Renewable Curtailment Research Articles

Powering hydrogen refueling stations with local renewable curtailment – A Lanzhou case study

To promote a hydrogen economy in the near term, in this work, curtailed power from renewable generation in Northwest China is used as the energy source for electrolytic H2. The feasibility of involving methanol as a liquid energy carrier is also explored considering the relatively high cost and safety risk of H2 storage and transportation. Four technology routes including both centralized and distributed versions of pure hydrogen and methanol-mediated supply chains for local H2 consumption at refueling stations are investigated with real-world scenarios in Lanzhou, China. The capacity of existing solar photovoltaics (PVs) is obtained from remote sensing images and a generic supply chain optimization model is developed to compute the minimum levelized cost of hydrogen (LCOH) for each route. Greenhouse gas (GHG) emissions and safety considerations are also assessed for each route. It was found that the green methanol route is the safest with GHG emissions being higher than expected.

Deep Low-Carbon Economic Optimization Using CCUS and Two-Stage P2G with Multiple Hydrogen Utilizations for an Integrated Energy System with a High Penetration Level of Renewables

Integrating carbon capture and storage (CCS) technology into an integrated energy system (IES) can reduce its carbon emissions and enhance its low-carbon performance. However, the full CCS of flue gas displays a strong coupling between lean and rich liquor as carbon dioxide liquid absorbents. Its integration into IESs with a high penetration level of renewables results in insufficient flexibility and renewable curtailment. In addition, integrating split-flow CCS of flue gas facilitates a short capture time, giving priority to renewable energy. To address these limitations, this paper develops a carbon capture, utilization, and storage (CCUS) method, into which storage tanks for lean and rich liquor and a two-stage power-to-gas (P2G) system with multiple utilizations of hydrogen including a fuel cell and a hydrogen-blended CHP unit are introduced. The CCUS is integrated into an IES to build an electricity–heat–hydrogen–gas IES. Accordingly, a deep low-carbon economic optimization strategy for this IES, which considers stepwise carbon trading, coal consumption, renewable curtailment penalties, and gas purchasing costs, is proposed. The effects of CCUS, the two-stage P2G system, and stepwise carbon trading on the performance of this IES are analyzed through a case-comparative analysis. The results show that the proposed method allows for a significant reduction in both carbon emissions and total operational costs. It outperforms the IES without CCUS with an 8.8% cost reduction and a 70.11% reduction in carbon emissions. Compared to the IES integrating full CCS, the proposed method yields reductions of 6.5% in costs and 24.7% in emissions. Furthermore, the addition of a two-stage P2G system with multiple utilizations of hydrogen further amplifies these benefits, cutting costs by 13.97% and emissions by 12.32%. In addition, integrating CCUS into IESs enables the full consumption of renewables and expands hydrogen utilization, and the renewable consumption proportion in IESs can reach 69.23%.

Model coupling and comparison on optimal load shifting of battery electric vehicles and heat pumps focusing on generation adequacy

The energy transition fosters a dynamic landscape marked by renewable energy, electrification, and complex interactions among actors and technologies. Employing model experiments and comparisons shows promise for exploring these connections and enhancing model clarity and precision. This study adopts a multi-model approach, integrating a model comparison to probe how the electrification of demand-side sectors and strategic load shifts of battery electric vehicles and heat pumps might impact Germany's generation adequacy by 2030. Specific demand models from the transport and heating sectors and a future load structure projection model are interlinked with three electricity system models. The comparative analysis of the three electricity system models unveils discrepancies in dispatch decisions for power plants, flexibility options' load shifts, and their effects on generation adequacy, directly tied to model attributes.The comparison underscores methodological variations (linear optimization versus agent-based simulation, myopic foresight versus perfect foresight) as pivotal, emphasizing the significance of considering load change and start-up costs for power plants. The results show that with optimized load shifting by electric vehicles and heat pumps, the adequacy of power generation is less strained despite increased electricity demand. Moreover, load shifts mitigate curtailment of renewables and consumers, reducing carbon emissions by lowering conventional power generation.

Revealing electricity conversion mechanism of a cascade energy storage system

With the increasing penetration of renewable energy in the power system, it is necessary to develop large-scale and long-duration energy storage technologies. Deploying pump stations between adjacent cascade hydropower plants to form a cascade energy storage system (CESS) is a promising way to accommodate large-scale renewable energy sources, yet the mechanism how renewable curtailment is converted to hydroelectricity is still unclear. In this paper, we aim to clarify this mechanism by evaluating the CESS's long-term operational efficiency and changes compared to the cascade hydropower system. First, operational features and principle of the CESS was outlined. Then, long-term operations of the CESS and cascade hydropower system were, respectively, optimized using a simulation-based optimization framework. Finally, the operational efficiency of the CESS, defined as a ratio of reduced renewable energy curtailment to increased hydropower production, was calculated based on the above two optimized operation results. China's Longyangxia-Laxiwa CESS was selected as a case study. Results show that: (1) long-term operational efficiency of the CESS reached 81.6 %, i.e., 81.6 % of the curtailed renewable could be converted to hydroelectricity; (2) the increase in hydropower production was mainly attributed to the upper hydropower plant, accounting for about 96.5 % of the total increment; and (3) the increase in generation flow was the main factor to impact the increased hydropower production of the upper plant, although it could decrease the hydropower plant's hydraulic head.

Optimising microgrid energy management: Leveraging flexible storage systems and full integration of renewable energy sources

The significance of microgrid systems has grown considerably. This research proposes an innovative approach to manage uncertainty in microgrids by employing energy storage systems as the exclusive flexible resource. To address this challenge, a mathematical problem is formulated as a two-stage stochastic programming model, considering two uncertainties in the microgrid: wind and photovoltaic production. The microgrid system encompasses multiple components, including a diesel generator, a microturbine, wind and photovoltaic power generation, an energy storage system, and the microgrid’s demand. Notably, the microgrid exhibits two distinctive features: (i) the complete integration of wind and photovoltaic production, and (ii) the utilisation of an energy storage system as the sole flexible resource. The objective is to minimise the expected cost of the microgrid system while determining the optimal capacity of the energy storage system to meet the energy balance constraint. This constraint takes into account the varying scenarios of wind and photovoltaic production. The decisions are taking for a duration of 8760 h, a long-term evaluation. A case study is presented for actual data from Greece and the results show high volatility of the renewable energy sources implies higher energy storage system capacity as a sole flexible source for avoiding renewable curtailment.

Frequency-constrained scheduling based on synchronous generators’ dynamic response in low inertia systems

Ensuring safe control over post-fault frequency dynamics is a complex task due to the future decline of inertial response and governor response in low-carbon power networks. This paper proposes a novel system scheduling model which incorporates a detailed description of the inertial and governor’s response of conventional generators as well as the system-level frequency dynamics. The proposed methodology is able to consider the typical overshoot of the governor’s response to optimally allocate enough headroom among generators. In addition, a set of constraints on the frequency deviation and on its rate of change allows to optimize the energy production whilst maintaining the security of the system. Furthermore, the paper develops a constraint on the rise time of the governor’s response. Hence, the proposed methodology allows to enforce specific dynamics concerning the governor’s response. The proposed model is applied to analyze a 2030 GB low-carbon scenario. Results demonstrate the value of the proposed methodology e.g. as reduction of system operational cost and curtailment of renewables. Results also indicate value of well formulating the post-fault rate of change of frequency and the impact of limitations to the dynamic response of conventional generators.

Towards low-carbon power networks: Optimal location and sizing of renewable energy sources and hydrogen storage

This paper proposes a systematic optimization framework to jointly determine the optimal location and sizing decisions of renewables and hydrogen storage in a power network to achieve the transition to low-carbon networks efficiently. We obtain these strategic decisions based on the multi-period alternating current optimal power flow (AC MOPF) problem that jointly analyzes power network, renewable, and hydrogen storage interactions at the operational level by considering the uncertainty of renewable output, seasonality of electricity demand, and electricity prices. We develop a tailored solution approach based on second-order cone programming within a Benders decomposition framework to provide globally optimal solutions. In a test case, we show that the joint integration of renewable sources and hydrogen storage and consideration of the AC MOPF model significantly reduces the operational cost of the power network. In turn, our findings can provide quantitative insights to decision-makers on how to integrate renewable sources and hydrogen storage under different settings of the hydrogen selling price, renewable curtailment cost, emission tax price, and conversion efficiency.

Fairness and usability analysis in renewable power curtailment: A microgrid network study using bankruptcy rules

The integration of renewable energy sources globally has effectively reduced carbon emissions and enhanced community self-sufficiency through local resource use. However, challenges arise with higher renewables penetration, especially at local and distribution levels. Curtailment of renewables becomes necessary during peak generation intervals to ensure power quality and system stability, raising fairness concerns. This study examines the feasibility of using bankruptcy rules to address fairness concerns in renewable power curtailment in microgrid networks. Four bankruptcy rules - proportional, constrained equal awards (CEA), constrained equal losses (CEL), and sequential priority rules - are evaluated using the IEEE 33-bus system transformed into a network of five microgrids with solar and wind generators. Voltage profiles of microgrid networks in Detroit and Chicago under high renewable penetration are assessed, and bankruptcy rules are applied to curtail surplus renewable power. The fairness of each rule is analyzed using Jain's fairness index, while a usability index evaluates power usability across microgrids under different bankruptcy rules. Simulation results show that the proportional and CEA rules exhibit better fairness and equal usability among microgrids, with voltage profiles just below the upper bound. Conversely, the priority rule improves voltage profiles at the expense of fairness and equal usability.

Energy systems capacity planning under high renewable penetration considering concentrating solar power

With the rapid development of renewable generation and the promotion of “Clean Heating”, the uncertainty of renewables as well as rising energy demand has posed significant problems to the energy system’s economical and flexible operation. As a renewable energy generation technology, concentrating solar power (CSP) with thermal energy storage (TES) offers a promising approach by providing operational flexibility and thermal energy supply to the energy system. We propose a long-term high-resolution planning model considering the operational characteristics of CSP and improved flexibility constraints of energy systems under high renewable penetration to meet the electricity and heat demand simultaneously in this paper. By applying the proposed model to a typical “Clean Heating” area in China, it demonstrates that the optimal deployment by integrating CSP can reduce the peak-valley depth of coal units, minimize the renewable curtailment and carbon emissions by 37.64 % and 19.05 % respectively with more than 5.98 % cost reduction at 85 % renewable penetration compared with the base scenario, which provides an economic and stable zero-carbon pathway for multi-energy systems.

Concentrated solar power for a reliable expansion of energy systems with high renewable penetration considering seasonal balance

With the increasing proportion of variable renewable energy characterized by fluctuation and the promotion of the “Clean Heating” policy, the problem of seasonal energy imbalance of the system has become increasingly challenging. There is a lack of effective means to mitigate this challenge under the background of gradual compression of the construction space for traditional thermal units. Concentrated solar power (CSP) is a promising technology to replace thermal units by integrating emergency boilers to cope with extreme weather, and can meet long-time energy balance as a seasonal peak regulation source. In this paper, we propose a long-term high-resolution expansion planning model of energy systems integrating CSP to address seasonal energy imbalances. The model takes into account both investment and operation considerations in full hourly resolution for the whole year based on a fast cluster optimization method. With the projection to 2050, we take the energy system in Xinjiang province which is a typical area of the “Clean Heating” project with rich irradiance as a case study. It shows that the optimal deployment of CSP and electric boiler (EB) can result in a 8.73 % reduction in costs, a 19.72 % decrease in the peak-valley difference of net load, and a substantial 58.24 % reduction in renewable curtailment at 65 % renewable penetration compared to the base scenario.

As Grids Reach 100% Renewable at Peak, Growing Curtailment of 8 Gigawatts Looms as a Challenge to Decarbonization

In April 2022, the California Independent System Operator (CAISO) power grid reached momentary peaks of 100% renewable energy for the first time. After a year, momentary 100% supply from renewables isn't a news any more, and CAISO reported record wind and solar renewable curtailment of 606 GWh (March 2023) and 686 GWh (April 2023). In addition, peak renewable coincided with curtailment rates of 8 GW in April 2023. Our prior studies documented monthly-peak renewable curtailment growth of 40% annually (23 GWh in March 2015 growing to 82 GWh in March 2017). Updating for 2018-2023 shows that 40% annual growth has continued through April 2023 and with it, CAISO has reached an average sunlight hours curtailment rate of 2 GW. If this 9-year trend continues unchecked for the next 5 years, monthly curtailment is projected to reach 3.3 TWh in both March and April of 2028, an average sunlight curtailment rate of nearly 11 GW. We analyze causes of increased curtailment, and discuss its likely future trajectory (growth). We also discuss the challenges its growth represents for grid decarbonization. Finally we outline the difficulties in reducing curtailment growth and highlight several new opportunities for power grids and computing systems.

Thermo-economic design of an electric heater to store renewable curtailment in solar power tower plants

Thermo-economic design of an electric heater to store renewable curtailment in solar power tower plants

Batteries or silos: Optimizing storage capacity in direct air capture plants to maximize renewable energy use

Direct air capture (DAC) of carbon dioxide is among the technologies that is forecast to play a major role in achieving the global ambition to constrain atmospheric temperature rise to below two degrees Celsius by 2100. However, DAC is an energy intensive chemical process, whose designs are currently incompatible with intermittent renewable energy (RE) sources. This research develops a model to enable the flexible operation of DAC, to maximize RE usage. A new model of the chemical process flow of a liquid solvent DAC that includes silos to store CaCO3 and CaO is developed. A linear programming optimization model that minimizes energy costs while achieving the CO2 capture targets of the DAC plant is developed. Scenario analysis establishes the storage silo size and battery storage size needed to reduce renewable energy curtailment to zero for a given RE profile. Simulations with a representative 336-hour RE profile reveal that two silos of sizes 660 tons and 370 tons would be needed to support flexible DAC plant operations and reduce RE curtailment to zero. For the same profile, a 355 MWh/65 MW battery would be required to achieve zero renewable curtailment. The results demonstrate that flexible operation of DAC is achievable, and DAC plants can adapt to variable RE without the need for battery energy storage. Furthermore, considering the scale of storage needed to minimize RE curtailment in a commercial-scale DAC plant, the results suggest that using physical storage silos could be more cost-effective than using battery energy storage.

Power Flow Optimization with Energy Storage - Sal Island Case Study

The correlation between energy costs and the country's economic competitiveness is an unquestionable reality also responsible for the improvement of the population's life conditions. In the past Cape Verdean electric power system (EPS), expansion was based on fossil-fuel power plants, nowadays it shifted to renewable energy (RE) which is abundant in the Cape Verde archipelago. However, no reduction in the electricity tariffs occurred, due to renewable curtailment and other pendent questions related to power transmission losses in the EPS. This paper presents an approach, that supports an implementation of a distributed electric energy storage system (ESS) on the Sal Island of Cape Verde archipelago, as a solution to increase the RE integration and power Transmission congestion relief. Thus, a power flow optimization is only achievable by storing excess RE as near as possible to consumption buses that can reduce overall transmission losses. The most advantageous allocation of ESSs along the EPS buses is combinational which faces a maximization of transmission loss reduction and minimization of ESS investment capital. The proposed tool to manage the “trade-off” between cost and avoided losses, is based on a genetic algorithm (GA) that is broadly applied to multi-objective problems like this.

Distributionally Robust Optimal Power Flow via Ellipsoidal Approximation

This paper proposes a distributionally robust joint chance-constrained AC optimal power flow to manage the risk of operational limits violations which are caused by uncertain renewable generation. By determining the dispatch schedule, this approach can help to decrease the risk of renewable curtailment, load shedding, or emergency redispatch in real-time. To model the proposed approach, the renewable uncertainty is first modeled as a distributionally robust ellipsoidal bound based on the Wasserstein metric. This bound is built upon a limited historical renewable forecast errors dataset without any assumption on the probability distribution of uncertainty. Then, this uncertainty bound is adopted within a semidefinite relaxation of the optimal power flow. The system responses to the renewable generation forecast errors are modeled as linear sensitivities, where all conventional generators are responsible for compensating the impacts of renewable forecast errors. Numerical experiments on IEEE 14-bus and 118-bus systems show the validity and scalability of the proposed method. Furthermore, the effectiveness of the proposed approach in terms of meeting probabilistic guarantees, cost-effectiveness and computational time is also demonstrated in the experiments.

The role of power – to – hydrogen in carbon neutral energy and industrial systems: Case Finland

To combat climate change, decarbonization measures are undertaken across the whole energy sector. Industry and transportation sectors are seen as difficult sectors to decarbonize, with green hydrogen being proposed as a solution to achieve decarbonization in these sectors. While many methods of introducing hydrogen to these sectors are present in literature, few system-level works study the specific impacts of large-scale introduction has on power and heat sectors in an energy system. This contribution examines the effects of introducing hydrogen into a Finnish energy system in 2040 by conducting scenario simulations in EnergyPLAN – software. Primary energy consumption and CO2 emissions of the base scenario and hydrogen scenarios are compared. Additionally, the differences between a constant and flexible hydrogen production profile are studied. Introducing hydrogen increases electricity consumption by 31.9%, but reduces CO2 emissions by 71.5% and fossil energy consumption by 72.6%. The flexible hydrogen profile lowers renewable curtailment and improves energy efficiency but requires economically unfeasible hydrogen storage. Biomass consumption remains high and is not impacted significantly by the introduction of hydrogen. Additional measures in other sectors are needed to ensure carbon neutrality.

Study on the electricity spot market trading mechanism considering the proportion of renewable energy consumption quota

The challenge of harmonizing the integration of renewable energy in market-driven transactions and assured accommodations presents a predicament in the development of China's electricity spot market. Moreover, as renewable energy penetration escalates, the issue of reserve undeliverability due to transmission congestion diminishes the power system's capacity to utilize renewable energy resources. To address this concern, this study introduces a secondary clearing mechanism for the electricity spot market, taking into account the proportion of renewable energy consumption quotas. Based on the first clearing, when renewable curtailment occurs, the bid pricing of abandoned power units undergoes flexible adjustment through the optimization of the price correction coefficient, followed by the execution of a secondary clearing utilizing the revised bidding information to fulfill the stipulations of the renewable energy consumption quota ratio. Drawing on the outcomes of the two-stage clearing, an incentive-compatible settlement compensation mechanism is proposed to preserve the impartiality of the market operator. The spot market clearing model accounts for the transmission safety margin, effectively mitigating the likelihood of transmission congestion, reserve inaccessibility, and renewable energy curtailment issues in real-time dispatching. Finally, a modified IEEE 30-bus system serves to substantiate the efficacy of the proposed market mechanism.

The potential assessment of pump hydro energy storage to reduce renewable curtailment and CO2 emissions in Northwest China

Pumped hydro energy storage (PHES) can effectively alleviate the renewable curtailment and resource waste caused by expansion of wind and solar-based renewable energy (RE) sources. However, the influences of regional hydrological characteristics, operational characteristics of PHES units, and power supply-demand balance on the regulating effect of PHES have been neglected. In this paper, an improved hybrid power system dispatch model (Dispa-set) that considers regional hydrological characteristics, unit operational characteristics, and RE curtailment penalty is proposed. The potential and limitations of PHES on reducing renewable curtailment and carbon emissions in four Northwest provinces (FNP) during the 14th Five-Year Plan (FYP) are evaluated through 6 sub-scenarios. Studies have shown that increasing PHES can effectively reduce renewable curtailment and carbon emissions, but uncoordinated development of PHES and RE results in resource waste and slows down carbon reduction. For example, a 10% increase in PHES during the 14th FYP could increase renewable curtailment in Qinghai by 1.1% and CO2 emissions in Gansu by 0.05%, due to uncoordinated development, demand for electricity supply, and regulated power sources. Therefore, combining PHES development with regional hydrological and operational characteristics is essential to achieve coordinated development with RE and unlock technology, economic, and environmental benefits.

High-dimension tie-line security regions for renewable accommodations

Tie-line power exchanges among regional power systems facilitate renewable accommodations. Power exchanges can be calculated based on a tie-line security region that provides the feasible region of coupling parameters. However, a tie-line security region is a high-dimension polytope due to multiple time periods and border buses in power system operations, generally leading to a heavy computational burden. A fast calculation for high-dimension tie-line security regions is studied in this paper. The high-dimension polytope across all the time periods is decomposed as a Cartesian production of lower-dimension polytopes at each time period by leveraging dispatch levels of generations. For each lower-dimension polytope, the computational burden brought by multiple border buses is alleviated by aggregating tie-line power. Minimum renewable curtailments are preserved in the tie-line security region by adding an additional dimension, providing information for renewable accommodations based on the tie-line security region. For coupling parameters within our tie-line security region, a feasible decision of the regional power system always exists. Finally, a decentralized and non-iterative framework is demonstrated to utilize our tie-line security region for renewable accommodations in an interconnected power system. The effectiveness of our methods is corroborated in the IEEE 9-bus system, a 661-bus utility system, and a five-region system.

Enhancing resilience and sustainability of distribution networks by emergency operation of a truck-mounted mobile battery energy storage fleet

Distribution networks have always been exposed to outages due to various internal and external causes. During emergencies, the damaged areas are disconnected and as a result, a portion of the connected loads remained unmet until ending required repairs. Accordingly, utilizing the total renewable potential in smaller islands may be unmanageable and result in curtailment. In this paper, a method is proposed to overcome these challenges by utilizing a fleet of mobile battery storage (MBS) systems. The MBSs will overcome renewable curtailment and unmet load simultaneously during emergencies via a shift in the produced energy. The excess energy produced in the islands with extra generation will be stored and then used at another location and time in the islands without production adequacy. To do this, a multi-stage and spatio-temporal operation model for a fleet of truck-mounted MBS systems based on road transport is proposed. Both time and cost of transportation are considered and modeled by linear formula. The battery lifetime and full four-quadrant power factor of the integrated inverter are also considered. The proposed model aids to decrease computational burden by decomposing the transportation model from the distribution network. Besides, it ensures the minimum cost operation while maximizing renewable resources utilization trapped on small islands. The model is linear and capable of handling real-life and large-scale systems when integrated into commercial distribution software. The model is validated by implementation on the 33-bus distribution grid coupled with a 15-node transportation network and results demonstrate increased resilience besides enhanced renewable resources utilization.