Variable Renewable Energy Generation Research Articles

Concurrent PV production and consumption load forecasting using CT‐Transformer deep learning to estimate energy system flexibility

AbstractThe integration of renewable energy sources (RESs) into power systems has increased significantly due to technical, economic, and environmental factors, necessitating greater flexibility to manage variable consumption loads and renewable energy generation. Accurate forecasting of solar energy production and consumption load is critical for enhancing power system flexibility. This study introduces a novel deep learning model, a spatial‐temporal hybrid convolutional‐transformer (CT‐Transformer) network with unique features and extended memory capacity. Additionally, a flexibility index (FI) is introduced to evaluate power system flexibility (PSF) based on the forecasting results. The CT‐Transformer forecasts PSF for the next 24 and 168 hours, using the FI to evaluate PSF based on forecasting results. The input data includes meteorological, solar energy production, load demand, and pricing data from France, comprising hourly data from 2015 and 2016 (about 17,520 entries). Data preprocessing involves correcting incomplete and irrelevant segments. The CT‐Transformer's performance is compared to other deep learning techniques, showing superior results with the lowest prediction error (2.5%) and a maximum error of 10.1% (MAE). It also achieved a prediction error of 0.08% for system flexibility, compared to the highest error of 0.96%. This research highlights the CT‐Transformer's potential for accurate RES and load forecasting and PSF evaluation.

Probabilistic assessment of short‐term voltage stability under load and wind uncertainty

AbstractContemporary electricity networks are exposed to operational uncertainties, which may jeopardise the stability of the power grid. More specifically, the increasing penetration level of variable renewable energy generation and uncertainty in load demand are key catalysts for these emerging stability issues. A mathematical relationship is established to track the system voltage trajectory with respect to variations in uncertain inputs (associated with wind speed, system load, and wind power penetration levels). Additionally, it demonstrates the consequences of varying uncertain inputs on the short‐term voltage response across different potential operating conditions. The theoretical proposition has further been verified by the simulation studies with two test power networks in DIgSILENT PowerFactory software. The simulation results revealed that uncertain injection sources significantly impacted the system voltage at the receiving end. High uncertainty in wind speed and system loads increased voltage recovery variation, causing delays in voltage response during low wind speeds and high system loads. Additionally, increased wind power penetration levels expanded voltage recovery uncertainties, resulting in decreased system voltage and potentially leading to voltage violations and instability at 30% wind power levels. Moreover, the results showed that the system's response time increased, and in some cases, it collapsed due to increased system capacity (>80%) and dynamic load (>75%), as well as encountering a large disturbance under uncertain circumstances.

The role of hydrogen as long-duration energy storage and as an international energy carrier for electricity sector decarbonization

With countries and economies around the globe increasingly relying on non-dispatchable variable renewable energy (VRE), the need for effective energy storage and international carriers of low-carbon energy has intensified. This study delves into hydrogen’s prospective, multifaceted contribution to decarbonizing the electricity sector, with emphasis on its utilization as a scalable technology for long-duration energy storage and as an international energy carrier. Using Japan as a case study, based on its ambitious national hydrogen strategy and plans to import liquefied hydrogen as a low-carbon fuel source, we employ advanced models encompassing capacity expansion and hourly dispatch. We explore diverse policy scenarios to unravel the timing, quantity, and operational intricacies of hydrogen deployment within a power system. Our findings highlight the essential role of hydrogen in providing a reliable power supply by balancing mismatches in VRE generation and load over several weeks and months and reducing the costs of achieving a zero-emission power system. The study recommends prioritizing domestically produced hydrogen, leveraging renewables for cost reduction, and strategically employing imported hydrogen as a risk hedge against potential spikes in battery storage and renewable energy costs. Furthermore, the strategic incorporation of hydrogen mitigates system costs and enhances energy self-sufficiency, informing policy design and investment strategies aligned with the dynamic global energy landscape.

Capacity contributions of Southern Oregon offshore wind to the Pacific Northwest and California

Variable renewable energy generation poses unique capacity challenges, which increasingly depend on weather events at varying timescales. Facilitated by transmission planning, geographic and technological diversity of the generation fleet may provide a mitigation to capacity shortfalls. In this work, offshore wind (OSW) energy is sited in the areas off the West Coast between Coos Bay, Oregon, and Crescent City, California. Three generation and transmission scenarios are modeled within the Western Interconnection: (i) 3.4 gigawatts (GW) of installed OSW capacity connected to Southern Oregon through a High Voltage Alternating Current (HVAC) Radial Topology in 2030; (ii) 12.9 GW of installed OSW capacity connected to Washington, Oregon, and California through a High Voltage Direct Current (HVDC) Radial Topology post-2030, and (iii) the same 12.9 GW connected to the same locations through a Multi-terminal DC (MTDC) Backbone Topology post-2030. Zonal dispatch simulations assuming coincident wind, solar, and hydropower production and loads over 18 meteorological years, accounting for temperature-dependent equipment derating and forced outages, serve as inputs to the Associated System Capacity Contribution (ASCC) methodology. The capacity credit is 33%, 25% and 34% for the 2030 HVAC Radial Topology, 2030+ HVDC Radial Topology, and 2030+ MTDC Backbone Topology, respectively. Transmission design is shown to mitigate the typical erosion of marginal capacity contribution as more OSW is developed, underscoring the opportunity for grid modernization while decarbonizing the generation mix.

A nationwide multi-location multi-resource stochastic programming based energy planning framework

With the escalating global energy demands, nations face greater urgency in diversifying their electricity market portfolio with various energy sources. The efficient utilization of these fuel resources necessitates the integrated optimization of the entire energy portfolio. However, the inherent uncertainty of variable renewable energy generators renders traditional deterministic planning models ineffective. Conversely, expansive stochastic models that capture all the complexities of the power generation problem are often computationally intractable. This paper introduces a scalable energy planning framework tailored for policymakers, which is adaptable to diverse geopolitical contexts, including individual countries, regions, or coalitions formed through energy trade agreements. A two-stage stochastic programming approach, including a scenario-based Benders decomposition method, is employed to achieve computational efficiency. Scenarios for representing parameter uncertainty are developed using a k-means clustering algorithm. An illustrative case study is presented to show the practical application of the proposed framework and its ability to inform policymaking by identifying actionable cost-reduction strategies. The findings underscore the importance of promoting resource coordination and demonstrate the impact of increasing interchange and renewable energy capacity on overall gains. Notably, the study shows the superiority of stochastic optimization over deterministic models in energy planning.

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.

Electricity sector impacts of water taxation for natural gas supply under high renewable generation

The future of energy development could be soon restrained by water scarcity. Shale gas, which is highly water-consuming in its extraction, is even more vulnerable. Thus, understanding the power system’s response to water constraints considering uncertainties from variable renewable energy generation becomes critical. This study presents a multi-stage stochastic Mixed Complementarity Problem for the energy sector, considering renewables variability and water scarcity’s impact on natural gas extraction. The power and natural gas sectors were modeled with hourly and daily resolution, respectively. Results demonstrate that stochastic planning enables smoother natural gas production and storage strategies, ensuring consistent operations with a narrower production range. Water taxation affects gas production and the generation mix, leading to electricity price changes. Gas-based electricity generation varies up to 16.2% based on water taxation and wind availability. Furthermore, water taxation of up to 20% can raise gas prices by up to 21.1%. This study underscores the need to integrate water scarcity considerations into energy planning, offering insights into sustainable decision-making, water resource management, reliable electricity generation, and price stability amidst evolving renewable portfolios.

The mid-transition in the electricity sector: impacts of growing wind and solar electricity on generation costs and natural gas generation in Alberta

In response to climate change, electricity grids are decreasing their carbon intensity with the addition of wind and solar variable renewable energy generation (VREN). This leads to a mid-transition period, where renewable energy is unable to satisfy electricity demand without contributions from other fossil sources such as natural gas, but also generates sufficiently to constrain conventional generation—changing their operating and market conditions. We use a simplified copper plate model, which scales up and down historical wind and solar generation, to examine how and when the patterns and generation costs for fossil fuel power could change by the increasing capacities of VREN on the relatively isolated Alberta electricity grid. We find that beginning at 20% VREN an increasingly diverse range and reduced hours of dispatched capacity is necessitated from the existing generation. However, even as capacity factors for fossil fuel generation decrease their costs remain reasonable and we found this to be a low-cost pathway for achieving moderate to deep emission reduction goals. A full 86% of demand could be met with VREN before generation costs exceeded 100$/MWh, allowing for an emissions reduction of 28.4–9 million tonnes yr−1 of CO2eq, on a lifecycle basis. In order to integrate the renewable generation, new and existing fossil fuel units will require market rules that incentivise flexibility and ensure they remain in place throughout the transitionary period as they are crucial to balance variable renewable generation.

Probabilistic spatiotemporal scenario generation method for dynamic optimal power flow in distribution networks

Due to the intricate intertwining of spatiotemporal characteristics and the substantial computational complexity caused by high dimensionality, the simultaneous consideration of both spatial and temporal correlations is a non-trivial problem in power system scheduling with variable renewable energy sources. This paper proposes a novel probabilistic spatiotemporal scenario generation (PSTSG) method for the dynamic optimal power flow problem in distribution networks, which generates probabilistic scenarios considering the spatial and temporal correlations among random variables simultaneously. First, static scenarios are generated by Latin hypercube sampling, and the probability of each static scenario is determined by copula-importance sampling theory, which is proposed to ensure the static scenarios yield the same probabilistic characteristics as the random variables. Next, a probability-based scenario reduction technique is implemented to retain effective scenarios and lower the computational burden. Then, multiple linear regression generalizes the static scenarios into dynamic ones with the same probabilities. Finally, a spatiotemporal scenario-based stochastic optimization is proposed for the dynamic optimal power flow problem, which considers uncertainties in variable renewable energy generation and aims to balance the output of controllable generators, renewable energy curtailment, and load shedding. Numerical simulations in a modified IEEE 33-node distribution network show that the proposed approach outperforms the existing methods that do not simultaneously consider spatial and temporal correlations in terms of computational efficiency and accuracy, proving that the proposed PSTSG method can efficiently capture the spatial and temporal correlation so as to make the optimal scheduling decision.

Electric-gas infrastructure planning for deep decarbonization of energy systems

The transition to a deeply decarbonized energy system requires coordinated planning of infrastructure investments and operations serving multiple end-uses while considering technology and policy-enabled interactions across sectors. Electricity and natural gas (NG), which are vital vectors of today’s energy system, are likely to be coupled in different ways in the future, resulting from increasing electrification, adoption of variable renewable energy (VRE) generation in the power sector and policy factors such as cross-sectoral emissions trading. This paper develops a least-cost investment and operations model for joint planning of electricity and NG infrastructures that considers a wide range of available and emerging technology options across the two vectors, including carbon capture and storage (CCS) equipped power generation, low-carbon drop-in fuels (LCDF) as well as long-duration energy storage (LDES). The model incorporates the main operational constraints of both systems and allows each system to operate under different temporal resolutions consistent with their typical scheduling timescales. We apply our modeling framework to evaluate power-NG system outcomes for the U.S. New England region under different technology, decarbonization goals, and demand scenarios. Under a global emissions constraint, ranging between 80%–95% emissions reduction compared to 1990 levels, the least-cost solution relies significantly on using the available emissions budget to serve non-power NG demand, with power sector using only 14%–23% of the emissions budget. Increasing electrification of heating in the buildings sector results in greater reliance on wind and NG-fired plants with CCS and results in similar or slightly lower total system costs as compared to the business-as-usual demand scenario with lower electrification of end-uses. Interestingly, although electrification reduces non-power NG demand, it leads to up to 24% increase in overall NG consumption (both power and non-power) compared to the business-as-usual scenarios, resulting from the increased role for CCS in the power sector. The availability of low-cost LDES systems reduces the extent of coupling of electricity and NG systems by significantly reducing fuel (both NG and LCDF) consumption in the power system compared to scenarios without LDES, while also reducing total systems costs by up to 4.6% for the evaluated set of scenarios.

Market Mechanism Design of Inertia and Primary Frequency Response With Consideration of Energy Market

The shortage of inertia and primary frequency response (IPFR) will be more severe in future power systems since conventional fossil-based synchronous generators are gradually being replaced by variable renewable energy (VRE) generators. To relieve the shortage of IPFR, corresponding market mechanisms should be designed and incorporated to motivate appropriate provision from various sources. The mechanism of IPFR provision from different types of generators and its tight relation with energy production should receive particular attention. This paper proposes a novel IPFR market mechanism in which the energy market is taken into joint consideration. The virtual inertia and droop factor provided by VRE generators are defined and introduced, considering its dominant share in future power systems. A differentiated pricing scheme is designed towards incentive compatibility, considering provision from different types of generators with different quality levels and opportunity costs. Then, the proposed IPFR market mechanism is formulated, and a modified piecewise linearization method is utilized to simplify the non-linear nadir constraints. Finally, the model is tested on a modified IEEE 30-bus system according to historical data in CAISO. The results indicate the proposed mechanism could increase the utilization of VREs, decrease system operation costs, and guarantee reasonable payback for various types of generators.

Techno-economic analysis of a combined power plant CO2 capture and direct air capture concept for flexible power plant operation

The electric power sector must be deeply decarbonized at a reasonable cost to achieve economy-wide decarbonization goals via sustainable electrification of other sectors. While variable renewable energy generation is expected to dominate grid decarbonization efforts, variability creates the need for supply- and demand-side technologies that can operate flexibly to balance the system. This paper proposes a new concept for power plant flue gas capture integrated with a novel lime-based direct air capture technology to enable flexible operation of the power plant and achieve negative emissions under all operating scenarios. Steady-state models are developed, and sensitivity analyses are conducted on key process variables to investigate system performance. The results, presented at three different power plant loading levels (100 %, 40 %, and 0 %), demonstrate negative emissions of -0.188 tCO2/MWh at 100 % loading and -2.087 tCO2/MWh at 40 % loading. Economic modeling suggests the need for carbon credits exceeding $170/tCO2 to achieve positive net present values.

Integration of ocean thermal energy conversion and pumped thermal energy storage: system design, off-design and LCOS evaluation

Increasing the penetration of Variable Renewable Energy (VRE) in electric generation systems is a fundamental goal in reducing greenhouse gases emission. To reduce power fluctuations in electricity networks and avoid curtailment, large-scale energy storages represent one of the most promising solutions. Thermally-Integrated Pumped Thermal Energy Storage (TI-PTES) systems are an interesting technology that can be used for this scope if the heat source adopted for thermal integration can provide significant thermal power. The ocean temperature gradient in tropical areas is an attractive heat source to be coupled with the PTES system to realise efficient electric storage when integrated with an Ocean Thermal Energy Conversion (OTEC) system. In this study, a heat pump refrigerated by the warm tropical surface water uses electricity surplus from VRE to heat an amount of water contained in an end-life cargo ship used as water storage. The system discharges the stored energy through an ORC cycle refrigerated by the cold deep seawater when VRE production is low. A preliminary sensitivity analysis of the storage size and temperature is proposed through detailed system modelling to define the optimal design and layout. Therefore, the part-load analysis of the system is assessed to characterise the off-design performances and evaluate the potentialities of this system when applied to a plausible case study that includes VRE generation and an electric demand profile. Finally, the Levelised Cost Of Storage (LCOS) is evaluated and compared to other storage technologies. Results show that the round-trip efficiency may achieve values higher than 60 %, and an equivalent electric battery capacity of 20 MWh is feasible using end-life ships acting as energy storage. In contrast, the obtained LCOS of 388 €/MWh is still not competitive in the energy market. However, since tropical areas have high energy prices, considering this application for remote island electrification could be an interesting solution.

(Invited) Proton Exchange Membrane Electrolyzers Based on Sub-Micron Thick Membranes

Significant decreases in the price of electricity from solar photovoltaics and wind are enabling concurrent decreases in the cost of clean hydrogen production by water electrolysis. However, to meet the US Department of Energy’s Hydrogen Shot Initiative target for levelized cost of hydrogen production of < $1 per kg of hydrogen by the year 2030,[1] it will also be necessary to drive down the capital costs of water electrolyzers. Reducing capital costs is especially important for scenarios where close to 100% of the electricity is provided by variable renewable energy generators, which greatly limits the capacity factor of the electrolyzer.[2] Towards this end, our team is exploring a proton exchange membrane (PEM) electrolyzer architecture based on ultrathin (< 1 micron) membranes. Modeling is used to show that defect-free membranes possessing appropriate proton and hydrogen transport properties present opportunities to decrease membrane resistances < 80% relative to conventional Nafion membranes, which can subsequently allow for operation at > 4 A cm-2 while maintaining the same efficiencies achieved by today’s commercialized PEM electrolyzers operated at < 2 A cm-2. Additionally, this talk will describe modeling and experimental efforts that address the viability of using sub-micron thick membranes that can operate with H2 crossover rates < 1%.

British imbalance market paradox: Variable renewable energy penetration in energy markets

The expansion of variable renewable energy (VRE) generation propagates numerous challenges for national energy systems. Despite recent years of VRE expansion and declining coal utilisation in the overall market profile, coal energy generation has maintained and grown its position as a marginal seller in the imbalance market. Coal’s disproportionate resurgence as a bidder of later resort in the imbalance market also represents a shift in its bidding behaviour. A comparative breakdown of Britain’s overall market with that of Germany, followed by a specific investigation of Britain’s imbalance market provides insight into changing roles of VRE, fossil fuelled energy, and compensation technologies. Historically, VRE trends in the British and German markets have been broadly consistent. Recently, increasing distress in Britain’s overall market is found to result in the increased use of high pollution technologies to meet imbalances. As a result, the composition of the overall and imbalance markets have increasingly diverged, and although the dominance of gas in the latter is expected, the resurgence of coal energy is more remarkable. Thus, while the proportion of generation by renewables has continued to increase, fossil fuelled (notably including coal) capacity, and its associated infrastructure costs and influence as the price setting marginal seller, remains dominant in the imbalance market.

Locational and market value of Renewable Energy Zones in Queensland

Efficient coordination in transmission planning and locating variable renewable energy (VRE) generation is important in transitioning to a low carbon electricity system. Renewable Energy Zones (REZ) provide an opportunity to strategically augment and expand the existing transmission network to maximise use of the available renewable resources. The Queensland region of Australia’s National Electricity Market provides a unique case for analysis, where complementary patterns of wind and solar supply exist across a broad geographical area. This article presents new information about the nine proposed REZ across the region and their utility in supplying energy as the incumbent fleet of baseload generators is forecast to retire. Understanding their locational and market value provides insight into the underlying cost of energy and its ability to satisfy energy demands. The recent entry cost shocks impacting the VRE industry in the post-pandemic recovery have been quantified, where increases of 23%–44% to the cost of energy have been observed. These increases have been driven by shifts in the capital and operating costs for new projects, which are compounded by the simultaneous increases to the cost of capital. Real world analysis has occurred to support the modelled outcomes and highlight the value of REZ in Queensland.

VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene

The Fluctuations in demand and weather conditions have a significant impact on the frequency and the voltage of Algeria's isolated PIAT power grid. To maintain stability and reliable power supply, it is crucial to keep these quantities close to their expected levels. An automatic (FRR) is employed to regulate real-time frequency deviations caused by integrating variable renewable energy (VRE), specifically wind and solar power in the Kabertene region. In order to mitigate wind power fluctuations, a power system stabilizer is implemented, which helps dampen oscillations. The use of Maximum Power Point Tracking (MPPT) techniques optimizes the extraction of power from solar panels under varying conditions. For efficient scheduling and dispatch of VRE generation, particle swarm optimization (PSO)-based algorithms are used. These algorithms ensure optimal utilization of renewable energy sources by considering their intermittent nature. This study proves the effectiveness of these techniques in enhancing grid stability, reducing frequency deviations, and improving VRE integration. Valuable insights are provided on their practical implementation, playing a crucial role in transitioning to a cleaner and more sustainable energy system.

Techno-Economic Analysis of Reversible and Paired Solid Oxide Cell Systems for Hydrogen Production

The use of green hydrogen to decarbonize the U.S. economy has been steadily gaining commercial interest as the cost and availability of renewable electricity decreases. At present, technologies can only take advantage of low electricity prices at low capacity factor, due to its intermittent availability, negatively impacting the economics. Reversible solid-oxide cell (r-SOC) based energy conversion systems can potentially solve this problem by producing power when electricity prices are high and hydrogen when they are low. However, the long-term operation of r-SOC systems has not been fully investigated compared to paired SOFC and SOEC units. This paper presents techno-economic results for two SOC-based hydrogen and power co-generation concepts. These technologies primarily generate hydrogen through solid oxide electrolysis but have the capacity to switch to power if signaled by the market. This operational flexibility provides a significant benefit to an electric grid with a growing share of variable renewable energy generation.

An Analysis of the Effects of Renewable Energy Intermittency on the 2030 Korean Electricity Market

Republic of Korea has unique geographical characteristics similar to those of an island, resulting in an isolated power system. For this reason, securing sufficient operating reserves for the system’s stability and reliability in the face of the intermittency of increasing variable renewable energy (VRE) is paramount, and this will pave the way to achieving the nation’s decarbonization target and carbon neutrality. However, the current reserve-operation method in Republic of Korea does not take into account energy-system conditions, such as the intermittency of the VRE. Therefore, this paper presents an analysis of the impact of changes in reserve-operation methods on the electricity market in the future Republic of Korean power system, with the increased levels of VRE that are currently envisioned. Specifically, three reserve-operation methods, including Korea’s current reserve-power-operation standards, were applied to the two power-system plans announced by the Korean government to analyze the annual generator operation and costs. The analysis results show that securing reserves proportional to the VRE would exert negative effects, such as increased power-generation costs and the curtailment of nuclear and VRE generation. These results can contribute to the estimation of operational reserves needed for high levels of VRE and to the design of new the Korean reserve market, to be introduced in 2025.

Evaluating energy flexibility requirements for high shares of variable renewable energy: A heuristic approach

Efforts to reduce carbon intensity of electricity involve increasing shares of variable renewable energy (VRE), including a trend towards decentralized generation. Ensuring their high utilization necessitates addressing generation variability at different spatial and temporal scales, likely involving a coordination of multiple systems (e.g. flexible loads, storage, dispatchable generation). This paper presents a methodology for estimating the energy flexibility required from such a synchronized system. The simple data-based approach uses local load and VRE production patterns, and provides a regional assessment considering (1) indicators to evaluate energy flexibility requirements based on VRE self-consumption (2) visualization methods to observe consumption and production patterns’ impact on flexibility requirements across day/week/year and (3) simple algorithms to estimate the energy flexibility requirements at different timescales. The approach is demonstrated for three Swiss distribution system operators, for both current and increased shares of VRE generation. The largest benefits for optimal self-consumption are realized for the energy flexibility timescale of 6–12 h. Medium- and long-term (seasonal) storage appears beneficial at VRE penetration levels beyond 40%. The proposed framework can be readily utilized to assess energy flexibility requirements of different regions, and serve as a basis for identifying a suitable mix of strategies needed to address them.