies and locations presents a surprisingly intricate challenge. Various methodological approaches exist in different bodies of literature, which have been applied to single technologies in specific locations or technology portfolios across multiple regions. We provide an overview of various methods for quantifying variable renewable energy shortage, focusing either on supply from variable renewables or its mismatch with electricity demand. We explain and critically discuss the merits and challenges of different approaches for defining and identifying shortage events and propose further methodological improvements for more accurate shortage determination. Additionally, we elaborate on comparability requirements for multi-technological and multi-regional energy shortage analysis. In doing so, we aim to contribute to unifying disparate methodologies, harmonizing terminologies, and providing guidance for future research.

Increasing variable renewables in coal-based energy systems under high electrification in the transport and heating sectors: The case of Kosovo

The increasing penetration of variable renewables poses major challenges in energy systems with limited flexibility. However, there are many solutions to support variable renewable integration when utilizing potential synergies among the different energy sectors. This research examines the technical and environmental effects of electrifying the transport and heating sectors in a coal-based energy system with limited flexibility, aiming to support the integration of variable renewable energy. Scenario analysis is employed to evaluate the use of heat pumps with thermal storage (power-to-heat) for individual heating solutions, electric vehicles, and Vehicle-to-Grid in the transport sector. These measures are evaluated as the primary means for enhancing the energy system flexibility to accommodate a larger share of variable renewables. Additionally, a dynamic analysis was conducted on thermal power plant operational capacities and efficiencies under varying electrification rates and renewable energy shares. The analysis is developed in the EnergyPLAN model using Kosovo energy system as a case study. The results confirm that the electrification of the heating and transport sectors positively impacts the integration of variable renewable energy by reducing critical excess electricity production and CO2 emissions, while power-to-heat and Vehicle-to-Grid facilitate synergies among different energy sectors. However, scenarios with high shares of variable renewable energy present challenges for the nominal operation of thermal power plants, potentially leading to lower operational efficiencies and slightly higher CO2 emissions compared to scenarios where thermal power plant part-load efficiency remains unchanged.

Renewable-battery hybrid power plants in congested electricity markets: Implications for plant configuration

Examining coupled renewable-battery power plants (“hybrids”) in congested areas provides insights into a future of increased wind and solar penetration. Our study focuses on two types of congested regions, Variable Renewable Energy (VRE)-rich Areas and Load Centers, and explores likely plant configuration choices for developers and transmission network planners. This paper examines how hybrid value, comprising energy and capacity value, varies by plant configuration and congested region type considering factors such as storage duration, battery degradation, and ability to charge from the grid. We select plant locations from across the seven main U.S. independent system operators (ISOs). Hybrid value for each configuration is computed based on profit-maximizing plant operation given perfect foresight, according to observed wholesale power market real time prices from 2018 to 2021. In VRE-rich Areas, the median increase in energy value from extending storage duration from one to 4 h is 29.4 % for solar and 26.8 % for wind, assuming low battery degradation costs and storage sized to 100 % of the plant's nameplate generation capacity. Increasing storage duration beyond 4 h does not substantially increase its value from energy markets, even in VRE-rich Areas. We find that solar hybrids reach a 90 % capacity credit with 4 h of storage, while wind hybrids require 8 h of storage, based on the capacity factor of each hybrid during the top 100 net load hours.

Scenarios on future electricity storage requirements in the Austrian electricity system with high shares of variable renewables

This paper presents three scenarios (policy, renewables and electrification and efficiency) for transitioning to a 100 % renewable electricity sector in Austria, based predominantly on wind and photovoltaics, alongside sector-specific electrification. Considering renewable expansion targets and three distinctive weather years from an overall system perspective, the core objective is to minimize variable costs of electricity storage and dispatchable power plants. The model developed determines their optimal dispatch for meeting the underlying electricity demand each hour. Within the scenarios for renewable expansion, a special focus lies on integrating short-duration (batteries), medium-duration (pumped storage hydro) and long-duration (hydrogen) energy storage. Our analysis reveals the significant impact of weather patterns on renewable electricity generation, particularly the differences between winter and summer generation quantities. This necessitates seasonal balancing and the mitigation of extremes like low wind power events, which require corresponding backup capacities. This contrast is particularly evident when comparing the years 2030–2050, wherein in the latter, certain dispatchable generators are only utilized in one of the three underlying weather years during extreme weather conditions. In our paper, we demonstrate how, especially for hydrogen production and storage, weather conditions influence production levels and the re-electrification demand. The results indicate the feasibility of achieving a fully decarbonized energy system in Austria through suitable policy measures and expanded renewable generation, with long-duration storage playing a crucial role in seasonal balance and compensating for the absence of fossil fuel generation. Strategic planning is essential to aligning the expansion of renewable energy generation with the necessary flexibility.

Hydropower Enhancing the Future of Variable Renewable Energy Integration: A Regional Analysis of Capacity Availability in Brazil

As the share of variable renewables in the power system generation mix increases, meeting capacity requirements becomes challenging. In this context, hydropower reservoirs can play a vital role in integrating renewable energy due to their storage potential, contributing to meeting power supply criteria. However, given that reservoirs serve multiple purposes, various constraints can limit their capacity potential. This article introduces an analytical methodology that is designed to evaluate the maximum available power of hydro plants in critical scenarios. By applying concepts related to hydropower production calculations for the peak power demand and metrics evaluating the compliance with supply criteria, this study distinguishes itself from region-specific investigations. It conducts a generalized analysis of power availability across all regions of Brazil, with a focus on identifying the reasons for the most significant power losses and their specific locations. The results of this analysis demonstrate the feasibility of enhancing the available power of reservoirs, effectively addressing demand fluctuations, and sustainably improving energy security. This is particularly crucial in countries that are heavily reliant on renewables, including hydropower, for a huge portion of their electricity. The findings underscore the feasibility of increasing the penetration of variable renewable generation by optimizing the operation of existing hydropower plants. This optimization not only enhances energy security but also contributes to a more resilient and sustainable future, benefiting policy makers, energy planners, and stakeholders in the field of hydropower with reservoirs.

Complementarity for Wind Power in Turkey: A Correlation Analysis Using XGBoost

Generation from resources such as wind power and photovoltaics are highly variable and relatively unpredictable. This variability has its own cost such that when the wind and photovoltaics happen to be low due to weather conditions, some other energy source should substitute them to satisfy the demand via market forces. The question is, to which extent does the thermal leg or the reservoir storage hydropower plants fill or substitute the gap in such cases? This is examined in the literature as the complementarity between the variable renewables and alternative sources of energy. For the purpose of answering this question, using hourly data for the period between 2015 and 2020 from Turkey, generation from the thermal leg and generation from reservoir storage hydropower plants are predicted with XGBoost, a machine learning algorithm, for different price and generation levels of wind power. The results point to a positive correlation between wind and reservoir storage hydropower, which concludes as the absence of complementarity between wind power and reservoir storage hydropower for the Turkish case. We comment that the feed-in-tariff system which guaranteed a price in US dollar terms per KwH of energy from reservoir storage hydropower decreased the incentives for substitution of wind power, cancelling out the balancing function of the reservoir storage hydropower. On the other hand, for positive prices, the natural gas fueled plants seem to substitute %63-%116 of the loss in wind power and the rest of the thermal leg happens to substitute %43-%59 of the loss in wind power, according to our calculations. These results point to a complementarity (over-substitution in this case) between wind power and the thermal leg.

On representation of energy storage in electricity planning models

This paper considers the representation of energy storage in electricity sector capacity planning models. The incorporation of storage in long-term systems models of this type is increasingly relevant as the costs of storage technologies, particularly batteries, and of complementary variable renewable technologies decline. To value energy storage technologies appropriately in optimization models, a representation of linkages between time periods is required, breaking classical temporal aggregation strategies that greatly improve computation time. Our paper reviews approaches to address the problem of compressing chronology for large-scale electricity planning models and provides a generalized conceptual model, conditions for lossless aggregation, and key principles to evaluate aggregation methods. We propose a novel approach, which we call the “expected value” method, to maintain key economic characteristics of energy storage, variable renewables, dispatchable generation, and other power system resources at a relatively low computational cost and conduct numerical experiments to compare its accuracy and computational performance with other temporal aggregation methods.

Brine Valorisation Using Mechanical Vapor Compression Desalination: Approaches to Consider.

Water scarcity is one of the biggest challenges we are facing due to climate change: lack of rainfall and polluted water sources are an increasing reality worldwide. Sustainable Development Goals reinforce the urgency of dealing with this issue, targeting scientific community’s efforts towards solutions for this trending topic, where desalination of seawater is one of the main proposals. However, concerns regarding to the environmental effects of residual brines, generated in the desalination process, are emerging on the spots where this technology has been applied.To contribute to the implementation of desalination technologies, the valorisation of these residual brines brings the opportunity not only to reduce the volume of wastewater generated, but increasing its final concentrations and producing more freshwater from a residue. Nevertheless, it comes with the cost of higher energy demands than in the previous stage: the higher the concentration of the fluid, the higher its energy consumption. We can approach this challenge from two different perspectives, focusing on the final amount of concentrated residue or focusing on the energy demand of the installation.While focusing on reducing the volume of residue to its minimum expression is the most attractive option for concentrating the dissolved salts, it comes with the cost of excessive energy demands. On the other hand, focusing on reducing the power consumption of the installation allows the usage of variable renewables, in a more efficient way, allowing the carbon neutrality of emissions during its operation but obtaining a lower concentrated residue. By using a computational model of the installation, we can replicate its operation and compare results from both perspectives.In this paper we will use two scenarios with fixed conditions for a basic mechanical vapor compression (MVC) desalination plant modelled in TRNSYS, where we can observe the correlations between the final volume of residual brine and the energy consumption required for achieving those results. One of the scenarios will show the biggest final concentration, while the other one will consider the minimum operating conditions for the desalination plant. Apart from those results, there will be an analysis of environmental and economic advantages that can be achieved by the implementation of this technology, as well as an early approach towards the technical aspects involving the development of the model used for these calculations.

Using electrolytic hydrogen production and energy storage for balancing a low carbon electricity grid: Scenario assessments for India

Nuclear reactors and variable renewables will play a significant role in the global energy transition as providers of low carbon electricity to various end use sectors. Real time balancing of power demand and supply without modulation or curtailment is possible using electrolytic hydrogen plants and energy storage systems. The generation mix adopted and load profiles are unique to a country and this study considers the specific case of India. This work analyses the use of grid connected water electrolysers, grid scale battery storage, hydrogen storage and fuel cells as flexible loads and dispatch schemes for grid balancing. Based on postulated long term power generation scenarios for India, the minimum required system sizes for grid balancing are estimated and techno-economic uncertainties are assessed. The use of water electrolysers is prioritized to make use of excess power, while minimizing battery storage requirement. This scheme can potentially produce a substantial share of low carbon hydrogen in India for use in industrial decarbonization, thus reducing the need for additional generation infrastructure.

Impact of short-term wind forecast accuracy on the performance of decarbonising wholesale electricity markets

As the proportion of variable renewable generation capacity in our electricity systems rises, so too will the associated absolute forecast errors in their generation. This work quantifies the complex interactions between short-term renewable generation forecasts, short-term demand forecasts, generator unit commitment and economic dispatch in electricity systems with levels of variable renewable generation spanning 49–79% of annual electricity demand. When the short-term operational uncertainty caused by renewable generation becomes larger in absolute terms than that of demand, the accuracy of renewable generation forecasting has a critical influence on electricity market performance. That is, inaccurate short-term wind forecasts can increase hours of unserved energy and scarcity hours spent at market price cap, increase total system costs and prices, significantly increase returns to thermal generators and energy storage, reduce returns to wind generators, and increase greenhouse gas emissions slightly. For the generalised case study considered in this work, the value of improved short term wind generation forecasts looks to becomes significant once variable renewables generate more than roughly 60% of annual electricity demand. Reductions in average market prices of 5 $/MWh or more then appear plausible as acceptable levels of reliability are recovered. As such, improvements in short-term renewable generation forecasting are likely required in order to justify continued investment in variable renewables as the major means of achieving decarbonisation efficiently and reliably, and these could be achieved by any combination of improved forecasting, dispatch control or on-site firming.

Artificial Intelligence for Management of Variable Renewable Energy Systems: A Review of Current Status and Future Directions

This review paper provides a summary of methods in which artificial intelligence (AI) techniques have been applied in the management of variable renewable energy (VRE) systems, and an outlook to future directions of research in the field. The VRE types included are namely solar, wind and marine varieties. AI techniques, and particularly machine learning (ML), have gained traction as a result of data explosion, and offer a method for integration of multimodal data for more accurate forecasting in energy applications. The VRE management aspects in which AI techniques have been applied include optimized power generation forecasting and integration of VRE into power grids, including the aspects of demand forecasting, energy storage, system optimization, performance monitoring, and cost management. Future directions of research in the applications of AI for VRE management are proposed and discussed, including the issue of data availability, types and quality, in addition to explainable artificial intelligence (XAI), quantum artificial intelligence (QAI), coupling AI with the emerging digital twins technology, and natural language processing.

On static vs. dynamic line ratings in renewable energy zones

Scaling-up Variable Renewable Energy will face critical bottlenecks vis-a-vis requisite transmission hosting capacity. Network developments must navigate the complexity of encroaching on private land, risk disturbing sites of cultural significance, compete with other environmental (i.e. biodiversity) objectives, and endure backlash from directly affected communities. Transmission is costly and post-pandemic supply-chain constraints are sending equipment costs higher. Given time and cost risks, existing transmission networks and successful augmentations need to function at their outer operating envelope. In this article, a Renewable Energy Zone (REZ) is examined by comparing static, seaonal and real-time dynamic line ratings. Historically, seasonal line ratings in the Queensland region of Australia's National Electricity Market reflected the still, hot conditions that characterised critical event maximum demand days. Widespread take-up rates of rooftop solar PV has shifted maximum (grid-supplied) demand to the late-afternoon when wind speeds are rising, which also provides thermal cooling to transmission lines. Optimisation modelling suggests a shift from static to dynamic line ratings for a reference 275 kV radial REZ in Queensland can increase wind hosting capacity from ∼1700 MW to >2800 MW with limited change in the asset base. Dynamically adjusting Frequency Control Ancillary Services further increases VRE hosting capacity.

Comparative energy performance analysis of micro gas turbine and internal combustion engine in a cogeneration plant based on biomass gasification

With a view to replacing fossil fuels, biomass electricity generation worldwide has grown from 509 TWh in 2015 to 685 TWh in 2021 and an upward trend is expected for the next years. It is about dispatchable, low-emission power to complement generation from variable renewables. Although modern bioenergy is considered a stable and carbon-neutral source, there is a need to boost the efficiency of the Biomass-to-Energy (BtE) conversion technologies. Accordingly, in this modeling study, attention was drawn to biomass gasification for heat and power, with a special focus on the prime mover characterization for distributed generation. An internal combustion engine (ICE) and a micro gas turbine (mGT), having the same nominal capacity of about 240 kWel when fueled by natural gas (NG), were inserted into a two-way biomass gasification chain and hence fed by clean syngas deriving from a downdraft gasifier. Simulations of the main components of the thermal power plant (gasifier, syngas cleanup, power island) were validated against data available in the published literature and in technical sheets, for specific operating conditions. The next step was to evaluate the overall performance of the entire BtE chain in terms of electrical, thermal, and total efficiency, both at full and part load, in order to highlight the pros and cons of each generator, in a twofold perspective. The last goal was to simulate a load following strategy, for two typical cold and hot days. The results of the thermodynamic analysis indicate that ICE is better performing than mGT, in the simulated context where the power demand from the grid ranges from 80 kWel to 190 kWel, with an ambient temperature between 2 and 35 °C. ICE provides the best performance in CHP mode, with a total efficiency of 62–69%.

Enhanced system for hydrogen storage and conversion into green methanol in a geothermal environment

Variable Renewable Energy Sources are crucial for decarbonizing industries and efficient energy storage. Hydrogen storage technologies are limited in their large-scale capabilities. PtL technology can synthesize alternative fuels like methanol, which can be used in existing energy infrastructures to produce liquid fuel. The paper presents an innovative approach for utilizing in-situ thermal energy, using a hot reservoir rock (HRR) system for methanol synthesis at high temperature and pressure in an underground large-scale natural reservoir reactor. This approach aims to integrate renewable energy technologies into a single energy generation and fuel production system, including the direct utilization of renewable sources. Solutions from the oil and gas industry can be adapted to this action, such as continuous injection, alternate injection, separate injection, or chemical flooding. Conventional geothermal reservoirs, HDR systems, and depleted hydrocarbon reservoirs can be used as “underground reactors”. However, it was also noted that there are challenges, such as catalyst distribution and the complexity of reservoir pore space.