Добірка наукової літератури з теми "RES-based intermittent scenario"

A power system can be defined as flexible if it can within economic and technological boundaries respond quickly and adequately to variations in supply and demand. The ongoing penetration of variable and intermittent renewable energy sources (RES) like wind and solar imposes additional and more critical requirement on power system flexibility. In this paper we propose a method to quantify these requirements based on the comparison of seven demand side parameters describing the statistical properties of the net load and the residual load of the referred power system. Each one of these parameters reflects a separate requirement on the available conventional generation in hourly and daily time scales—ramp up and ramp-down capabilities, technological minimum of generation, daily variation of generation. The proposed approach can be used to predict the requirements for generation flexibility according to the expected scenario of RES penetration in the future development of energy power system. It has been applied and integrated from the Bulgarian Transmission System Operator (TSO) which name is the Bulgarian Electricity System Operator (ESO).

Electrical energy and power demand will experience exponential increase with the rise of the global population. Power demand is predictable and can be estimated based on population and available historical data. However, renewable energy sources (RES) are intermittent, unpredictable, and environment-dependent. Interestingly, microgrids are becoming smarter but require adequate and an appropriate energy storage system (ESS) to support their smooth and optimal operation. The deep discharge caused by the charging–discharging operation of the ESS affects its state of health, depth of discharge (DOD), and life cycle, and inadvertently reduces its lifetime. Additionally, these parameters of the ESS are directly affected by the varying demand and intermittency of RES. This study presents an assessment of battery energy storage in wind-penetrated microgrids considering the DOD of the ESS. The study investigates two scenarios: a standalone microgrid, and a grid-connected microgrid. The problem is formulated based on the operation cost of the microgrid considering the DOD and the lifetime of the battery. The optimization problem is solved using non-linear programming. The scheduled operation cost of the microgrid, the daily scheduling cost of ESS, the power dispatch by distributed generators, and the DOD of the battery storage at any point in time are reported. Performance analysis showed that a power loss probability of less than 10% is achievable in all scenarios, demonstrating the effectiveness of the study.

There is a surge in the total energy demand of the world due to the increase in the world’s population and the ever-increasing human dependence on technology. Conventional non-renewable energy sources still contribute a larger amount to the total energy production. Due to their greenhouse gas emissions and environmental pollution, the substitution of these sources with renewable energy sources (RES) is desired. However, RES, such as wind energy, are uncertain, intermittent, and unpredictable. Hence, there is a need to optimize their usage when they are available. This can be carried out through a flexible operation of a microgrid system with the power grid to gradually reduce the contribution of the conventional sources in the power system using energy storage systems (ESS). To integrate the RES in a cost-effective approach, the ESS must be optimally sized and operated within its safe limitations. This study, therefore, presents a flexible method for the optimal sizing and operation of battery ESS (BESS) in a wind-penetrated microgrid system using the butterfly optimization (BO) algorithm. The BO algorithm was utilized for its simple and fast implementation and for its ability to obtain global optimization parameters. In the formulation of the optimization problem, the study considers the depth of discharge and life-cycle of the BESS. Simulation results for three different scenarios were studied, analyzed, and compared. The resulting optimized BESS connected scenario yielded the most cost-effective strategy among all scenarios considered.

We report the upper and lower bounds for the levelized cost of high-temperature industrial process heat, supplied from electricity generated with solar-photovoltaic (PV) and wind turbines in combination with either thermal or electric battery storage using hourly typical meteorological year (TMY) data, in systems sized to supply between 80% and 100% of continuous thermal demand at a site in the northern part of Western Australia. The system is chosen to supply high-temperature air as the heat transfer media at temperatures of 1000 °C, which is a typical temperature for an alumina or a lime calcination plant. A simplified model of the electrical energy plant has been developed using performance characteristics of real PV and wind systems and TMY data of renewable energy resources. This was used to simulate a large sample of possible system configurations and find the optimal combination of the renewable resources and storage systems, sized to provide renewable shares (RES) of between 80% and 100% of the yearly demand. This allowed the upper and lower bounds to be determined for the cost of heat based on two scenarios in which the excess energy is either dumped (upper bound) or exported to the electricity grid (lower bound) at the average generating cost. The lower bound of the levelized cost of energy (LCOEL), which occurs for the system employing thermal storage, was estimated to range from USD 10/GJ to USD 24/GJ for RES from 80 to 100%. The corresponding upper bound (LCOEU), also estimated for the system using thermal storage, are between USD 16/GJ and USD 31/GJ, for RES between 80% and 100%. The utilization of electric battery storage instead of thermal storage was found to increase the LCOE values by a factor of two to four depending on the share of renewable energy. Compared with current Australian natural gas cost, none of the systems assessed configurations is economical without either a cost for CO2 emissions or a premium for low-carbon products. The estimated cost for CO2 emission that is needed to reach parity with current natural gas prices in Australia is also presented.

Energy systems face radical –almost revolutionary changes which, however, will be stretched over the long period. The critical factors influencing the future development of the Polish power sector are discussed in this paper. Development of intermittent energy supplies from renewable energy sources imposes a challenge on the entire power system and requires specific adaptations and responses from traditional generation units. Up to the present time they have been used to work in the stable mode while now they need more operational flexibility. The share of RES constantly increases. On one hand, this has a very positive environmental impact, but on the other it disturbs economics of classical generation units. Also liberalized electricity markets are impacted and the risks in power investments have increased. The capacity market could constitute a remedy, which will incentivise the investments necessary to fill the gap created by closing exhausted and inefficient plants. On the consumer side electromobility could change the demand, not only in quantity but also in terms of load profile. Climate policy tends to detriment coal based generation. For countries abundant in coal resources which make use of this cheap fuel, such as Poland, the question arises about its future role. Even in the most coal-supportive scenarios revised in this paper its relative share in electricity generation does not exceed 50% in 2050 while in others it rather goes much below 30%. .

The EIA projects that 60% of cumulative capacity additions in the U.S. by 2050 will be renewable electric generating technologies.1 The use of intermittent renewable energy in the U.S. electricity grid requires energy storage. NREL predicts that for a scenario in which 80% of electricity in the U.S. comes from renewable energy by 2050, 120 GW of energy storage would be needed,2 yet as of 2020, the U.S. has only 24 GW of storage capacity.3 Redox flow batteries (RFBs) are a useful technology for ensuring the smooth integration of renewable energy into the U.S. electricity grid because of their long lifecycles and discharge times. RFBs are currently too expensive for market deployment, however, with the all vanadium RFB (VRFB) costing double the DOE target.4,5 One way to improve the cost effectiveness of RFBs is to explore chemistries that increase the voltage window. The replacement of the VO2+/ VO2 + chemistry at the positive electrode of a VRFB with the Ce3+/Ce4+ chemistry would result in an increased theoretical voltage, but it is unclear how the kinetic, ohmic, and mass transport overvoltages would change. Additionally, studies of the environmental burdens of life cycle phases of Ce RFBs are limited. To advance the most cost effective and least environmentally harmful RFB, in this study, we develop a combined Technoeconomic Assessment-Life Cycle Assessment (TEA-LCA) model that is informed by our performance measurements to compare the levelized cost of electricity (LCOE) and levelized greenhouse gas (LGHG) emissions of VRFBs and Ce-V RFBs. The TEA-LCA model allows the user to select from a list of positive and negative electrode redox chemistries, solvents, electrode materials, and electricity grid generation profiles to calculate the LCOE and LGHG emissions of the battery for the delivery of 1 kWh of energy. A solver function optimizes the current density that minimizes either LCOE or LGHGs. The TEA-LCA model uses a bottom-up approach, in which energy- and power-dependent capital costs and environmental burdens are calculated by converting the amount of material to a kWh basis. Cost estimates are sourced from vendors and GHG emissions are pulled from the GREET database and literature. The amount of active species required to deliver 1 kWh of electricity at a specified discharge time is calculated using the redox couple properties, including redox potential, exchange current density, and limiting currents. These performance parameters are based on measurements collected in lab. The use phase burdens are calculated using the roundtrip efficiency of the battery and the price and GHGs associated with the electricity grid generation mix. End-of-life costs consist of the economic and environmental burdens of recycling and disposing of the battery material and are collected from vendors and GREET. The TEA-LCA model answers important questions related to the optimal operating conditions of an RFB. In addition to comparing the economic and environmental performances of the VRFB and Ce-V RFB, it demonstrates how different electricity grid mixes influence total cost and emissions and highlights the difference in optimal operating current density if cost or GHG emissions are prioritized, e.g., lower current density results in fewer emissions but higher cost in carbon-intensive electricity grid profiles. Preliminary results using literature values show that the Ce-V RFB has an LCOE that is 45% lower than the VRFB LCOE, with capital costs dominating. We will present the finalized LCOE for the VRFB and Ce-V RFB, as well as LGHGs, as a function of discharge time and electricity grid mix. Sensitivity analyses of the input parameters found that for both RFBs, the discount rate, discharge faradaic efficiency, and lifetime of battery had the most influence on LCOE, with a 20% decrease in discharge faradaic efficiency resulting in a 16% increase in LCOE for the VRFB. The results of this TEA-LCA model show that the use of cerium is a viable option for reducing the cost of RFBs to advance their use in renewable energy storage grid applications. Additionally, this model is generalizable to other batteries and electrochemical systems, such as CO2 conversion. Thus, the development of this TEA-LCA model represents not only an advancement to the field of redox flow batteries but also the wider field of electrochemistry. U.S. EIA. Annual Energy Outlook. (2021). Mai, T. et al. Renewable Electricity Futures Study. NREL. (2012). CSS University of Michigan. U. S. Grid Energy Storage Factsheet. (2021). Mongird, K. et al. 2020 Grid Energy Storage Technology Cost and Performance Assessment. (2020). Weber, A. Z. et al. J. Appl. Electrochem. 41, 1137–1164 (2011). Smith, G. F. & Getz, C. A. Ind. Eng. Chem. Res. 10, 191–195 (1938).

Among Renewable Energy Sources (RES), wind energy is emerging as one of the largest installed renewable-power-generating capacities. The technological maturity of wind turbines, together with the large marine wind resource, is currently boosting the development of offshore wind turbines, which can reduce the visual and noise impacts and produce more power due to higher wind speeds. Nevertheless, the increasing penetration of wind energy, as well as other renewable sources, is still a great concern due to their fluctuating and intermittent behavior. Therefore, in order to cover the mismatch between power generation and load demand, the stochastic nature of renewables has to be mitigated. Among proposed solutions, the integration of energy storage systems in wind power plants is one of the most effective. In this paper, a Hybrid Energy Storage System (HESS) is integrated into an offshore wind turbine generator with the aim of demonstrating the benefits in terms of fluctuation reduction of the active power and voltage waveform frequency, specifically at the Point of Common Coupling (PCC). A MATLAB®/SimPowerSystems model composed of an offshore wind turbine interfaced with the grid through a full-scale back-to-back converter and a flywheel-battery-based HESS connected to the converter DC-link has been developed and compared with the case of storage absence. Simulations were carried out in reference to the wind turbine’s stress conditions and were selected—according to our previous work—in terms of the wind power step. Specifically, the main outcomes of this paper show that HESS integration allows for a reduction in the active power variation, when the wind power step is applied, to about 3% and 4.8%, respectively, for the simulated scenarios, in relation to more than 30% and 42% obtained for the no-storage case. Furthermore, HESS is able to reduce the transient time of the frequency of the three-phase voltage waveform at the PCC by more than 89% for both the investigated cases. Hence, this research demonstrates how HESS, coupled with renewable power plants, can strongly enhance grid safety and stability issues in order to meet the stringent requirements relating to the massive RES penetration expected in the coming years.

Abstract A key approach to large renewable energy sources (RES) power management is based on implementing storage technologies, including batteries, power-to-hydrogen (P2H), pumped-hydro, and compressed air energy storage. Power-to-hydrogen presents specific advantages in terms of suitability for large-scale and long-term energy storage as well as capability to decarbonize a wide range of end-use sectors, e.g., including both power generation and mobility. This work applies a multi-nodal model for the hourly simulation of the energy system at a nation scale, integrating the power, transport, and natural gas sectors. Three main infrastructures are considered: (i) the power grid, characterized by instantaneous supply-demand balance and featuring a variety of storage options; (ii) the natural gas network, which can host a variable hydrogen content, supplying NG-H2 blends to the final consumers; (iii) the hydrogen production, storage, and re-electrification facilities. The aim of the work is to assess the role that can be played by gas turbine-based combined cycles in the future high-RES electric grid. Combined cycles (GTCCs) would exploit hydrogen generated by P2H implementation at large scale, transported through the natural gas infrastructure at increasingly admixed fractions, thus closing the power-to-power (P2P) conversion of excess renewables and becoming a strategic asset for future grid balancing applications. A long-term scenario of the Italian energy system is analyzed, involving a massive increase of intermittent RES power generation capacity and a significant introduction of low-emission vehicles based on electric drivetrains (pure-battery or fuel-cell). The analysis highlights the role of hydrogen as clean energy vector, not only for specific use in new applications like fuel cell vehicles and stationary fuel cells, but also for substitution of fossil fuels in conventional combustion devices. The study also explores the option of repowering the combined cycles at current sites and evaluates the effect of inter-zonal limits on power and hydrogen exchange. Moreover, results include the evaluation of the required hydrogen storage size, distributed at regional scale or in correspondence of the power plant sites. Results show that when extra hydrogen generated by P2H is fed to GTCCs, up to 17–24% H2 use is achieved, reaching up to 70–100% in southern regions, with a parallel reduction in fossil NG input and CO2 emissions of the GTCC plants.

As the share of renewable energy sources (RES) in distribution grids increases, several power quality challenges arise. Due to its intermittent nature, RES lead to voltage and frequency fluctuations in the grid that affect power quality. Moreover, as RES are connected via power converters, there is also a higher harmonic distortion pollution introduced by the switching power electronics involved, (Liang, 2017). A proven solution is the implementation of Active Power Filters (APF), which are able to compensate the unbalanced, harmonic, and reactive components of a load under different supply conditions. In order to achieve the desired compensation characteristics, the selection of an appropriate control strategy is critical, (Kumar & Mishra, 2016). Classic APF control strategies achieve said goals, although with struggles under changing load scenarios with limitations on their operational modes, (Weihe, Cateriano Yáñez, Pangalos, & Lichtenberg, 2018).This paper proposes the use of an advanced model-based control method, i.e. Model Predictive Control (MPC), to improve the performance of APF devices. Model-based control methods allow for better performance when the model of the plant is known before hand or through measurements, the MPC extends this further by introducing a cost function that ensures optimal operation even under constraints, (Maciejowski, 2002). References Kumar, P., & Mishra, M. K. (2016). A comparative study of control theories for realizing APFs in distribution power systems. 2016 National Power Systems Conference (NPSC), 1–6. https://doi.org/10.1109/NPSC.2016.7858905 Liang, X. (2017). Emerging Power Quality Challenges Due to Integration of Renewable Energy Sources. IEEE Transactions on Industry Applications, 53(2), 855–866. https://doi.org/10.1109/TIA.2016.2626253 Maciejowski, J. M. (2002). Predictive Control with Constraints. Pearson education. Weihe, K., Cateriano Yáñez, C., Pangalos, G., & Lichtenberg, G. (2018, July). Comparison of Linear State Signal Shaping Model Predictive Control with Classical Concepts for Active Power Filter Design. 167–174. Retrieved from http://www.scitepress.org/PublicationsDetail.aspx?ID=QatbWGUbqSE=&t=1