Energy Accommodation Research Articles

Two-stage robust optimization for optimal operation of hybrid hydrogen–electricity storage system considering ladder-type carbon trading

The prominent problems of renewable energy curtailment and its uncertainty have become a hot topic. To the end, with consideration of environmental friendliness, energy utilization efficiency and operation cost, this paper proposes a hybrid hydrogen–electricity storage system (HHES) operation framework comprising assorted types of coupling devices and carbon capture system (CCS) under ladder-type carbon trading (LCT) mechanism. By considering energy balance constraints, equipments’ operation constraints and erratic rates of RESs and multiple loads, a scheduling model with source-load uncertainties is developed with the goal of minimizing the system’s operation cost and carbon emission. Then, a two-stage tri-level robust model is built to find the optimal scheduling plan under multiple uncertainties given the various sources and loads. The first level is to make an optimal dispatch plan and the second level is to find the worst scenario under the given uncertainty set. The third level aims at enhancing renewable energy accommodation rate and reducing load shedding rate in the worst case. Since the model is formed as a tri-level mixed integer optimization problem, the Column and Constraint Generation (CCG) method is adopted to achieve the optimal result. Finally, numerical analyses are performed. The results show that the proposed approach realizes a flexible dispatch of multiple energy and a high utilization level of multiple storages. Furthermore, this paper studies the influence of uncertainty and uncertainty budget parameters with the comparison of the deterministic model and robust models with different uncertainties. The results show that the proposed HHES has strong robustness and can provide a good reference for energy dispatch.

Aggregate power flexibility of multi-energy systems supported by dynamic networks

The multi-energy system, encompassing electricity networks, district heating networks (DHNs), and hydrogen-enriched compressed natural gas (HCNG) networks, provides an alternative for promoting intermittent renewable energy accommodation and enhancing operational flexibility. This paper investigates the aggregate flexibility of the multi-energy system based on dynamic network models and admissible power fluctuation regions of decomposed subsystems. The dynamic processes within HCNG networks/DHNs are analyzed, and the inner-box method is employed to approximately quantify the individual flexibility of the dynamic networks. Furthermore, the optimal dispatchable regions of decomposed subsystems, accounting for internal gas/heating load uncertainties, are evaluated based on distributionally robust optimization. Through distribution-level power aggregation, the flexibility of the multi-energy system is quantified utilizing geometric methods. Numerical results on two test systems verify the effectiveness of the proposed methodology.

Flexible energy utilization potential of demand response oriented photovoltaic direct-driven air-conditioning system with energy storage

The surge in air conditioning electricity consumption exacerbates grid peak load. To counteract grid peaking pressures and accommodate a high penetration rate of renewable energy, a photovoltaic direct-driven air-conditioning system (PVACS) integrated with energy storage was suggested. The power response characteristics of the air conditioner based on indoor temperature set-point regulation were clarified with an on-site test. The test results indicated a significant flexible energy utilization potential through intelligent temperature management. Whereas, its flexibility is limited by high ambient temperature or inadequate air conditioner capacity. Then, the effects of demand response were simulated, aiming to achieve the synchronization between air conditioner power and photovoltaic (PV) power. Simulation results showed that the demand response strategies effectively reduced peak power by 45.2% and increased self sufficiency ratio and self consumption ratio to 0.83 and 0.91, respectively. Moreover, the role of short-term electricity energy storage was considered for further promoting solar energy accommodation and grid peak shaving. Optimized energy storage further reduced peak power by more than 23.4%, while mitigating the temporal supple-demand mismatch.

Low carbon collaborative planning of integrated hydrogen-ammonia system and power distribution network

The conversion of renewable energy into chemical energy carriers, such as ammonia, enhances the accommodation of renewable energy for power distribution networks (PDN) and supports the decarbonization for ammonia production systems (APS). This paper addresses the integration of PDN with APS through a collaborative planning considering a carbon emission flow (CEF) model. A collaborative planning model with carbon emissions constraints is designed, and a sensitivity analysis is performed to evaluate the impact of varying renewable energy costs on the system. To further reduce carbon emissions from green ammonia production and stabilize renewable energy volatility, a nodal CEF model that incorporates energy storage systems (ESS), wind turbines (WT), and photovoltaics (PV) is proposed. The economic feasibility of the proposed model is verified via comprehensive experiments. Numerical results show that collaborative scheduling reduces both costs and carbon emissions in PDN and APS. Implementing a carbon tax encourages the transition from grey to blue ammonia production, while a decrease in renewable energy costs further promotes the shift from blue to green ammonia. Besides this, the analysis indicates that integrating long-term operation of WT and PV, together with low-cost renewable electricity and ESS, boosts the economic efficiency of the green ammonia production system.

Mechanism-specific chemical energy accommodation with finite-rate surface chemistry in non-equilibrium flow

During atmospheric reentry, the vehicle surface is exposed to highly non-equilibrium flow. The vehicle surface can experience heterogeneous recombination of reactive atoms, which contributes to its aerothermodynamic heating. This process is followed by chemical energy accommodation (CEA), where the released energy is either transferred to the surface or the internal energy modes of the recombined molecule. Heterogeneous recombination can be categorized into Eley–Rideal (ER) and Langmuir–Hinshelwood mechanisms, which differ in their methods of molecule formation and degrees of CEA. The complete CEA assumption may not consider the dependency of CEA on the mechanisms of heterogeneous recombination. This study aims to consider the mechanism-specific CEA for a more accurate prediction of surface heat flux. The authors implement mechanism-specific CEA within the direct simulation Monte Carlo framework using the finite-rate surface chemistry model, resolving elementary surface reactions and assigning a CEA coefficient, β, to each mechanism. The model is verified through comparisons with analytical solutions of surface coverage and validated against benchmark references. A parametric investigation of rarefied hypersonic flow over a two-dimensional cylinder is conducted under different freestream Mach and Knudsen numbers. Results show a reduction in total heat flux of up to 14.44% using mechanism-specific CEA compared to the complete CEA assumption. The reduction is attributed to the relative contribution of the ER mechanism, which can be a function of atomic partial pressure at the boundary layer.

Optimal operation of energy-intensive load considering electricity carbon market

Energy-intensive load benefits from low electricity tariff and carbon emission, since they occupy certain amounts in the total cost of the product. This paper considers energy-intensive load participation in the electricity as well as carbon trading to reduce the cost. Firstly, an electricity-carbon model is established based on the correlation value method to calculate the carbon emissions of energy-intensive load based on their electricity consumption to realize the carbon amount. Afterwards, the baseline method is used to allocate free carbon emission quotas to energy-intensive load and a reward-penalty carbon trading price mechanism considering offset is proposed. Next, the objective function to achieve maximum benefits, and to reduce output fluctuation, and to improve new energy accommodation is proposed. The case studies show that, by comparing multi-objective function optimization, the optimization target proposed in this paper can effectively reduce wind power output fluctuations and improve wind power accommodation. Through the total participation in carbon trading and electricity market income, multi-objective optimization can increase the system income while ensuring that energy-intensive load meets production requirements under the premise of reducing carbon emissions, verifying the effectiveness of the low-carbon optimal operation model proposed in this paper.

The effects of energy accommodation of reflected gas molecules on flow structures during expired spacecraft reentry

To study the influence of energy accommodation of scattering gas molecules on flow fields during large expired spacecraft reentry, a more elaborated gas-surface interaction model, compared with full Maxwellian diffuse model, is employed in implicit algorithms based on Boltzmann model equation. The characteristic distributions around cylinder at different fluid regimes are accordingly obtained by implicit algorithms, Navier-Stokes solver and DSMC ((Direct Simulation Monte Carlo) method. And the consistency of these results is verified. It is confirmed that present algorithms are capable of solving external flow problems covering various fluid regimes. Then the simulation results see that under current conditions set in the paper, pressure and temperature are proportional to wall activation (ω=Tw/T∞, Tw is surface temperature, T∞ denotes as free stream temperature), but their amplitudes alter with ω at different fluid regimes. As for the effects of energy accommodation coefficients (αe), both pressure and temperature profiles vary in a linear way with αe. However, the variation ranges of these parameters are diverse with regard to different fluid regimes. These observations are favor to the construction of efficient forecasting software, which could predict the flight path of large defunct spacecraft. In this forecasting software, the external ballistics computations and aerothermodynamic simulations are synchronously carried out.

Distributed optimal scheduling for virtual power plant with high penetration of renewable energy

The virtual power plants are aggregations of distributed generators, grid-connected devices in user side. The operation of virtual power plants affects the economic benefits and environmental benefits. However, due to the stochastic and fluctuating nature of power generation from renewable energy sources, the optimal scheduling problem for the virtual power plant containing high-dimensional random variables is difficult to solve. The conic power flow constraints are considered in the virtual power plant day-ahead optimal scheduling models to maximize the revenue by virtue of optimizing the flexible resources such as energy storage system and interruptible load. To quantify the uncertainties in the optimization problem, this paper proposes a network state-based power scenario reduction strategy for renewable energy generation, where typical scenarios are selected by the state of the grid voltage. The proposed day-ahead scheduling model is a mixed-integer, nonlinear, large-scale, stochastic optimization problem with high dimensional random variables, which is difficult to be solved directly by traditional centralized method. By temporally decoupling the charging and discharging model of energy storage systems, a distributed optimization algorithm is proposed based on multi-temporal power flow decoupling optimization model. The simulation results show that the proposed distributed optimization algorithm has high accuracy and good convergence, the virtual power plant can achieve day-ahead optimal scheduling and effectively promote renewable energy accommodation under the security and reliability of the grid.

Efficiency improvement and flexibility enhancement by molten salt heat storage for integrated gasification chemical-looping combustion combined cycle under partial loads

Chemical-looping combustion offers a promising carbon capture technology for coal-fired power generation. Enhancing the operational flexibility and energy efficiency of such plants is crucial for achieving primary energy savings and renewable energy accommodation. In this study, the operating characteristics of an integrated gasification chemical-looping combustion combined cycle (IGCLCCC) under various loads are studied, and the deterioration mechanism of its thermodynamic performance is revealed. Further, an IGCLCCC scheme coupled with molten salt heat storage is proposed and evaluated from thermodynamic performance and operational flexibility. Study results indicate that the net efficiency of the IGCLCCC reaches 37.7% under 30% load, which is superior to those of conventional CO2 capture power plants under full load. Adopting the heat storage system significantly improves the operational flexibility and energy efficiency of the IGCLCCC by expanding its operating range from 30.0∼100.0% to 25.7∼105.3%. The equivalent round-trip efficiency of the heat storage system reaches 134.6% due to the upgrading of the thermal energy from the exhaust gas of the air turbine from original low levels to high levels driven by the exergy saving during the oxygen carrier-air reaction because of the air preheating to a high temperature.

Optimal Scheduling of a Cascade Hydropower Energy Storage System for Solar and Wind Energy Accommodation

The massive grid integration of renewable energy necessitates frequent and rapid response of hydropower output, which has brought enormous challenges to the hydropower operation and new opportunities for hydropower development. To investigate feasible solutions for complementary systems to cope with the energy transition in the context of the constantly changing role of the hydropower plant and the rapid evolution of wind and solar power, the short-term coordinated scheduling model is developed for the wind–solar–hydro hybrid pumped storage (WSHPS) system with peak shaving operation. The effects of different reservoir inflow conditions, different wind and solar power forecast output, and installed capacity of pumping station on the performance of WSHPS system are analyzed. The results show that compared with the wind–solar–hydro hybrid (WSH) system, the total power generation of the WSHPS system in the dry, normal, and wet year increased by 10.69%, 11.40%, and 11.27% respectively. The solar curtailment decreased by 68.97%, 61.61%, and 48.43%, respectively, and the wind curtailment decreased by 76.14%, 58.48%, and 50.91%, respectively. The high proportion of wind and solar energy connected to the grid in summer leads to large net load fluctuations and serious energy curtailment. The increase in the installed capacity of the pumping station will promote the consumption of wind and solar energy in the WSHPS system. The model proposed in this paper can improve the operational flexibility of hydropower station and promote the consumption of wind and solar energy, which provides a reference for the research of cascade hydropower energy storage system.

Low-carbon scheduling research of integrated energy system based on Stackelberg game under sharing mode

To achieve a win-win situation among multiple stakeholders within the integrated energy system, this paper proposes a low-carbon scheduling research of integrated energy system based on Stackelberg game under sharing mode. Firstly, an operation framework of integrated energy system based on leader-follower game was established, and a model of integrated energy system operator and user coalition was established considering carbon trading mechanism. Secondly, bi-directional long short-term memory is used to predict the travel data of electric vehicles, and a schedulable capacity model for electric vehicle cluster as shared energy storage was established. Then, an energy trading optimization model based on leader-follower game was constructed for integrated energy system operator and user coalition, and an improved Shapley value is adopted to realize cost allocation within user coalition. Finally, based on the demonstration project of Sino-Singapore Tianjin Eco-City is selected as the research object to make example analysis. The calculation results show this paper can achieve a reasonable benefit allocation among multiple participants, reduce carbon emissions of integrated energy system, and increase renewable energy accommodation capacity. The relevant achievements are a preliminary exploration for an effective mode of sharing economy in integrated energy system.

Energy saving and flexibility analysis of combined heat and power systems integrating heat-power decoupling technologies in renewable energy accommodation

World energy is undergoing a decarbonization transformation with the rapid growth of renewable energy. Combined heat and power, with its abundant stock and efficient characteristics, can support decarbonization. This study focuses on enhancing the energy saving and flexibility of combined heat and power systems decoupled by the vapor compression heat pump and electric boiler. The characteristics of the governing valves and the governing stage are confirmed as key factors influencing energy saving. A general modeling method is proposed to accurately determine the characteristics of the governing valves and the governing stage. The valve-point effect is obtained from the formation mechanism. With a reference case, applying the heat-power decoupling technologies results in a maximum reduction of power load of up to 70 MW, greatly enhancing the operation flexibility. The fuel saving per unit peak shaving ranges from 0.1355 kg·kWh−1 to 0.1382 kg·kWh−1 in the system decoupled by the electric boiler and from 0.2284 kg·kWh−1 to 0.2481 kg·kWh−1 in the system decoupled by the vapor compression heat pump. The maximal variation ranges of fuel saving per unit peak shaving, with and without the valve-point effect, are 0.0197 kg·kWh−1 and 0.0055 kg·kWh−1, respectively. After considering the valve-point effect, the range of fuel saving per unit peak shaving is tripled. Additionally, there are higher energy-saving regions near valve points. It is recommended to operate the decoupling systems under these working conditions, with governing valves opened at an appropriate opening degree. The energy-saving potential of these systems can be further exploited by accommodating the valve-point effect in the integration of renewable energy.

The planning method of new energy distribution network in plateau area based on local accommodation

Abstract The planning method of new energy distribution network in plateau area based on local accommodation is studied to improve the local accommodation capacity of new energy distribution network in plateau area. The framework of new energy distribution network planning in the plateau area is constructed, and the distribution network equipment suitable for the plateau environment is selected based on the harsh environment in the plateau area; in the framework of new energy distribution network planning in plateau area, a bi-level planning model considering multi-flexible resource coordinated scheduling and energy storage is established. The upper level planning model takes the maximum accommodation of new energy as the objective, and the lower level planning model takes the optimal daily operation benefit of energy storage under the given configuration as the optimization objective; the probabilistic power flow method and C-PSO are used to solve the bi-level model. The experiment shows that this method ensures the stability of the new energy distribution network in the plateau area, reduces the amount of abandoned wind energy and the operating cost, and improves the local accommodation capacity of the core higher than the distribution network.

Enhancing Renewable Energy Accommodation by Coupling Integration Optimization with Flexible Retrofitted Thermal Power Plant

Thermal power units (TPUs) play a crucial role in accommodating the high penetration of renewable energy sources (RESs) like wind turbines (WTs) and photovoltaics (PVs). This paper proposes an evaluation framework to quantitatively analyze the flexibility potential of retrofitted TPUs in enhancing the accommodate capability of RESs through coupling integration and optimal scheduling. Firstly, the coordination framework for coupling TPUs with RESs is outlined, including a comprehensive analysis of benefits and implementation strategies. Secondly, an annual optimal scheduling model for TPUs and RESs is developed, incorporating deep peak regulation services, ladder-type constraints for retrofitted TPUs, and their operational characteristics before and after the coupling integration. Thirdly, indices to evaluate RES accommodation levels and TPU regulation capacities are proposed to quantify the performance of power sources. Finally, a real-world case study is conducted to demonstrate that integrating retrofitted TPUs with RESs through coupling significantly enhances RES utilization by 3.6% and boosts TPUs’ downward regulation capabilities by 32%.

Investigation of solar accommodation via storage configuration in district heating system based on granularity analysis

In the pursuit of achieving carbon neutrality, it is essential to advance the broad accommodation of renewable energy for the realization of a low-carbon district heating system (DHS). The heat storage configuration serves as an effective assurance for facilitating the accommodation of renewable energy in DHS. This paper analyzes the impact of heat storage configuration on the accommodation of solar energy in DHS, employing a granularity analysis method. This study proposes an optimization method for determining the maximum solar energy accommodation rate in solar-assisted DHSs using the granularity analysis method. Furthermore, this study optimizes the heat storage capacity configuration to facilitate varying ratios of solar energy accommodation. Finally, a technical-economic analysis of the solar-assisted DHS is performed in the context of rising energy cost. The case study reveals that greater granularity leads to a higher solar energy accommodation rate. Specifically, when the granularity increases from 0.43% to 22.22%, the solar energy accommodation rate increases by 8.01%. Moreover, the heat storage capacity configuration increases with the increase of the solar energy accommodation rate, while the heat storage capacity required to accommodate per unit of solar energy decreases. Additionally, as the granularity increases from 0.43% to 22.22%, the heat storage capacity configuration under the same solar energy accommodation ratio increases gradually. This study explores the potential of granularity-based heat storage configuration optimization in promoting solar energy accommodation and achieving the economy of DHS, which is of great significance for the decarbonization of DHS.

Grey-box model-based demand side management for rooftop PV and air conditioning systems in public buildings using PSO algorithm

As the major power consumer in buildings, Heating, ventilation and air conditioning (HVAC) systems can significantly contribute to the economical operation of the power system during the peak periods in summer or winter, by flexibly responding to the grid demands. Indoor air temperature set-point resetting is a typical passive demand response (DR) control strategy that have potentials to be widely implemented by inverter air conditioners in residential buildings. However, in the existing small and medium-size public buildings, the compressor motor of HVAC systems mostly does not allow for stepless speed changes. This means that the indoor temperature set-point resetting strategy may results in frequent on/off switching of the chiller plant, leading to a compromised lifespan. Although rooftop photovoltaic systems (PVs) are expected to be widely adopted in new buildings, their potential for peak load shaving or valley load filling has received limited investigation. This study proposes a grey-box model-based demand side management (DSM) method for variable air volume systems (VAVs) and rooftop PVs in public buildings. The DSM method utilizes the particle swarm optimization (PSO) algorithm to determine optimal indoor air temperature and/or evaporator outlet water temperature set-point schedules for the VAVs, as well as optimal charging/discharging schedules for the storage battery of rooftop PVs. This approach aims to reduce the peak power demands of the integrated system without causing severe thermal discomfort, increasing chiller mechanical costs (refers to frequent on/off switching of the chiller plant in this paper), or overcharging/over-discharging of storage batteries. The results of case studies demonstrate that the strategy of co-resetting indoor air temperature – evaporator outlet water temperature set-points outperforms the indoor air temperature set-point resetting strategy in terms of both peak power demands reduction and mechanical cost saving when applied to the VAVs in low performance buildings. In comparison, for the VAVs installed in normal buildings, both the strategies yield significant decreases in peak power demands and mechanical cost by fully utilizing the thermal capacity of the building internal thermal mass. Furthermore, by implementing the DSM method for rooftop PVs, the integrated system can achieve zero or near-zero net power demands during the DR periods. The proposed DSM method can also be utilized in valley load filling programs to facilitate the accommodation of renewable energy.

A novel virtual synchronous port control strategy for microgrid cluster

AbstractInterconnecting multiple microgrids (MGs) to form a MG cluster (MGC) is significant to improve the MG power supply reliability and increase the new energy accommodation capacity. However, for the traditional MGC in complex operational conditions, the following technologies need to be further researched, such as mutual power support among MGs, voltage support and power quality improvement and so on. Focusing on the above problems, a novel virtual synchronous port control (VSPC) strategy for MGC is proposed. Firstly, a multi‐port soft open point (SOP) is used to interconnect each sub‐MG in the MGC, to achieve a better flexible interconnection among sub‐MGs. Secondly, on this basis, the VSPC strategy is proposed. By adopting the DC voltage control of multi‐port SOP and the virtual synchronisation control of interconnecting ports, multiple voltage source converters (VSCs) are cluster controlled to provide the sub‐MGs with superordinate ports with virtual synchronisation characteristics, which ensures the dynamic balance of the power inside the MGC and achieves better voltage and frequency support capability. Finally, the example results verify the feasibility and effectiveness of the proposed VSPC strategy.

A day-ahead coordinated scheduling strategy for source storage and load considering demand response and lines loss

Day-ahead scheduling strategy is an effective way to improve the renewable energy accommodation. To increase the renewable energy accommodation in the regional power grids, reduce the total costs of the power system, and improve the supply reliability of the power system, this research suggests a multi-time-scale “source-storage-load” coordinated dispatching strategy that considers the distribution and characteristics of pumped energy storage and loss of the network. Taking the wind curtailment penalty costs, the system operating costs, and the load loss penalty costs as the objective functions, a day-ahead coordinated scheduling strategy for source storage and load considering demand response and lines loss is established. Finally, the commercial software package CPLEX is called through the MATLAB platform to complete the optimization of mixed integer programming. Simulation results shows that the proposed scheduling strategy could build the power generation plant, effectively adjust the output power of pumped storage, and regulate the assumption of translationable load and transferable load.

Influence of Gas-Surface and Gas-Gas interactions on the energy accommodation coefficient in non-equilibrium hypersonic gas flows

Accurate accommodation coefficients are crucial in predicting aerodynamic force and heating in hypersonic rarefied flows. This study employs molecular dynamics simulations to investigate the characteristics of non-equilibrium hypersonic flow and its impact on the energy accommodation coefficient (EAC). Our findings reveal that the non-equilibrium gas flow in the gas-surface interaction region comprises an equilibrium subsonic flow, an incident hypersonic flow, and its reflected counterpart. Gas-surface and gas–gas interactions occur simultaneously as gas atoms incident toward the solid surface, with the latter enhancing the EAC by altering the ratios of collision types. Overall, an increase in the ratios of trapping-desorption and permanent-adsorption collisions enhances the EAC at the interface. Results indicate that the number density of the subsonic flow determines the transition from immediate-reflection collisions to trapping-desorption collisions, while the ratio between the potential well depth and the internal energy of the subsonic flow determines the occurrence of permanent-adsorption collisions. These findings disclose the influence of the gas-surface and gas–gas interactions on the atomic collision types and EAC in a hypersonic flying interface, providing valuable insights for predicting the aerodynamic heating in rarefied gas flow.

Performance study of 660 MW coal-fired power plant coupled transcritical carbon dioxide energy storage cycle: Sensitivity and dynamic characteristic analysis

As the demand of modern society for electrical energy continues to rise, the combustion of fossil fuels has led to deterioration of global climate due to the emission of greenhouse gases. The introduction of zero-carbon goal has spurred rapid development of renewable energy. However, the intermittent nature of it has revealed the growing issue of insufficient capacity in existing power systems. To tackle this challenge and enhance the adaptability of power systems, improving the flexibility of coal-fired power plants has become a critical objective.In this work, a novel solution is proposed to address the lack of renewable energy accommodation capacity. It is the method of coupling transcritical carbon dioxide (T-CO2) energy storage cycle with the 660 MW coal-fired power plant (CFPP), using energy storage process to further reduce unit load and energy release process to increase it. The results show that, under the design operating parameters, CFPP achieves load increase and decrease rates of 70.32 MW/min and 35.04 MW/min, respectively. Moreover, at a thermal storage temperature of 353.1 K, T-CO2 energy storage cycle achieves a round-trip efficiency of 61.37% and an energy storage density of 0.989 kWh/m3. The results indicate that the combined system exhibits excellent performance, particularly under relatively lower thermal source temperature.