Optimization Of Hybrid Energy System Research Articles

Optimal design and analysis of a grid‐connected hybrid renewable energy system using HOMER Pro: A case study of Tumbatu Island, Zanzibar

AbstractThis study addresses the pressing issue of quality electricity access in remote regions, with a specific focus on Tumbatu Island in Tanzania. Most studies on quality improvement concentrate on low‐voltage distribution lines and leave high‐voltage (HV) transmission lines behind. It is essential to address quality issues in HV lines due to their critical role in electricity transmission and distribution infrastructure. The objective of the study is to improve the voltage profile on the island's HV transmission line by identifying the optimal hybrid energy system comprising solar PV, wind turbine, and battery technologies. The study begins by presenting the total power demand and consumption on Tumbatu Island, which are important factors in designing an efficient energy system. The findings reveal a power demand of 7173 kW and a consumption of 28540 kWh/day, with an average scaled value of 1507.9 and 6000 kWh/day. To achieve the desired voltage profile improvement, the research incorporates HOMER Pro software for simulating and analyzing various hybrid system configurations. Essential input parameters, such as costs, resources, technology components, and load, are considered in the simulation process. The software generates a ranked list of options based on the system's net present cost (NPC). The simulation results demonstrate that the integration of solar PV, wind turbine, and HV lines provides a substantial improvement in the voltage profile, increasing it from 29.6 to 31.23 kV during peak demand periods. This solution proves to be the most economically viable, with the lowest NPC of $4,003,851 and a relatively short payback period of 3.79 years. In addition, a sensitivity analysis is performed to identify the most influential parameter in the system's performance. Wind speed is found to have the greatest impact, emphasizing its significance in the design and operation of the hybrid energy system. The implementation of this optimal hybrid renewable energy system on Tumbatu Island will not only improve the voltage profile and meet the island's energy needs but also shall contribute to global efforts in reducing pollution and the cost of electricity to the Tumbatu Island population. Moreover, it addresses the current and future demands for clean energy, underlining its importance in achieving sustainable and accessible electricity in sub‐Saharan Africa and beyond.

Multi-objective optimization of Hybrid Energy Systems based on Life Cycle Exergy and Economic criteria

The present study aims to develop a novel optimal design of hybrid energy systems based on exergy and lifecycle concepts using genetic algorithms. The model consists of both stand-alone and on-grid options with scenarios for exchanging energy with the grid. The objectives include cost minimization or benefit maximization primarily, and lifecycle exergy efficiency, i.e., cost as the sustainability index secondarily. This research considers renewable sources such as solar, wind, hydropower, and hydrogen production and storage in addition to conventional diesel generators. The optimization was performed subject to weather conditions and solar radiation profiles, demand, and environmental or economic aspects. Also, the model contains various modules such as water-heating, waste energy utilization, as well as the options of power exchange with the distribution network and injection of hydrogen produced from excess renewable sources into the gas network. The application was demonstrated in a case study, where specific demands and the climate of Tehran were assumed. The case study considers four scenarios, including standalone, completely on-grid, on-grid with a non-backup generator, and on-grid without an energy sale option. The first optimal objective, the levelized unit cost of energy for the standalone system, is $0.22 per kWh. Moreover, the second optimal objective, the lifecycle exergy cost, ranges from 1.93 to 4.13 in different grid-connection states.

Effects of dispatch algorithms and fuel variation on techno-economic performance of hybrid energy system in remote island

A stand-alone hybrid energy system is needed to mitigate the growing demand for future energy and to reduce emissions generated by conventional fuel sources. This work shows and proposes an optimum hybrid energy system configuration with less environmental pollution for a coastal region of Bangladesh with a load demand of 292.20 kWh/d and a peak load of 41.14 kW. This research presents the cost of energy (COE) and net present cost (NPC) for a PV-wind hybrid system with five alternative fuel generator technologies. For each possible configuration, the effects of three alternative dispatch algorithms, load following (LF), cycle charging (CC), and combined dispatch (CD), are examined. All three algorithms were validated using a genetic algorithm (GA), Cuckoo search algorithm (CUSA), Constrained Particle Swarm Optimization (CPSO), Harmony search algorithm (HSA), and Non-dominated Sorting Genetic Algorithm (NSGA-II). Furthermore, a sensitivity analysis is also conducted by utilizing the gasoline price, discount rate, battery cost, PV cost, and inflation rate. The results show that the PV-wind-natural gas-based system provides the minimum COE (0.196 USD/kWh) and NPC (270,483 USD) when the CD algorithm is followed. For the same optimal hybrid energy system, the COE is 0.201 USD/kWh, 0.0998 USD/kWh, 0.101 USD/kWh, 0.101 USD/kWh, and 0.0987 USD/kWh respectively for GA, CUSA, CPSO, HSA, and NSGA-II. However, COE increases by 8 % (0.212 USD/kWh) and 15 % (0.225 USD/kWh) when the CC and LF algorithms are followed. In addition, a comparison of all configurations reveals that the PV-wind-biomass configuration with the CD algorithm excludes biomass generators to lower the COE, making the system emission-free.

Optimal planning and configuration of adiabatic-compressed air energy storage for urban buildings application: Techno-economic and environmental assessment

As urbanization and demand for energy increase, the importance of localized renewable energy resources and energy storage system solutions becomes more prominent. Adiabatic-compressed air energy storage (A-CAES) has been identified as a promising option, but its effectiveness in decentralized applications is not widely concerned. This study aims to plan and design a decentralized A-CAES system to enhance its significance within urban building infrastructure. The focus is on the optimal design of a decentralized A-CAES system for urban building utilization through a comprehensive analysis of its thermodynamic, techno-economic, and environmental aspects. A sizing-designing approach inducing simulation and optimization is proposed to customize the A-CAES system according to the specific application requirement. To do so, this study investigates several energy management operation strategies (EMOS) toward different potential applications of decentralized A-CAES to maximize the system's value and adaptability during the project's lifetime. Multiple scenarios concerning managing solar PV-surplus power are proposed to investigate the overall performance of the proposed model. Additionally, a sensitivity analysis (post-optimization) is conducted to ensure the model's applicability across different case studies. The results demonstrate that an energy cost saving in the range of 0.015–0.021 $/kWh is achieved for the optimal hybrid system in which the A-CAES system is planned for solar photovoltaic (PV) integration and seasonal load shifting, leading to shaving the grid peak demand. Adopting such an A-CAES-PV hybrid system allows for achieving a 52 % electrical load management ratio and 65 % carbon emission reduction compared to the primary power system (grid). Furthermore, under the worst-case scenario (zero selling back), such an optimal hybrid energy system (HES) achieves a PV self-consumption rate of around 92 % and a payback time of 15.5 years. This analysis provides useful insights for policymakers, building owners, and energy planners interested in implementing sustainable and energy-efficient solutions, especially in the feasibility study phase.

Optimizing Security Systems with an Optimum Design of a Hybrid Renewable Energy System

Security systems play a crucial role in protecting individuals and assets within diverse infrastructures, including seaports. The uninterrupted operation of these systems heavily relies on a continuous power supply, as any disruptions can lead to severe consequences. Therefore, security systems are classified as critical loads requiring uninterrupted power availability. This study focuses on the investigation of an optimal hybrid energy system (HES) to ensure a reliable power supply for security systems in two seaports located in Turkiye. Through the utilization of the HOMER software, optimization analyses were conducted, considering both conventional sources such as grid-generator or grid-generator-battery configurations, as well as off-grid and on-grid HES solutions integrating photovoltaic (PV) and wind turbine technologies. The findings reveal that on-grid HES solutions incorporating PV and wind technologies offer a more cost-effective and dependable energy supply for security systems in seaports, surpassing traditional alternatives. This study represents a significant contribution to the existing literature, as it presents the first comprehensive optimization study on the design of HES for security systems. The outcomes serve as a valuable reference for future research endeavors in this field.

A Techno-Economic Optimal Evaluation and Feasibility Analysis of Hybrid Microgrid Electrification for Smart Cities in Tamil Nadu

The cost-effectiveness of the hybrid design of microgrids for determining if a hybrid MG system is necessary is taken into consideration as the study focuses on improving power access in an optimal and economical manner. Both the cost of electricity (COE) and the loss of power supply probability (LPSP) of the hybrid MG design are optimized. The hybrid microgrid design including the photovoltaic (PV)-wind systems with battery storage and diesel generators are modeled and optimized for technical and economic feasibility using MATLAB. The energy management technique is applied between hybrid energy sources and loads. For this hybrid microgrid energy management system, an optimisation approach called spider monkey optimization (SMO) is employed. Using their distinct fission and fusion techniques, spider monkeys always engage in natural foraging behavior. Here, a variety of common constraints related to PV, wind, energy storage elements, inverters, and diesel generators with a variety of cost functions and dimensions are resolved by the proposed optimization method. The SMO optimization method is used to find a utilitarian optimal hybrid energy system configuration with a minimum COE, minimum LPSP, and leading renewable factor to meet the customer load throughout the entire time horizon.

Technical and economic appraisal for harnessing a proposed hybrid energy system nexus for power generation and CO2 mitigation in Cross River State, Nigeria

By creating hybrid energy systems and obtaining a framework that equally satisfies a continuous operation for renewable energy technology, this study presents renewable and sustainable energy options as an integral method to energy transitioning from non-renewable to renewable energy utilization in Cross River State, Nigeria. For a needed load of 2424.25 kWh/day in Cross River State, this study focused on proposing a designed hybrid energy system (HES) nexus, mitigating CO2, and appraisal of the technical and economic viability. To accomplish this, HOMER software was utilized in simulating the ideal components that suggested a HES nexus. The software enabled the selection of the optimal HES using various renewable energy sources since it predicts future electrical demand, wind speed, solar irradiation, and temperature. Economic results obtained showed that the proposed HES's Levelized cost of energy (LCOE), net present cost (NPC), and operating cost (OC) were $0.89/kWh, $10,138,702 and $134,084.37 respectively. Further technical appraisal showed that the renewable energy conversion systems (RECs) make up 78.74% of the proposed HES. The photovoltaic (PV) arrays were primarily responsible for the hybrid energy system's electricity output. The annual electrical energy output was 1,984,111kWh (89.4%), produced by the PV arrays. The generic fuel cell produced the least, at 29,957kWh/year, accounting for just 1.35% of the total electricity produced. However, the wind power plant produced 205,365kWh/year annually. Furthermore, comparing the HES with diesel-powered generators, the system achieves a net-zero carbon emission status. Therefore, it has proven to be the most reliable energy as it will solve the problem of energy demand and reduces carbon emissions in Cross River State, Nigeria

Multi-objective optimization of a hybrid energy system integrated with solar-wind-PEMFC and energy storage

The move towards achieving carbon neutrality has sparked interest in combining multiple energy sources to promote renewable penetration. This paper presents a proposition for a hybrid energy system that integrates solar, wind, electrolyzer, hydrogen storage, Proton Exchange Membrane Fuel Cell (PEMFC) and thermal storage to meet the electrical and heating demands of a student dormitory in Shanghai. The proposed system is optimized to simultaneously account for multiple objectives, including economy, environmental benefits, and grid interaction, measured by Equivalent Annual Cost (EAC) for the life cycle of 20 years, Primary Energy Saving Ratio (PESR) of the heating system and Grid Interaction Level (GIL) of the electrical system. The effectiveness of the optimization results from NSGA-II is verified and compared with MOPSO to determine the optimal installation configuration and operation strategies. The results highlight the significance of energy storage in enabling greater renewable integration and the potential of hydrogen to play a vital role in the transition to a low-carbon economy. The optimal design of the proposed hybrid system can meet the power and heat demand of a student dormitory with a floor area of 2679m2. The Pareto-optimal solutions of PESR and GIL for NSGA-II fall within the range of (89 %, 104 %) and (70 %, 88 %), respectively. A significant number of Pareto-optimal solutions cluster around an EAC of approximately 160 k RMB. The optimization by MOPSO exhibited the similar results. Additionally, the sensitivity analysis provides insights into the sensitivity of objectives to changes in optimal design parameters, facilitating the design and optimization of similar hybrid energy systems integrated with a closed loop for hydrogen production and utilization in the future.

Techno-economic analysis and optimization of hybrid energy systems based on hydrogen storage for sustainable energy utilization by a biological-inspired optimization algorithm

Wind energy resources based on hydrogen energy storage systems are recognized as clean alternative sources from the perspective of sustainable development. A low-cost hydrogen energy storage system is recognized as a cornerstone of a renewables-hydrogen economy. The hybridization of wind turbines, as a non-dispatchable resource, and hydrogen storage system, as energy storage, can provide a promising hybrid energy system. The main outlook of the present paper is to develop a biological-inspired optimization algorithm for the optimal design of an off-grid wind power generator considering a hydrogen energy storage system. The parameters of the system are optimized with respect to two objective functions, namely the total cost, and load loss of the system. To obtain an efficient optimum capability, an artificial bee colony optimization method is introduced. Its results are compared with the results of the particle swarm optimization algorithm. Eight different small horizontal-axis wind turbines are used for the optimal design of an off-grid system. A sensitivity analysis is conducted by varying the capital cost of the components to determine how total cost and load loss are affected by the change of the input variables. Simulation results show that at load loss = 0 and 20 %, the cost of energy (COE) is around 0.6907 and 0.3771 $/kWh, respectively. The variation of wind turbine (WT) and hydrogen storage system capital costs have a significant impact on total cost value. Among the investigated systems, the Fortis-WT- hydrogen storage system with 0.5987 $/kWh COE has the minimum cost and maximum reliability (100 %). The superiority of the proposed algorithm compared to the particle swarm optimization algorithm is confirmed.

Superior Optimization for a Hybrid PEMFC Power System Employing Model Predictions

This research investigated the impacts of model prediction on the optimization of hybrid energy systems using a system consisting of solar panels, batteries, a proton exchange membrane fuel cell (PEMFC), and a chemical hydrogen generation system. A PEMFC has several advantages, such as low operating temperatures, fast response times, high power density, and environmental friendliness, and it can convert hydrogen into electricity. However, because hydrogen costs are an important consideration, the PEMFC is usually integrated with hybrid energy systems to guarantee system sustainability. Therefore, in this study, a whole-year household load and solar radiation data were applied to optimize the system components and power management, thereby reducing the system cost by 42.43% and improving system sustainability by 7.05%. The system responses showed that some hydrogen consumption might be saved if the solar and load profiles could be foreseen. Two prediction models were developed that could accurately forecast the radiation and load profiles. Next, a second-year dataset was employed to verify the effectiveness of the model prediction. The results showed that the system cost was reduced by 40.20% without model prediction and by 44.06% with model prediction compared to the original system settings. Finally, experiments to illustrate the feasibility of the hybrid energy system were conducted using prediction models. Based on the results, the model prediction was deemed effective in improving the performance of hybrid energy systems.

Technoeconomic Optimization of a Photovoltaic Wind Energy‐Based Hydrogen Refueling Station: A Case Study

Increased use of renewable energy sources is expected to contribute to long‐term sustainability and robust economic growth. A better global economy and lower greenhouse gas emissions are possible due to intensive research into more effective energy production, storage, and utilization technologies. The exciting solution for advancing the development of green hydrogen production and the clean transportation sector is the conversion of electrical energy generated from wind parks into green hydrogen. Therefore, herein, a technoeconomic optimization of hydrogen production for refueling fuel cell vehicles by comparing two different renewable energy sources is presented. Results obtained in this article demonstrate that Riyadh possesses sufficient wind speed and sunlight, which can be used to produce renewable hydrogen. It is evident from the evaluated and optimized results that the selected wind‐based hybrid energy system has the lowest net present cost, levelized cost of energy, and levelized cost of hydrogen of $247,654.00, $/kWh 0.1720, and $/kg 4.23, respectively, as compared to the other system counterpart, making the selected optimized hybrid energy system the preferred choice to fulfill the electricity and hydrogen production demand of the refueling fuel cell vehicles. It is expected that the stakeholders through this study can encourage the production of hydrogen in Saudi Arabia.

Assessment and Selection of a Hybrid Energy System for Small Agricultural Farms

A comprehensive system for evaluating the efficiency of green hybrid energy systems for small farms on the basis of the production pattern, energy consumption, and state of natural resources in typical small farms is elaborated, and a method for carrying out the assessment is defined. Six different structures of green hybrid energy systems are developed taking a small farm in southern China as an example. The developed energy system structures are compared using the analytic hierarchy process (AHP) and TOPSIS methods. It has been shown that the optimal hybrid energy system can fully and efficiently utilize the natural resources and wastes on the farm territory, and features significant economic and environmental advantages in comparison with alternative solutions.

Optimization of a grid-connected hybrid energy system: Techno-economic and environmental assessment

This study aimed to provide sustainable, secure, and clean energy for Tuzla campus of National Defense University Turkish Naval Academy. Research problem was to find technically and economically optimized hybrid energy system consists all or some of solar, wind, biomass, and battery sources in addition to grid and diesel generator of the campus. Greenhouse gas emissions of the optimum solution were calculated for environmental effect analysis. Additionally, the effects of the variables such as solar radiation, wind speed, expected inflation, and electricity unit prices on system were analyzed. The study conducted via Homer software under two scenarios based on legal regulations. As a result, the optimum system in both scenarios is a grid-connected hybrid system consisting of photovoltaics and wind turbines. Results presented reduction in net present cost of energy by 86.2%–90%, unit cost of energy by 92.7%–95.8%, operation & maintenance costs by $862,093–$933,695, emissions by 79%–82%. According to both optimization results and sensitivity analysis, no biomass generator was discovered in optimum solutions. It was also observed that batteries could be in the optimum system depending on economic variables. It is believed that this study, in which solar, wind, and biomass as well as battery, grid, and diesel generator were evaluated together under legal based scenarios, can be a reference for further researches due to its diversity in system components and its scenarios consisting legal aspects. The study also can serve as an example and a guide for other public university campuses.

Building a Sustainable Energy Community: Design and Integrate Variable Renewable Energy Systems for Rural Communities

This study proposes a decentralized hybrid energy system consisting of solar photovoltaics (PV) and wind turbines (WT) connected with the local power grid for a small Najran, Saudi Arabia community. The goal is to provide the selected community with sustainable energy to cover a partial load of the residential buildings and the power requirements for irrigation. For this, a dynamic model was constructed to estimate the hourly energy demand for residential buildings consisting of 20 apartments with a total floor area of 4640 m2, and the energy requirements for irrigation to supply a farm of 10,000 m2 with water. Subsequently, HOMER software was used to optimize the proposed hybrid energy system. Even considering the hourly fluctuations of renewable energies, the artificial neural network (ANN) successfully estimated PV and wind energy. Based on the mathematical calculations, the final R-square values were 0.928 and 0.993 for PV and wind energy, respectively. According to the findings, the cost of energy (COE) for the optimized hybrid energy system is $0.1053/kWh with a renewable energy penetration of 65%. In addition, the proposed system will save 233 tons of greenhouse gases annually.

Modeling and optimization of the energy system for series hybrid electric fixed-wing VTOL

In this paper, the fixed-wing vertical take-off and landing (VTOL) aircraft is studied. Based on the typical mission profile, the flight process of fixed-wing VTOL aircraft is divided into rotor mode and fixed-wing mode, and the dynamic models of the two modes are established respectively. The power transmission model of the series hybrid electric system is established, the concept of hybridization for power (Hp ) is introduced, and an optimization method of power allocation based on Hp is proposed. The optimization method is verified by simulation, and the results show that, compared with the pure electric energy system, the performance of the optimized hybrid energy system is improved obviously.

A review on configuration optimization of hybrid energy system based on renewable energy

Hybrid energy system based on renewable energy is an important way to solve current energy and environmental problems. However, its achievable benefits need to be realized through an integrated optimization that considers optimization objectives, optimization models, and optimization algorithms. In this paper, the integrated structure and configuration optimization techniques of the hybrid energy system based on renewable energy (RE-HES) is summarized. The performance indicators, system characteristics, model construction, and solutions of RE-HES optimized configuration are comprehensively reviewed. Current review highlights the diversification of performance evaluation index, consideration of uncertainty and dynamic properties, superstructure approaches and intelligent algorithms.

Development of an Intelligent Solution for the Optimization of Hybrid Energy Systems

This paper presents a proposal for the development of a new intelligent solution for the optimization of hybrid energy systems. This solution is of great importance for installers of hybrid energy systems, as it helps them obtain the best configuration of the hybrid energy system (efficient and less expensive). In this solution, it is sufficient to enter the name of the location of the hybrid energy system that we want to install; after that, the solution will show the name of the best technology from which the optimal configuration of this system can be obtained. To accomplish this goal, the study relied on the ontology approach for two reasons, one of which is related to the nature of hybrid systems, because it is characterized by a large amount of information that requires good structuring, and the second reason is the interaction of hybrid energy systems with the external environment (climate, site characteristics). Afterward, to develop the knowledge base of the ontology, many steps were followed, the first of which is related to a detailed study of the existing one and the extraction of the basic elements, such as the concepts and the relations between them, followed by the development of the rules of intelligent reasoning, which is an interaction between the elements of the ontology through which all possible cases are treated. The “Protégé” software was used to edit these elements and perform the simulation process to show the results of the developed solution. Finally, the paper includes a case study, and the results show the importance of the developed solution, and it is open to future developments.

Experimental Characterization of Transitory Functioning Regimes of a Biomass Stirling Micro-CHP

Micro-cogeneration (micro-combined heat and power) is a technology that simultaneously produces decentralized thermal and electrical energy with a power of less than 50 kWel. This technology consists of using the waste heat generated by a thermodynamic process to meet the heating and hot water demands of buildings. The use of biomass as a fuel offers important advantages: use of a renewable energy, carbon neutrality, availability, and low cost. Furthermore, the analysis and optimization of hybrid energy systems, which include existing micro-cogeneration systems powered by renewable energy, is a scientific challenge needing experimental characterization of such micro-cogeneration systems. In this context, a biomass Stirling micro-CHP unit (μCHP), was tested to characterize its energy performance. A dynamic model based on these experimental investigations was developed to evaluate its thermal power output and energy efficiencies. The dependence of the nominal load on the water flow rate of the consumer and the inlet temperature of the fluid heated by the cogeneration system was studied. Results showed that the flow rate of the heat transfer fluid rejecting heat from the μCHP unit influences the temperature of the heat transfer fluid exiting the μCHP to supply domestic hot water to the user, which, if too high, will prompt the self-guarding mechanism of the machine.

Diffuser augmented wind turbines – a case study for hybrid energy system applications and comparison with horizontal axis wind turbines

ABSTRACT Hybrid energy system that combines diffuser-augmented wind turbines with photovoltaic panels and batteries are proposed in this research. ANSYS fluent® is used to simulate diffuser performance and ratified experimentally. HOMER® is used to perform a techno-economic analysis of the proposed hybrid energy system in terms of the levelized cost of electricity and the net present cost. Units of 1 kW wind turbines, 1 kW solar PV units, and 1 kWh Li-ion battery units are being used in the simulation. Input parameters like solar radiation, wind speed, and electricity tariff are considered for a typical location in Palakkad, India (10.7976° N, 76.7430° E). The proposed hybrid system with off-grid and on-grid mode are analyzed, and the results are presented. For 20 years project life, the proposed optimal on-grid hybrid energy system based on diffuser-augmented wind turbines has a levelized cost of electricity of $0.0044/kWh and a net present cost of $22,857. The corresponding values for the optimal on-grid hybrid energy system based on wind turbines are $0.0096/kWh and $41,143, respectively. Sensitivity analysis is performed on wind speed, solar radiation, and export tariff. According to this study, the usage of diffuser augmented wind turbine benefits low-speed wind regimes.

Making Optimal Location-Sizing Decisions for Deploying Hybrid Renewable Energy at B&Bs

The adoption of renewable energy (RE) is a promising business strategy for bed and breakfasts (B&Bs) to mitigate climate change while maintaining a competitive edge. However, there is still a lack of analytical studies to determine an optimal RE mix for tourism accommodations. This study thus proposes a practical approach to enable all B&Bs to make optimal RE decisions for their facility. A mixed-integer programming (MIP) model is developed and tested in a case study. The model successfully identifies an optimal hybrid energy system for two scenarios, the base case that generates 116,942 kWh of electricity annually at the cost of USD 21,499, and the unconventional technology case that generates 114,474 kWh of electricity annually at the cost of USD 24,670. Compared to purchasing all the required electricity from the power grid, both scenarios can save more than 26 tons of CO2e/year. The analysis provides valuable information for B&Bs to initiate a smooth energy transition with affordable costs. This study considers various energy components, including hybrid RE, batteries, the power grid, self-sufficiency targets, and various RE technologies. Therefore, B&Bs can choose a preferred self-sufficiency target where RE satisfies a specific portion of the energy demands and the power grid satisfies the rest. The model can also evaluate the tradeoff between investing in RE technologies and purchasing larger batteries. These findings will assist B&Bs in accelerating the adoption of RE globally.