Intermittent Renewable Energy Sources Research Articles

Economic viability of Li-ion batteries based on the price arbitrage in the European day-ahead markets

The accelerating increase in the power capacity of intermittent renewable energy sources has a significant impact on the operation of power systems. First, it causes a growth in electricity price volatility in energy markets. Second, it requires balancing the system to meet the demand also in windless hours at night. Li-ion batteries, as a promising energy storage technology, are considered a response to the abovementioned challenges. However, their use must generate profits to encourage potential investors. With this in mind, the objective of this paper is to examine the economic profitability of Li-ion batteries based on price arbitrage in the European day-ahead market. For this purpose, 7 years of data from 22 European markets are analysed. These data are multiplied to maintain the volatility of electricity prices within the entire lifetime of the energy storage system. The results provide for each country (i) sets of hours of electricity purchase and sale that corresponds to hours of storage charging and discharging, (ii) a number of charging/discharging cycles, (iii) potential profits of transactions in day-ahead markets, and (iv) net present values of investments for current and projected costs. The study contributes to the existing literature by pointing out the most competitive markets for Li-ion batteries, depending on economic results, market size and renewable generation in power systems. The results of NPV are below zero in each case analysed when the current capital cost is considered. However, a reduction of capital costs increases the profitability of the system, indicating Finnish and Romanian markets as the most competitive for Li-ion batteries.

Stochastic energy management of a multi-microgrid system with battery/ supercapacitor energy storages considering demand response and transactive energy

This paper proposes stochastic energy management for an electrical system consisting of a multi-microgrid and a distribution company (DISCO). The objective function aims at finding an optimal day-ahead energy schedule of dispatchable resources, energy storages, and demand response in the presence of intermittent renewable energy sources. Two different energy storage devices, i.e., battery and supercapacitor (SC), are modeled in the system to provide both high power and energy density. Wind speed, solar irradiation, and electrical demand uncertainties have been modeled using probability density functions of uncertain parameters, and the number of scenarios has been decreased using mixed-integer linear programming (MILP) based scenario reduction with a novel characteristic. In the proposed model, the DISCO, as a leader, attempts to maximize its profit while the microgrids (MGs), as followers, tend to minimize their operational costs. Karush-Kuhn-Tucker, strong duality, and Fortuny-Amat transformation are used to convert the non-linear bi-level problem into a linear single-level problem. The proposed model was tested on a hypothetical distribution system and the results showed the efficiency of the model in reducing operational costs of MGs by 7.5%, increasing the DISCO profit by 6.9%, and improving the reliability of the system by reducing the energy not supplied.

Improving flexibility of thermal power plant through control strategy optimization based on orderly utilization of energy storage

Operational flexibility in thermal power plants has assumed a growing significance in maintaining power grid stability primarily driven by the increased penetration of intermittent renewable energy sources. Substantial energy resides within the deaerator and boiler subsystems of thermal power plants, and optimizing the utilization of the stored energy is crucial for enhancing the operational flexibility of these plants. A novel coordinated control strategy, informed by the characteristics of distributed energy storage and power ramping stages of thermal power plants, is proposed. This control strategy systematically activates energy reserves within the deaerator, regenerative heaters, and boiler subsystems through load decomposition, valve regulation, and revised coal feeding rate, respectively. Control performance is subsequently assessed within a reference scenario. The results demonstrate a notable improvement in the control performance. The variations in the reheat steam temperature, main steam pressure, and output power are reduced by 2.0 °C, 0.47 MPa, and 2.4 MW, respectively. Moreover, the maximum power ramp rate increases from 1.5 % to 5.5 % Pe0 min−1. Furthermore, a substantial reduction in coal consumption of up to 7.09 % is achieved through the orderly utilization of energy storage. This study provides a comprehensive reference for enhancing the operational flexibility of power plants.

On the Vaneless Space Vortex Structures in a Kaplan Turbine Model Operating at Speed No Load

The growing installation of intermittent renewable energy sources is forcing hydraulic turbines to work more frequently at speed no load when dangerous vaneless space vortex structures and stochastic flow phenomena can occur. An experimental campaign has been performed in a reduced-scale Kaplan turbine model at speed no load for different combinations of guide vane and runner blade angles under non-cavitation and cavitation conditions. Several simultaneous vaneless space vortex structures, all of them inducing torsional rotor vibrations, have been observed. Nonetheless, only one of them has been found to dominate over the rest depending on the blade and guide vane angles. Off-board pressures, torques and vibrations as well as on-board strains have been measured to characterize their nature, intensity, dynamic behavior and induced structural response. Their precession frequencies have been found to depend on the discharge factor, the number of vortices and their location inside the vaneless space. Under cavitation conditions, their dynamic behavior has not been significantly altered but the induced structural response has increased at the low-pressure side of the turbine.

Improved Vanadium Flow Battery Performance through a Pulsating Electrolyte Flow Regime

AbstractThe interest in flow batteries as energy storage devices is growing due to the rising share of intermittent renewable energy sources. In this work, the performance of a vanadium flow battery is improved, without altering the electrochemical cell, by applying a pulsating flow. This novel flow battery flow regime aims to enhance performance by improving its mass transfer properties. Both the pulse volume and frequency have an influence on the battery performance, and lead to a 38.7 % increase in accessible discharge capacity compared to the conventional steady flow regime at values of 0.40 cm3 and 2.4 Hz in this cell, respectively. Furthermore, at these parameter settings a reduction of the mass transfer resistance by 71.4 % is achieved at 0.2 cm3/min ⋅ cm2. These results show that a pulsating flow can be beneficial in certain conditions, opening new possibilities for boosting performance in flow batteries.

Investigation of power quality issues in 14-bus electrical network with high penetration of renewable generation

Power quality issues arise in electrical networks when variable renewable energy (VRE) is integrated into them due to their random and intermittent nature which depends on weather conditions and other factors. The variation of solar irradiance throughout the day affects the energy produced by solar panels and the integration of solar power into electrical networks will result in changes and fluctuations in the voltage profile of buses. Reactive power compensation is required to improve the bus voltage levels of the electrical network to be within the required limits and the optimal allocation of reactive power compensation devices in the network is a complex problem to be investigated for the optimum injection of reactive power to obtain better voltage profiles for the entire network. This research investigated the penetration of variable solar energy into an electrical network in terms of voltage and reactive power flow. A variety of literature was reviewed in the scope of reactive power management in power systems and a gap in addressing the optimal allocation of compensation devices in the IEEE-14 bus was addressed based on the proposed methods followed by discussions of the results in terms of voltage profiles and reactive power flow in the buses. The objective is to produce an output power of higher quality and reliability for the loads so that intermittent sources of renewable energy can be more competent with energy sources such as fossil fuels that do not depend on weather conditions. Integration of methods using compensation optimisation (optimal allocation of capacitors) and volt-var regulation (smart inverter) to improve the voltage profile that was dropped and the fluctuations after penetration of solar power were carried out. A solar bus with variable energy generation was connected to the IEEE-14 bus to study the voltage variations. This was executed by the power flow calculation module to determine the voltages and reactive power in the buses of the network. With the optimum allocation of the capacitors, the voltage levels in all weak buses of the IEEE-14 bus were increased to be between 0.95 p.u. and 1.05 p.u. which was the voltage specifications of the Malaysian Grid Code Requirements. The voltage for every weak bus in the IEEE-14 bus showed a rise of 5.7% from 7 a.m. to 12 p.m. With that, the volt-var function was used for reactive power regulation at the point of common coupling (PCC) and a reduction of voltage deviation of 2.828 to 1.3% in the IEEE-14 bus was observed. The average voltage profile of all buses managed to attain a value of 98.99% from 95.673% (with solar power) with the optimal allocation of capacitors and volt-var regulation. The beneficiaries of this project will be the Sustainable Energy Development Authority (SEDA) which administers the Net Energy Metering (NEM) scheme and Tenaga Nasional Berhad (TNB) which is the Malaysian multinational electrical company focused primarily on the generation, transmission, and distribution of electricity in Peninsular Malaysia. The Energy Commission and Ministry of Energy and Natural Resources are also beneficiaries as they carried out a competitive bidding programme for large-scale solar (LSS) known as the LSS@MEnTARI or LSSPV4 to attain bids for the development of around 1000 MW AC of LSS power plants to be operational in Malaysia by 2022. This work will also be beneficial in future research in planning reactive power compensation devices in networks of multiple VRE sources, communication, and coordinated control of smart inverters, and incorporation of these devices for smart grid applications.

Enhancing thermal energy storage in buildings with novel functionalised MWCNTs-enhanced phase change materials: Towards efficient and stable solutions

Phase change materials (PCMs) are a promising panacea to tackle the intermittency of renewable energy sources, but their thermal performance is limited by low thermal conductivity (TC). This pioneering work investigates the potential of organic PCM-enriched surface-modified and un-modified multi-walled carbon nanotubes (MWCNTs) for low-temperature thermal energy storage (TES) applications. The functionalised and un-functionalised MWCNTs enhanced PCM have demonstrated a TC enhancement of 158 % and 147 %, respectively, at 25 °C. However, the TC value of the unmodified MWCNTs-based PCM dropped by 52.5 % after 48 h at 25 °C, while that of the functionalised MWCNTs-based PCM remained stable. A DSC analysis of up to 200 thermal cycles confirmed that the surface-modified and un-modified MWCNTs had no major effect on the peak melting and cooling temperatures of the nano-enhanced PCMs although a minor decrease of 7.5 % and 7.7 % in the melting and crystallisation enthalpies, respectively, was noticed with the inclusion of functionalised MWCNTs. Moreover, functionalised MWCNTs incorporated PCMs have led to increases in specific heat capacity by 23 % with an optimal melting enthalpy value of 229.7 J/g. In addition, no super-cooling, no phase segregation, and a small phase change temperature were noticed with these nano-enhanced PCMs. Finally, no chemical interaction from nano-PCMs was seen in the FT-IR spectra with the incorporation of both functionalised and un-treated MWCNTs. It is evident that the functionalised MWCNT-based PCM has better thermal stability and it offers a promising alternative for improving thermal storage and management capabilities in buildings, contributing to a sustainable and energy-efficient building design.

Day-ahead optimal scheduling of micro gas turbine-based microgrid considering electricity and heating energy

Microgrids are considered as the crucial element in the integration of various distributed energy resources in buildings. They are capable of operating in both grid-connected and islanded mode and have shown immense potential in absorbing renewable energy. However, the widespread implementation of intermittent renewable energy sources, coupled with variable electricity pricing, has significantly increased the operation uncertainty of microgrids. This paper presents an analysis of the operation strategies of an integrated energy system that includes a micro gas turbine, a ground source heat pump, PV panels with the aim of meeting the heating and electricity demands of a commercial building. To facilitate this endeavor, a neural network model for micro gas turbines was developed with a focus on fast computation time and high accuracy in capturing off-design performance. Furthermore, mathematical models for ground source heat pump, PV panel were developed and validated using the Modelica language. Dymola optimization package was utilized to derive the day-ahead scheduling followed by one-hour intervals for the system, with the purpose of minimizing the electricity and heating costs associated with the system. The results demonstrate that the total costs could be reduced by approximately 51% during the analyzed period, indicating a promising avenue for cost savings in the system’s operation.

Cooperative grid frequency control under asymmetric V2G capacity via switched integral reinforcement learning

In recent years, V2G techniques have been successfully implemented to stabilize frequency deviations in the grid caused by intermittent renewable energy sources. However, the battery capacity constraints and real-time dynamic driving demands of electric vehicles (EVs) in V2G systems hinder the coordination between V2G control and power plant frequency control strategies. It leads to the dynamic asymmetry of regulation up (RU) and regulation down (RD) frequency regulation (FR) capacity of V2G system, which can affect the performance of V2G FR. To cope with this problem, this paper proposes a switched integral reinforcement learning (SIRL) scheme for cooperative grid frequency control. The proposed scheme integrates V2G control with the power plant frequency control, which are cooperated with each other to complete FR tasks. A novel switched neural network (NN) structure is constructed for the training process of the SIRL algorithm to solve the problem of dynamic asymmetric FR capacity. A switched V2G utility function and a global cost function are constructed for RU and RD. Two independent subnetworks with the same structure are adopted for RU and RD learning to optimized V2G control parameters respectively under dynamic asymmetric output constraints. Two case studies of the IEEE 14-bus test system demonstrate the effectiveness and advantages of the proposed scheme.

Modeling and Simulation of Energy Storage Performance of Renewable Energy Storage System

In recent times, there has been a notable increase in attention towards the reduction of greenhouse gas emissions and the enhancement of energy security. Over the past decade, there has been a significant increase in the incorporation of intermittent renewable energy sources (RESs), such as photovoltaic (PV) and wind energy, into the existing power system. However, the integration of this system hinders the reliable and steady running of the grid due to many operational and control challenges. Several challenges exist, including generation uncertainty, voltage and angular stability, power quality issues, reactive power support, and fault ride-through capabilities. The electricity produced by renewable energy sources (RESs) exhibits fluctuations due to meteorological phenomena beyond human control, such as wind speed and sunlight intensity. Energy storage systems (ESSs) play a crucial role in mitigating volatility by effectively storing excess electricity generated and facilitating its availability when needed. This study utilises the MATLAB/Simulink programme to develop an optimised configuration model for the wind hybrid power storage system.

The effect of time resolution on energy system simulation in case of intermittent energies

The management and integration of intermittent renewable energy sources, such as wind and solar power, require precise capacity planning due to their variable nature. This study investigated the efficacy of using hourly time resolution in energy system models, a common practice in capacity planning. Concerns have been raised about the ability of hourly data to accurately represent rapid fluctuations in energy production and demand since it inherently constantly under- or overestimates actual real-time conditions. This research compared the outputs of energy models using 60-min resolution data with those utilizing a 1-min resolution benchmark across various dimensions: stability of outputs, temporal performance, geographical performance, impact of starting time shifts in data sampling, and trend effects. Results indicate that models using 60-min resolution data maintain a high level of accuracy, with output deviations of less than 2 % from the benchmark. This finding provides strong support that the current significant number of research studies, based on 60-min resolution data, do not carry potentially biased results due to their time resolution and are suitable for capacity planning decisions, thereby aiding in policy formulation.

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.

Improved Control Strategy for Water Pumping System Fed by Intermittent Renewable Source

This paper focuses on a water pumping system fed by a hybrid (PV–Wind) generator. The water pumping system uses centrifugal pumps driven by variable speed Induction Motors (IM) controlled by a Field Oriented Control (FOC). The absence of battery storage to decouple sources and power demand is the main originality of the contribution, together with the typical adaptation of the FOC strategy. Furthermore, the absence of battery storage will consequently lead to fixing the system operating point at a steady state which is imposed both by the intermittent renewable energy sources and by the hydraulic load characteristics. The basic idea is then to adapt the system impedance by using the two degrees of freedom offered by the power source inverter in order to control, firstly, the DC bus voltage and, secondly, the rotor flux of the induction machine; the adaptation of the FOC strategy is based on this idea. Simulation results clearly confirmed by experimental investigations show the satisfying performance of the system even with variable powers of the intermittent renewable source.

Multi-criteria site selection workflow for geological storage of hydrogen in depleted gas fields: A case for the UK

Underground hydrogen storage (UHS) plays a critical role in ensuring the stability and security of the future clean energy supply. However, the efficiency and reliability of UHS technology depend heavily on the careful and criteria-driven selection of suitable storage sites. This study presents a hybrid multi-criteria decision-making framework integrating the Analytical Hierarchy Process (AHP) and Preference Ranking Organisation Method for Enrichment of Evaluations (PROMETHEE) to identify and select the best hydrogen storage sites among depleted gas reservoirs in the UK. To achieve this, a new set of site selection criteria is proposed in light of the technical and economic aspects of UHS, including location, reservoir rock quality and tectonic characteristics, maximum achievable hydrogen well deliverability rate, working gas capacity, cushion gas volume requirement, distance to future potential hydrogen clusters, and access to intermittent renewable energy sources (RESs). The framework is implemented to rank 71 reservoirs based on their potential and suitability for UHS. Firstly, the reservoirs are thoroughly evaluated for each proposed criterion and then the AHP-PROMETHEE technique is employed to prioritise the criteria and rank the storage sites. The study reveals that the total calculated working gas capacity based on single-well plateau withdrawal rates is around 881 TWh across all evaluated reservoirs. The maximum well deliverability rates for hydrogen withdrawal are found to vary considerably among the sites; however, 22 % are estimated to have deliverability rates exceeding 100 sm3/d, and 63 % are located within a distance of 100 km from a major hydrogen cluster. Moreover, 70 % have access to nearby RESs developments, with an estimated cumulative RESs capacity of approximately 181 GW. The results highlight the efficacy of the proposed multi-criteria site selection framework. The top five highest-ranked sites for UHS based on the evaluated criteria are the Cygnus, Hamilton, Saltfleetby, Corvette, and Hatfield Moors gas fields. The insights provided by this study can contribute to informed decision-making, sustainable development, and the overall progress of future UHS projects within the UK and globally.

CoLinFlow: An Iterative Solution Approach for the Scenario-Based AC OPF in Active Meshed Distribution Grids With Batteries

Distribution grids are characterized by an increased installation of renewable energy sources (RESs) and of batteries. Both the uncertainty of RESs and the controllability of batteries should be considered when optimizing their operation. This leads to large-scale, non-convex Optimal Power Flow (OPF) problems. Existing solution approaches either refer to radial grids or do not work under uncertainty. However, many Distribution System Operators operate their grids in meshed topologies. In this paper, CoLinFlow, an efficient solution approach for a scenario-based AC OPF in meshed balanced three-phase distribution grids with intermittent RESs and controllable batteries is proposed. First, a particular power flow form in rectangular coordinates that is accurate for meshed grids is applied. Then, Generalized Linearized Power Flow (GLPF), a novel linearization of the power flow equations based on replacing non-linear terms with constants is developed. Based on GLPF, we design CoLinFlow, a heuristic iterative scheme that at each iteration solves a convex OPF and updates GLPF until convergence. The solution of CoLinFlow at convergence is proven to be feasible with respect to the original non-convex OPF and convergence is reached after very few iterations. Also, it is shown that CoLinFlow achieves almost the same optimal objective as Ipopt, while being faster.

Exploring the Effectiveness of Carbon Cloth Electrodes for All-Vanadium Redox Flow Batteries

Vanadium redox flow batteries (VRFBs) have shown to be a promising technology for integrating intermittent renewable energy sources into the existing electrical grid. Incorporation of carbon cloth electrodes into VRFB is an area of interest for their enhanced electrochemical performance, however, issues with performance degradation throughout the duration of the experiment persist. This study investigates the performance evolution of carbon cloth electrodes during VRFB cycling to build a hypothesis on possible reasons for the declining performance. Electrochemical impedance spectroscopy and polarization curve measurements are used in conjunction to monitor the electrode degradation and shed light on the effectiveness of carbon cloth electrodes during extended cycling experiments. A detailed investigation into the structure of the carbon cloth electrodes before and after cycling, via several material characterization tests, provides insight needed to determine an explanation for the increasing resistance. The structural integrity and surface morphology of the carbon cloth electrodes are evaluated to compare the electrode before and after cycling, displaying any changes to the electrode due to cycling. Durability of hydrophilicity during RFB cycling is found to be a key feature for future carbon cloth electrode design efforts.

How do uncertain renewable energy induced risks evolve in a two-stage deregulated wholesale power market

Integrating renewable power into power market transactions is significant in terms of achieving carbon peaking and carbon neutrality. However, the integration of intermittent renewable energy sources (RES) introduces instability into power generation and brings certain risks to deregulated power market transactions. This study aims to identify the risks arising from RES power integration and analyze how these risks transmit and evolve in deregulated power markets. A Cournot game model is constructed to analyze the generation decisions of a thermal power generation company (GENCO) and a wind power GENCO in a two-stage power market. According to the results, in the mid-to-long-term power market, an increase in the uncertainty of wind power generation (WPG) could reduce wind power supply, increase the clearing price and decrease the power demand. Then, in the spot power market, the increased uncertainty related to WPG might decrease the amount of wind power traded, increase the marginal generation cost of the thermal power GENCO, raise the clearing price, and reduce the market demand for power. Finally, the uncertainty related to wind power generation could result in diminished revenue for the wind power GENCO and a loss in overall social welfare in the two-stage power market transaction.

State of the art approach for comprehensive power system security assessment—Real case study

Power system security assessment plays a critical role in ensuring the safety and stability of the electric grid, evaluated by the operating state’s proximity to the loadability limits. However, with the increasing integration of intermittent renewable energy sources and rising electricity demands, there is a growing need for fast and reliable algorithms to perform power system security assessments effectively. This work reviews state-of-the-art approaches for steady-state security assessment and demonstrates the advantages of the recently proposed Transversality Enforced Newton Raphson (TENR) algorithm. The algorithm provides better computational tractability, scalability, and the capability to incorporate various technological constraints like limits on voltage setpoints, transmission line thermal limits, generator power outputs, etc. This work presents a generalization of the TENR algorithm, proof of convergence, and an adaptive step-size strategy with improved computational performance. The proposed algorithm was used to study maximum loadability, maximum boundness of the nodal power injections, and total transfer capability on a realistic case study of the Russian Far-East power system model, which expects substantial development in the nearest future.

Economic Viability of NaS Batteries for Optimal Microgrid Operation and Hosting Capacity Enhancement under Uncertain Conditions

Recent developments have increased the availability and prevalence of renewable energy sources (RESs) in grid-connected microgrids (MGs). As a result, the operation of an MG with numerous RESs has received considerable attention during the past few years. However, the variability and unpredictability of RESs have a substantial adverse effect on the accuracy of MG energy management. In order to obtain accurate outcomes, the analysis of the MG operation must consider the uncertainty parameters of RESs, market pricing, and electrical loads. As a result, our study has focused on load demand variations, intermittent RESs, and market price volatility. In this regard, energy storage is the most crucial facility to strengthen the MG’s reliability, especially in light of the rising generation of RESs. This work provides a two-stage optimization method for creating grid-connected MG operations. The optimal size and location of the energy storage are first provided to support the hosting capacity (HC) and the self-consumption rate (SCR) of the RESs. Second, an optimal constrained operating strategy for the grid-connected MG is proposed to minimize the MG operating cost while taking into account the optimal size and location of the energy storage that was formerly determined. The charge–discharge balance is the primary criterion in determining the most effective operating plan, which also considers the RES and MG limitations on operation. The well-known Harris hawks optimizer (HHO) is used to solve the optimization problem. The results showed that the proper positioning of the battery energy storage enhances the MG’s performance, supports the RESs’ SCR (reached 100% throughout the day), and increases the HC of RESs (rising from 8.863 MW to 10.213 MW). Additionally, when a battery energy storage system is connected to the MG, the operating costs are significantly reduced, with a savings percentage rate of 23.8%.

Effect of structural characteristics on the transport characteristics of solid particles in the thermal storage and release system of circulating fluidized bed

Coal-fired power generation stands as the most economically viable modulating power source in present-day China. It holds the potential to offer prospective solutions to the challenges posed by the rapid expansion of intermittent, unpredictable, and unstable renewable energy sources. Solid particle thermal storage technology emerges as an effective means to enhance the flexibility of coal-fired circulating fluidized bed power units. To attain an optimized structure for the solid particle thermal storage and release system in circulating fluidized bed units, experimental research was conducted on a 0.1 MWth circulating fluidized bed test platform. This study delved into the impact of ash storage bin geometries and the shapes of their feed-discharge valves on the control properties of solid particle transportation. The experimental outcomes reveal that employing inverted m-shaped valve and dual U-shaped valves for feed control, alongside U-shaped valves and N-shaped valves for discharge control, both enable efficient and rapid storage and release of solid particles within the circulating fluidized bed. Under similar air distribution conditions, the inverted m-shaped valve exhibits lower conveying energy consumption than the dual U-shaped valves, while the N-shaped valve excels in control characteristics over the U-shaped valve. Furthermore, the inverted m-shaped valve and the N-shaped valve demonstrate optimal overflow port heights, and the ash storage bin exhibits an optimum height-to-diameter ratio.