Variable Renewable Energy Penetration Research Articles

Optimal sizing and placement of battery energy storage system for maximum variable renewable energy penetration considering demand response flexibility: A case in Lombok power system, Indonesia

Indonesia is a tropical climate country with considerable renewable electrical energy source prospects, including photovoltaic (PV) and wind energies. Nevertheless, several variable renewable energy sources (VREs) have exhibited uncertain attributes and substantial reliance on natural conditions, leading to unstable load-related power supply risks. Hence, integrating battery energy storage systems (BESSs) with VRE generators is a dependable approach to bolster renewable energy generator applications on a large-scale grid while providing load demand flexibility. This study determined adequate sizing and placement of the BESS to achieve maximum VRE generator penetration while considering the demand response flexibility. Key indicators, including technical minimum load and system ramp capacity, were identified to achieve maximum penetration of thermal generators. This study also combined a unit commitment procedure with direct current optimal power flow (DC-OPF) as a novel approach to determine the maximum VRE penetration level. An optimization problem model concerning mixed integer linear programming (MILP) was subsequently employed in this study using the CPLEX solver in the general algebraic modeling system (GAMS). The study is based on the IEEE RTS-24 system modified and a real-life case study of the Lombok energy system in Indonesia. Results from the simulated Lombok power system highlighted that optimal sizing and placement of the BESS could lower system costs by 37.66%, 33.63%, and 22.26% compared to the current system conditions during the weekday, weekend, and the lowest day scenarios, respectively. The VRE penetrations of the generators were also higher than the current system conditions by 83%, 51%, and 39% during the weekday, weekend, and the lowest day scenarios, respectively.

Variable renewable energy modeling system to study challenges that impact electrical load at different penetration levels: A case study on Kuwait's load profile

The transitioning from conventional power systems to variable renewable energy (VRE) could impose significant challenges on transmission, short-term balancing requirements, and more cycling to ramp conventional plants. Kuwait's government has set a target of 15% of electricity generation from renewable resources by 2030 and more in the following years. This ambitious target requires close collaboration between researchers and decision-makers to overcome the upcoming challenges. The current study comes in the context of this objective to support decision-makers technically during planning and deploying VRE plats in various parts of the country. An in-house simulation modeling system for solar photovoltaic (PV) and wind power based on high-quality weather data has been developed. The system can model centralized or decentralized VRE scenarios. Several load characteristics have been used to examine the output of the scenario, such as the residual load, impact on the peak, and baseload due to changes in VRE penetration level. Other parameters, including capacity credit, full load hours, ramping power magnitude and rate, and overproduction of resources, are also outputs of the system. The output results of the modeling system have been validated against two years of operational solar PV and wind Shagaya power plants data. The results show combining solar PV with wind could dramatically increase the capacity credit, reduce overproduction, and reduce ramping power. The authors will continue evolve and improve this in-house modeling system to support research in this field and for the upcoming future RE projects instead of relying on commercial software.

Voltage Stability Constrained Economic Dispatch for Multi-Infeed HVDC Power Systems

Multi-infeed LCC-HVDC decreases voltage stability margins due to its current source nature. Moreover, the high penetration of variable renewable energy makes it difficult to reserve enough margins for all periods. Therefore, voltage stability constraints need to be considered in the scheduling stage. However, the challenge is that the voltage stability margin is not analytic with respect to state variables. We propose a sparse support vector machine to extract the nonlinear voltage stability rule. To embed the rule into economic dispatch (ED), we apply a convex reformulating technique to the rule and then formulate a voltage stability constrained ED (VSCED) model by semi-definite programming. The model is tested on a modified IEEE-14 system and a real-world system from Jiangsu Province, China; and it is compared with other typical data-driven-based models in the Jiangsu system. The numerical experiments suggest that the stability margins can be effectively reserved above the required threshold within an acceptable computation time by the proposed VSCED model, which outperforms the other models.

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.

The role of energy storage in Great Britain's future power system: focus on hydrogen and biomass

The increasing deployment of variable renewable energy (VRE) in the power sector, such as wind and solar photovoltaic, is expected to reduce emissions. However, VRE poses challenges due to their intermittency and variability. The Future Renewable Energy Performance into the Power System Model (FEPPS) is used to analyse VRE penetration in Great Britain's (GB) power system, resulting in VRE shares of around 65%, far from over 80% forecasted by 2030 and 2040 due to flexibility and stability constraints. The incorporation of new power generation and energy storage technologies is also analysed, including the role of biomass and hydrogen as low-carbon fuel options. Hydrogen is assumed to be produced from the curtailment of VRE and biomass. Between 6.57 and 283 Mt. of biomass would be required to balance bio‑hydrogen requirements by 2040; therefore, hydrogen production would depend on technology prioritisation. Power generation from hydrogen technologies (fuel cells and turbines) has a significant role in power system decarbonisation, with hydrogen turbines meeting up to ∼10% of annual electricity demand. In contrast, generation from batteries, adiabatic compressed air energy storage and natural gas turbines is not significant. Moreover, between 7.7 and 9.7 TWh of hydrogen storage would be needed, and there is substantial potential for salt cavern storage in GB, providing many 100s TWh. Finally, incorporating new generation and storage technologies relies on levelized cost of electricity (LCOE) reductions of 31% and 13% by 2030 and 2040, respectively, to keep the power sector on track towards decarbonisation.

Assessment of the carbon emissions reduction potential in Thailand’s power sector with high penetration of variable renewable energy sources and electric vehicles in the year 2030

Abstract The power sector has substantial carbon emissions reduction potential that could achieve the new nationally determined contribution target in 2030 by increasing low-carbon technologies, e.g. variable renewable energy sources and electric vehicles (EVs). Therefore, two approaches were suggested in this work. In the first approach, Thailand’s power sector was modelled by using PLEXOS software to find the impact of the high penetration of variable renewable energy (RE) and EV charging load for the projected year 2030. The second approach proposed a demand–response and energy storage system solution with carbon pricing in the model to assess the targets. As a result, the electricity demand from charging EVs will cause a new peak demand at night, while the high variable RE penetration will cause curtailment in the power system due to excess supply at noon. Therefore, Thailand’s power sector has the potential for carbon emissions reduction by 45% with clean energy technologies, which could increase to 68% with carbon pricing, easily achievable by the nationally determined contribution target in 2030. However, these benefits could only be derived if various entities involved in the energy regulatory, transport and power sectors coordinate to implement the required technological and financial policies.

Using neural networks to forecast marginal emissions factors: A CAISO case study

Marginal Emissions Factors (MEFs) quantify the time-dependent changes in CO2 emissions resulting from changes in electricity consumption. Accurate MEFs are critical for calculating the emissions impact of demand-side management (DSM) activities and programs, but current methods of calculating MEFs are limited by their temporal resolution, accuracy (particularly in grids with high penetrations of variable renewable energy), and ability to predict MEFs ahead of time, reducing their utility for DSM. We improve upon existing techniques by introducing a novel multi-layer perceptron to linear composite model that uses publicly available grid data to calculate historical MEFs and predict day-ahead MEFs. We test our model on publicly-available data from the California Independent System Operator over the period of 2019–2021, a grid with high daytime VRE generation. Results indicate that our model produces more accurate and more granular demand-based MEF estimations than comparable regression techniques and maintains high accuracy when use to forecast future MEFs. Our MEF framework can be applied to other regional grids to evaluate and design DSM strategies that leverage CO2 emissions-reductions as motivation for altering electricity consuming behaviors.

Variable renewable energy penetration impact on productivity: A case study of poultry farming.

Like all current industrial systems, agriculture overwhelmingly relies on energy supply from controllable sources, mainly fossil fuels and grid electricity. Power supply from these sources can be adapted to perfectly match the timing of power requirements of demand systems. The energy transition largely consists in substituting renewable power-which is intermittent by nature-to controllable sources, leading to disconnection between instantaneous power production and demand. Energy storage is a potential solution for balancing production and demand and safeguarding the operating conditions of the demand system. In this paper we quantify the effects of renewable power supply (solar and wind) on the operation of a standard poultry farm. We model the balance of power generation and demand considering the growth conditions of poultry and local weather data including temperatures, wind speed and solar radiation. We assess scenarios of renewable power supply in function of the size of the power plant, the wind-to-solar power generation mix and energy storage, and assess the impact of power supply patterns on the operating intensity (productivity) of the demand system. We show that, with a limited storage capacity, it is possible to achieve non-negligible shares of renewable power penetration without major loss in farm productivity. However, a full transition to renewable power would require the combination of i)-large energy storage compared to the annual demand, ii)- significant oversizing of the power production plant, and iii)-the exclusion of power generation combinations (wind/solar) that deviate from the timing of demand. Storage and power plant oversizing is all the more critical as production and demand are uncorrelated over the year. The ratio of useful to unused energy storage by the end of the year varies with the energy mix and operating intensity (productivity) of the farm. We discuss the implications of different energy configurations on the performance of the demand system.

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.

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.

Distributed coordinated planning for cross-border energy system: An ADMM-based decentralized approach

Cross-border interconnection and trade (CBIT) can effectively leverage the differences in resource endowments and energy demand between regions and countries, making cross-border cooperation a potential option for addressing the high penetration of variable renewable energy. This paper presents centralized and decentralized planning approaches for the cross-border energy transmission expansion planning (TEP) problem. The proposed centralized mixed-integer second-order cone programming (MISOCP) model collaboratively optimizes the expansion of national energy networks, while considering the impact of CBIT. To protect the privacy of energy data in each country, the alternating direction method of multipliers (ADMM) algorithm is extended to decompose the centralized optimization formulation into mutually independent sub-optimization issues, and adaptively adjust the penalty parameters and Lagrangian multipliers to improve convergence. This study also quantifies the effect of cross-border cooperation in such co-expansion problems as a comparative consideration. Numerical simulations on the modified cross-border integrated energy network validates the correctness and effectiveness of the proposed model and solution methodology. The results show that cross-border cooperation can reduce a country's internal energy network congestion, thus postponing the expansion investment decisions. It also shows that the distributed coordinated planning is more efficient in terms of lower cost and renewable generation curtailment that than independent optimization method. Therefore, cross-border collaboration brings economic, environmental, and renewable integration benefits to interconnected countries.

An improved decentralized scheme for incentive-based demand response from residential customers

Demand response is becoming increasingly important due to the high penetration of intermittent and variable renewable energy and electric vehicles in power systems. Real-time Incentive-Based Demand Response (IBDR) is helpful for power balancing in normal and emergency scenarios. The paper focuses on making an efficient IBDR scheme and increasing the participation of residential customers. A feature in the Home Energy Management System (HEMS) that provides the quantity of flexible load demand available with the residential customers for real-time IBDR in a decentralized scheme is explored. This paper analyzes the scheduling of flexible residential appliances in a dispersed manner over time by HEMS to increase the participation of residential customers in real-time IBDR. The error accumulation in the IBDR in a decentralized scheme due to the discrete character of residential appliances is examined and addressed. A financial ratio is proposed to give a fair opportunity to all the participants in IBDR when the cumulative flexible load demand available with the participants is greater than the required quantity of demand response. This paper provides algorithms that improve demand response systems by increasing the flexibility available to participants, reducing the error accumulation in IBDR, and ensuring the fairness of the IBDR opportunity to participants. The simulation analysis is done with 400 residential customers with a different number of flexible appliances and different energy requirements. The paper highlights the potential benefits of using a decentralized scheme to enable real-time IBDR in power systems.

Modelling the impacts of carbon pricing in India’s power system using a dynamic optimization approach

India has a significant importance in achieving the global Paris agreement’s long-term goal as it is the world's third-largest consumer of energy. This paper aims to improve the understanding of the opportunities and constraints of decarbonizing India’s electricity sector and adds to the growing body of literature by modelling the electricity sector in India with a dynamic optimization approach that assesses options for effective greenhouse reductions through carbon pricing. Attaining significant variable renewable energy penetration in India by 2050 is consistent with the lowest cost power generation options identified through our simulations, where solar and wind can provide 66 % of the electricity needs by 2050, even without a carbon price. With a carbon price of US$50/tCO2e, the simulations project that wind and power generation share in the electricity mix will rise to 81 %, leading to significant emission reductions. In this scenario, power sector emissions will be 164 million tCO2e by 2050, which is only about 14 % of the emissions levels in 2019. The analysis also indicates that fossil fuels remain part of India’s electricity mix in 2050, but their role and operation would dramatically change. When a carbon price of US$50/tCO2e is introduced, coal capacity remains valuable to fill demand when solar and wind are not available. This would require modifications in operation schedules and repurposing coal power plants for frequent ramping up and down.

Assessing electric mobility and renewable energy synergy in a small New Caledonia Island community

ABSTRACT In this paper, we evaluate the synergy between variable renewable energy (VRE), electric mobility, and Vehicle to Grid (V2G) deployment for a small community transitioning to a low-carbon economy. We propose an integrated deterministic modeling approach that accurately describes electric mobility activity within the electric grid in the ETEM-SG long-term capacity expansion model. This approach allowed us to keep the entire approach in the linear programming domain. We then perform a scenario analysis on the Isle of Pines case. The results show that V2G is essential for electric vehicles to make a positive contribution to the electric system by providing a supply–demand balance service. The deployment of electric vehicles allows reaching a VRE penetration rate of up to 94%, at no additional cost compared to a solution without electric vehicles, and even with a global-cost reduction of up to 5.3% thanks to a decrease of the capacity of stationary battery packs needed for storage.

Assessing the potential of demand-side flexibility to improve the performance of electricity systems under high variable renewable energy penetration

Assessing the potential of demand-side flexibility to improve the performance of electricity systems under high variable renewable energy penetration

Optimal future energy mix assessment considering the risk of supply for seven European countries in 2030 and 2050

The scope of energy system modeling is to support policy-makers in the definition of an effective energy strategy to achieve key targets (emissions, energy security, affordability, etc.). The aim of this article is to study the future optimal energy mix needed to reach European energy targets by also containing the risk of supply for seven European countries in 2030 and 2050. The considered countries are the following: Spain, Italy, France, Germany, Netherlands, Poland, and Sweden. EPLANopt which couples the deterministic simulation model EnergyPLAN developed by Aalborg University with a Multi-Objective Evolutionary Algorithm built on the Python library DEAP is used for this analysis. The multi-objective approach allows for the assessment of the optimal future scenarios considering both an economic and environmental objective functions. Moreover, the security of supply is evaluated for each optimal solution. The results obtained in terms of variable renewable energy penetration, taking into account ground-mounted, rooftop photovoltaics, onshore and offshore wind power, are compared to the penetrations obtained from the scenarios of ENTSO-E. The results show that the decarbonization process represents an opportunity because it improves the security of supply while decreasing CO2 emissions.

The overarching role of electric vehicles, power‑to‑hydrogen, and pumped hydro storage technologies in maximizing renewable energy integration and power generation in Sub-Saharan Africa

Globally, efforts are underway to keep global warming well below 1.5–2 °C as outlined in the Paris Agreement. Ghana plans to achieve 10 % renewable energy (RE) participation in the national energy mix by 2030. In the Renewable Energy Masterplan 2030, the target is a total installed RE utility scale of 1094.63 MW. In the current work, we propose a better pathway to gradual decarbonization of the Ghanaian energy sector (power, transport, industry, residential, and others) at higher technical levels of variable RE (VRE) penetration, 0 critical excess electricity production (CEEP), and lower cost than the 2030 Business-as-Usual (BAU) scenario. In our proposed scenario, High Renewable Energy Penetration (HREP) 2030, we assess the overarching role of electric vehicle integration, power-to-gas (hydrogen), and pumped hydro storage technologies in maximizing VRE penetration in Ghana. The results from the current study show that it is technically feasible to include solar and wind power penetrations of 32.66 % and 38.11 % in the 2030 HREP scenario compared to the 2.64 % and 1.99 % of the 2030 BAU case, respectively. The HREP scenario will ultimately lead to 26.45, 30.86, and 23.34 % contribution of solar, wind, and thermal in the total electricity production in 2030 compared to the 2.36, 1.78, and 74 % of the BAU scenario, respectively. The CO2 emissions and its cost in the HREP case are 22.5 and 22.81 % lower than in the BAU case, and the total annual cost of the former is 12 % lower than the latter. The total electricity production from wind and solar energy alone in the 2030 HREP will create an additional 723 jobs and 11.96 Mt avoided CO2 emissions. The proposal made in the current study could usher in a long-term transition pathway that leads from the current fossil-based system to an affordable, efficient, sustainable, and secure energy future for Ghana. The findings presented in the current study should be of significance to decision-makers in formulating and adopting zero and low-carbon strategies for long-term decarbonization targets and planning in Ghana beyond 2030.

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.

Synergetic Scheduling Energy and Reserve of Wind Farms for Power Systems with High-Share Wind Power

With wind and other variable renewable energy (VRE) generation gradually becoming the main power source, it is difficult to ensure the flexible and secure operation of the system by completely relying on conventional sources to balance the uncertainty and volatility of VRE. The increase of VRE penetration leads to the shortage of operation reserves, and wind power is allowed to participate in reserve services. However, the output of wind power is uncertain, and how to ensure the reliability and sustainability of wind power reserves is still an open question. A robust energy and reserve dispatch method considering the flexibility of wind power is proposed to solve this problem. To effectively measure the output and reserve margin of wind power under uncertain scenarios, (1) the grid connection coefficient of wind turbine generators (WTGs) is defined, and the uncertainty set considering active wind power curtailment is established; and (2) based on two kinds of WTG control methods, the reserve model of wind farms is established. The model links the reserve capacity between the base scenario and uncertain scenarios through the reserve coefficient, which ensures that the wind power reserve determined in the base scenario is still deliverable in any uncertain scenario. The robust scheduling model determines the optimal dispatching and reserve plan of conventional units and wind farms by balancing the system operation economy and the schedulable reserve of wind power. The column-and-constraint generation algorithm is used to solve the model. The effectiveness of the proposed model is verified by the illustrative results of the IEEE normal system.

Off-design characteristics of energy conversion equipment in integrated energy systems

With the increasing penetration of variable renewable energy, integrated energy systems (IES) have become increasingly complex. Unfortunately, the widely used constant efficiency model is too simplified to reflect actual operating conditions. Therefore, this study investigated the effects of off-design characteristics on the operation and configuration of integrated energy systems, both singly and collectively. To this aim, a two-stage optimization framework was applied to optimize the operation and configuration of IES. The off-design characteristics include the electric-thermal correlation of gas turbines (GTs), the load rate-efficiency correlation of gas boilers (GBs) and absorption chillers (ACs), and the temperature-efficiency correlation of heat pumps (HPs) and electric chillers (ECs).When off-design characteristics are considered, the optimal capacities of the energy conversion equipment tend to increase and system costs would increase. For all system equipment, the capacity of the EC increases by 515.4% and the system cost increases by 7.3%. Regarding system operation, the effects of off-design characteristics on the operation of the GT and AC are most significant for all energy conversion equipment. The electric energy storage (EES) and the thermal energy storage (TES) help to reduce the capacity of the GT and system cost. When off-design characteristics are considered, their effects are magnified.