Diesel Generator System Research Articles

Techno-economic analysis of hybrid renewable energy systems for cost reduction and reliability improvement using dwarf mongoose optimization algorithm

The global energy crisis, particularly in isolated and remote regions, has increased interest in renewable energy sources (RESs) to meet growing energy demands. Integrating RESs with energy storage systems offers a promising solution to mitigate fluctuations and intermittency, but concerns about cost and reliability remain. This study explores the optimal design of various microgrid configurations, combining photovoltaic (PV), wind turbine (WT), battery energy storage system (BESS), and diesel generator (DG) systems for Najran city, Saudi Arabia, via real-world meteorological and load demand data. The Dwarf Mongoose Optimization Algorithm (DMOA), alongside the salp swarm algorithm (SSA) and whale optimization algorithm (WOA), was applied to minimize the levelized cost of energy (LCOE) while improving system reliability. The results demonstrate that the PV/BESS configuration, although cost-effective with an LCOE of 0.038 USD/kWh, fail to meet reliability constraints with a loss of power supply probability (LPSP) of 0.679. In contrast, the PV, WT, BESS, and DG configurations achieved an LPSP of 1.9 × 10^--8% with an LCOE of 0.199 USD/kWh, offering a robust and reliable solution for the region's energy needs. This paper presents a novel application of the DMOA for optimizing hybrid renewable energy systems, demonstrating its effectiveness in achieving a balance between cost and reliability. This strategy provides a viable approach for sustainable energy planning in similar regions facing energy challenges.

Enhancing energy control for a hybrid system comprising a wind turbine, diesel generator, and storage systems

The increase in demand for electrical energy has made renewable energy sources, such as wind power, increasingly attractive. However, intermittency and variability represent the major problems of these types of energies. The hybridization of several energy sources allows to have a reliable and efficient supply system. This paper was interested in the control of a hybrid energy system, which includes a wind turbine, storage systems (batteries and super-capacitors) and a conventional diesel generator, with the aim of generating constant power. A control strategy is developed taking into account the various constraints of the hybrid system. Both of storage systems as well as the diesel generator operate according to the modes presented in the supervision algorithm to absorb and compensate the fluctuation of the wind energy and reach to a constant energy flow. The super-capacitor operates before the battery to absorb the power peaks in both charge and discharge modes. The hybrid system is simulated using MATLAB/Simulink software, and the results are provided in order to show the effectiveness of this control strategy.

The health status assessment method and practice of emergency diesel generator system in nuclear power plant based on deterioration degree

Abstract Due to the complexity of the emergency diesel generator (EDG) system in nuclear power plants and the lack of detailed equipment-level health status assessment models, this article introduces a deterioration-based system health status assessment method. Taking the large and complex EDG system as a pilot, the method combines monitoring data and maintenance information of the EDG to achieve dynamic assessment of the health status of the EDG system at the equipment level. This provides guidance for predicting and repairing faults of EDGs in nuclear power plants. Additionally, this method can be extended to other large and complex systems.

Numerical study of a hybrid system of solar panels, a diesel generator, and a wind turbine using a battery system

This paper gives an overall quantitative analysis of a hybrid renewable energy system (HRES) incorporating solar photovoltaic system, wind system, diesel generator and battery storage system. The system is aimed at coordination the management of the energy resources for providing the off-grid or remote facilities. The best intervention is thus to increase the consumption of renewable energy sources to minimize the reliance on diesel generators. The findings show that the hybrid system is capable of supplying different levels of power, which is pumped from the solar PV panels at maximum of 30.38 kW for the photovoltaic system at maximum solar intensity, and the wind power system to a maximum of 3213 kW of power generation under standard wind potential. The diesel generator serves a backup power source, which ranges from 91.24 kW and 864 at a rate of 250 kW during high activity and 5 kW during high-demand periods. Battery storage integration has a crucial part in matching the short-term supply-demand imbalance problem. The study suggests that the hybrid system reduces diesel use, emissions, and improves energy sustainability making the system a worthy proposition for remote areas. The findings therefore affirm the use of hybrid systems in off grid electrification since they operate economically and are eco-friendly.

A reinforcement learning method for two‐layer shipboard real‐time energy management considering battery state estimation

AbstractIncreasing global environmental concerns encourage a continuous reduction in carbon emissions from the shipping industry. It has become an irreversible trend to replace traditional fossil fuels with advanced energy storage technology. However, an improper energy management leads to not only energy waste but also undesired costs and emissions. Accordingly, the authors develop a two‐layer shipboard energy management framework. In the initial stage, a shipboard navigation planning problem is formulated that considers battery state estimation and is subsequently solved using particle swarm optimisation to obtain an optimal speed trajectory. To track the scheduled speed, a reinforcement learning method based on a deep Q‐Network is proposed in the second stage to realise real‐time energy management of the diesel generator and energy storage system. This approach ensures that the state of charge remains within a safe range and that the performance is improved, avoiding excessive discharge from the energy storage systems and further enhancing the efficiency. The numerical results demonstrate the necessity and effectiveness of the proposed method.

Techno-economic study of a hybrid photovoltaic-diesel system for a remote area in southwest Algeria

Exploiting natural sun and wind resources in remote and isolated areas is undoubtedly an excellent decision to generate electrical energy due to their availability and cleanliness. Various systems were used to generate this energy, such as photovoltaics (PV), wind turbine sand other energy systems. Moreover, for optimum energy use, some of these systems are combined either with each other or with other conventional systems, such as diesel generators with PV systems (i.e., hybrid systems). This work aims to present a technical-economic study of PV/diesel autonomous hybrid systems to supply electrical power for an isolated house located in a hot desert climate, Adrar. For optimizing the hybrid systems, hourly input data of solar radiation and load were used according to two configurations, where the annual load is 11.2 kWh/day. The findings showed that the diesel system had a high cost, with a cost for energy of $0.407/kWh and a fuel price of $0.140/l. Among the hybrid power systems but with significant pollution, the proposed hybrid system 2 kw photovoltaic and diesel generator with 2.3 kW has important economic feasibility, where the energy cost amounted to $0.172/kWh. In addition, CO2 emissions are reduced by approximately 5 tons every year compared to an independent diesel generator system.

FACTORS ANALYSIS USE ELECTRICAL ENERGY SOURCES IN MICROGRIDS FROM ENERGY MANAGEMENT SYSTEM POSITION

The analysis of the factors of the use of electrical energy sources in microgrids from the point of view of the energy management system is a comprehensive study aimed at studying and evaluating various aspects of the use of electrical energy in small energy systems that can function independently of centralized energy networks. The main purpose of such an analysis is to identify key factors , which affect the efficiency and stability of the microgrid, as well as in the development of strategies to optimize their operation from the point of view of energy management. To achieve this goal, research is conducted covering the following aspects: technical characteristics of electrical sources, economic aspects, environmental consequences, energy management, social aspects. This is an important stage in the development of energy systems, aimed at creating efficient and sustainable energy solutions for the future. The analysis of the efficiency, reliability and power of various energy sources, such as solar batteries, wind turbines, batteries, etc., was considered. The cost of installation and operation of electric energy sources was calculated. , including the costs of maintenance, maintenance and replacement of equipment. The method of analyzing the impact of the use of various energy sources on the environment and the development of strategies for reducing emissions of greenhouse gases and other harmful substances are given. The essence of energy management systems that allow efficient management of production, storage and distribution of electricity in microgrids to ensure maximum efficiency and stability of system operation is considered. The question of the development of alternative energy sources has become particularly relevant, therefore, considering the existing structures of microgrids, it is advisable to notice the peculiarities of the construction of each microgrid, for example, the structure of a microgrid based on a wind generator can be built in several variants, and in a solar power plant, for efficient operation, the MPPT control algorithm is used, which aims to control the step-up converter in that point of the current and voltage characteristics of the photovoltaic battery, where the maximum output power can be obtained. In such microgrid structures, storage batteries are used for reserve, which are charged through step-up converters. Inverters are used to power the AC load. It is advisable to combine the solar power plant and the wind generator system into one microgrid structure, and to ensure the operation of the microgrid in conditions of low generation of one or both generating units, a diesel-generator system is used. In the built hybrid structure of the microgrid, there are operational costs that must be minimized.

Design and techno-economic assessment of a standalone photovoltaic-diesel-battery hybrid energy system for electrification of rural areas: A step towards sustainable development

The recent persistent power interruption in Nigeria has significantly disrupted commercial activities, resulting in a magnificent economic loss, supply chain ripples and revenue loss. As a result, harnessing renewable energy sources to generate electricity has become a popular choice for satisfying ever-increasing load demand and reducing apprehensions on global warming and reliance on depleted fossil fuels. The goal of this research is to determine whether powering a remote community with a hybrid energy system (HES) is technologically, financially and environmentally viable. The optimum design of a standalone HES with the diesel generator (DG), photovoltaic (PV) and battery storage system (BSS) is provided in this study to satisfy the electrical power needs of a farm settlement in Kura, Nigeria by considering generation constraints and load demand. This research work presents a genetic algorithm (GA) to minimize wearing cost of the system (WCS), minimize the land needed for the installation of the DG and PV system, minimize the total annual cost of the system (TAC) and maximize the benefit to cost ratio and revenue from electricity consumption. The findings of the research showed that PV/BSS/DG system is a prospective solution to satisfy the load requirements with least TAC of 67374 $/yr, annual maintenance cost (AMC) of 2808.2 $/yr, annual fuel cost (AFC) of 32300 $/yr and annual emission cost (AEC) of 774.2023 $/yr. The outcomes of the study show that a considerable TAC, AMC, AFC and AEC savings of 26766 $/yr (28.43 %), 2808.2 $/yr (53.09 %), 32300 $/yr (25.4 %) and 774.2023 $/yr (60.69 %) are recorded when compared with using DG alone. The control approach applied in this study has reduced the operational capacity of the DG and prevented about 41157 kg/yr, 419.19 kg/yr and 22.52 kg/yr of CO2, NOx and SO2 emissions from being injected into the atmosphere. The simulation outcomes of the research demonstrate that the developed model can significantly reduce cost of electricity in rural communities with the application of HES. Hence, a 45.36 % cost of energy saving has been accomplished through the energy management system introduced in the proposed HES. The study's outcomes can be used as benchmarks to help many countries to enhance access to electricity, raise their living standards and stimulate economic growth. The application of the proposed HES in remote communities can result in greater economic and environmental benefits to a general population of rural dwellers. The findings of the research work are beneficial to designers, independent power providers, investors, researchers and electricity consumers that are looking for a feasible power solution.

Feasibility and sustainability analysis of a hybrid microgrid in Bangladesh

The demand for renewable sources-based micro-grid systems is increasing all over the world to address the United Nation’s (UN) sustainable development goal 7 (SDG7) “affordable and clean energy”. However, without proper viability analysis, these micro-grid systems might lead to economic losses to both customers and investors. Therefore, this paper aims to explore the feasibility and sustainability of a hybrid micro-grid system based on available renewable resources in remote hill tracts region of Bangladesh. Nine different scenarios are analyzed here, and a combination of solar, hydro, biogas, and diesel generator systems are found to be the best feasible solution in regard to the least cost of electricity and emission. The optimized result shows that with a renewable fraction of 0.995, the unit levelized cost of energy of the micro-grid system is $0.182 and it emits 54 and 117 times less CO<sub>2 </sub>compared to grid-based and diesel-based systems. Further, the fuel share of the system being 0.5% and greenhouse gas per energy being 0.06425 kg/KWh, validate the system as highly sustainable and eco-friendly. With the ability to fulfill load demands without interrupting supply, and reducing the emissions of greenhouse gases, the designed microgrid can provide sustainable energy solutions to any hill-tracts of Bangladesh.

Optimal planning of solar energy using a sensitivity factor for rural electricity needs in an off-grid system (case study: Sebesi Island, South Lampung, Indonesia)

ABSTRACT Small islands in Indonesia usually have a million beauty and extraordinary natural wealth. However, the development of remote islands is prolonged due to the limited electricity supply on these islands. This limitation occurs because the island is far from the primary power grid or uses a diesel generator (DG). Using the DG will increase the cost of shipping fuel oil through limited sea transportation. Therefore, this study aims to conduct a feasibility study of a solar power plant to meet the electricity needs of Sebesi Island, South Lampung, Indonesia. The availability of solar Energy and limited battery life are the main challenges in providing solar Energy today. Therefore, this study also considers the uncertainty of resources by using the sensitivity factor. This research uses HOMER software. This study assumes operating reserve peak, operating reserve, solar reserve, and lifetime battery life to account for resource uncertainty. This method is very effective in overcoming operational limitations and problems. The research results show that the optimal peak operating reserve, operating reserve, solar reserve, and lifetime battery are 10%, 10%, 10–30%, and 5 years, respectively. To meet the daily electrical energy needs of 505.1 kWh, the minimum net current cost (NPC) and energy cost (COE) are $1.26 million and 0.346 $/kWh, respectively. Therefore, this research succeeded in finding a scenario that takes into account sensitivity factors that are more economical. Compared with a diesel generator (DG) with a capacity of 100 kW, the NPC and COE values are $1.29 million and 0.397 $/kWh. Meanwhile, in terms of technology, solar power systems produce much more energy than DG. This system has an energy of 583,316 kWh/year, while the DG system can produce an energy of 268,469 kWh/year. As a result, this system can also reduce CO2 emissions by 241,812 kg/year.

Construction strategy of diesel generator system for large-scale cloud computing center

Construction strategy of diesel generator system for large-scale cloud computing center

Hydrogen Production using a Hybrid System Built with Renewable Energy Resources in Yenice

Benefits of hybrid renewable energy; has a continuous power supply, has a better return on investment, is independent of the grid, has fewer operating hours of the diesel generator, requires less maintenance than a diesel generator system, and does not need frequent refueling, one-time initial capital required, protects from ever-increasing grid electricity tariffs. On the other hand, the demand for renewable energy sources such as wind, solar, hydrogen, biomass, and geothermal, which are the least harmful to nature and natural life, has increased due to the depletion of fossil fuels used in energy production and the greenhouse gases they have released to the environment. Thus, with the inclusion of renewable energy sources in the system, a rich structure in terms of energy diversity has emerged. An area that simulates a system consisting of renewable energy sources using HOMER Pro software and has an annual average electrical energy need of 3997104 kWh/day was selected. Solar radiation and wind data belonging to the region were taken from NASA Surface and used. The energy system of the area where the feasibility study was conducted consists of a generator, wind turbine, solar panel, hydrogen tank, electrifier inverter, and battery system. The energy produced by the resulting system will be used by 11.26 kg/day hydrogen load and 3997104 kWh/day electrical load. The economic evaluation criteria of the hybrid renewable energy system are the energy unit cost of energy production, the net present value (NPC), and the payback period; The environmental evaluation criteria were determined as the renewable energy rate and emission values evaluation criteria. When the renewable energy rate is at the lowest level, the most economical system is the Gen/PV/WT/Bat/300Htank/ H loaded hybrid system when emissions are not considered, while the Gen/PV/WT/Bat hybrid system has the lowest emissions without considering the cost. When the renewable energy rate is high, the most economical system has been the PV/WT/Bat hybrid system when emissions are not considered.

Multiport Energy Management System Design for a 150 kW Range-Extended Towing Vessel

This paper proposes a multiport energy management system (EMS) and its rule-based expert control strategy for a 150 kW range-extended towing vessel (RETV). The system integrates a diesel generator system, a permanent magnet synchronous motor, a lithium battery, and supercapacitors. To verify its feasibility and effectiveness, the proposed multiport EMS was modelled and tested through MATLAB/Simulink. Simulation results demonstrate that the designed multiport EMS works efficiently under the five typical operating conditions of the 150 kW RETV. In addition, two case studies were conducted and compared to investigate the impact of the battery’s initial state of charge (SoC) on the system’s energy efficiency. It was found that an overall 85% energy efficiency can be achieved for the RETV when the initial SoC is either 75% or 15%. The battery consistently operates within the optimal SoC range of 20% to 80%, and the supercapacitors effectively meet the instantaneous high-power demand.

Optimizing day-ahead energy management with demand response in a PV-diesel-battery system using a hybrid GOA-SNN strategy

This manuscript presents a hybrid technique for the day-ahead energy management strategy of hybrid renewable energy systems (HRES) integrated with demand response (DR). The HRES consists of Photovoltaic (PV), Diesel Generator (DG), and battery systems. The proposed method, named GOA-SNN strategy, combines the Gazelle Optimization algorithm (GOA) and spiking neural network (SNN) to improve outcomes for consumers and utility providers. The objective is to minimize human intervention and leverage advanced bi-directional communication. The focus of this study is on off-grid systems. The proposed strategy determines optimal incentives and power commands to maximize the operation of the HRES within a 24-hour control horizon. The GOA is used to optimize the scheduling of energy resources, considering constraints such as energy demand, battery state of charge, and grid availability. The SNN is used to predict energy demand using historical data and external factors. The strategy utilizes lower electricity prices to influence consumer behavior and identifies the ideal time periods to offer these discounted prices, optimizing the expected benefits of energy management. The proposed technique's performance is evaluated through MATLAB or Simulink simulations and compared against existing methods. The results demonstrate that the GOA-SNN strategy achieves cost savings and reduces computation time, making it an efficient and effective solution for energy management in hybrid renewable energy systems. The existing approach like BSSA, NPO, OSA and proposed technique accuracy becomes 70.23%, 75.59%, 89.42% and 95.21%. From this analysis, it concludes that the proposed method based accuracy is high compared with existing techniques.

Optimal sizing and techno-enviro-economic evaluation of a hybrid photovoltaic/wind/diesel system with battery and fuel cell storage devices under different climatic conditions in Cameroon

Due to advancements in renewable energy technology and their ability to mitigate the issue of global warming, solar and wind energy sources are becoming increasingly popular for power generation. However, the intermittent nature of these sources means that their availability does not always correlate with load fluctuations. Hence, to solve the unpredictability concerns associated with solar and wind energy sources, they may be integrated with storage technologies and conventional energy sources (diesel generators) in a hybrid energy system (HES) to continuously supply the load demand. This paper performs a techno-economic and environmental assessment of hybrid systems integrating photovoltaic (PV), wind turbine generator (WT), and diesel generator (DSL), considering fuel cell (FC) and battery (BAT) storage devices, to supply three non-domestic loads at different locations in Cameroon, namely, Fotokol, Idabato, Kousseri, and Figuil. The Cuckoo Search Algorithm (CSA) is introduced to optimally size the various components of the proposed systems in order to fulfill the load demands in the most cost-effective manner with excellent reliability. The results show that in the short term period, hybrid systems incorporating battery storage devices are more cost effective than fuel cell storage systems. Indeed, the most optimal system found was PV/WT/BAT/DSL at the city of Idabato, with a COE of 0.151$/kWh, 0.180$/kWh, and 0.220$/kWh for high, medium, and low consumers, with corresponding break-even distances of 0 km, 0.14 km, and 0.44 km, respectively. Traditionally, using diesel generator systems for power generation costs 0.469$/kWh, 0.618$/kWh, and 0.766$/kWh, with CO2 emissions of 13694.3 kg/year, 10351.4 kg/year, and 8978.1 kg/year for high, medium, and low consumers, respectively. However, using the PV/WT/BAT/DSL configuration at Idabato in comparison to the conventional diesel generator reduces CO2 emissions in this locality by 94.32%, 95.22%, and 93.79% for high, medium, and low consumers, respectively. On the other hand, the PV/WT/FC/DSL hybrid system at Idabato presents COE of 1.018$/kWh, 1.655$/kWh, and 2.289$/kWh, with saving CO2 emissions of 91.27%, 91.76%, and 94.63% for high, medium, and low consumers, respectively.

Design and Implementation of Digital Twin Diesel Generator Systems

In stationary power generation units such as distributed remote site power systems and ship power systems, diesel engine generator systems are essential for supplying electricity. This paper proposes a digital twin diesel generator system for teaching and research purposes. A five-layer resilient architecture, including a web interface layer, server cluster layer, real-time data layer, controller layer, and equipment layer, is proposed in this paper. Based on the resilient architecture, users are able to build, implement and monitor the digital twin through web interfaces. Apart from MATLAB/Simulink, a modeling tool called M2PLink is developed to allow users to create mathematical models using a block diagram editor similar to Simulink. Various basic blocks for control systems are provided for users to form sophisticated models. These models are converted into executable codes which are downloaded to the simulator in the controller layer, where the real-time simulations are implemented. A web-based real-time monitoring interface with many widgets such as charts, oscilloscopes, and three-dimensional (3D) animation is also provided for users to customize their monitoring interface. All the signals can be traced and all the parameters can be tuned in the monitoring interface. The users are able to interact with the digital twin just like they do with the real system. The proposed system can not only be used for research such as digital twin-assisted real-time online monitoring but also for educational purposes, which is not only cost-effective but can also ensure the safety of the user as well as the equipment.

Operation of The Hybrid Energy Resources with Storage System Participation

This paper focused on the optimal operation of the hybrid energy resources in the off-grid state considering energy storage participation. The hybrid energy resources consist of wind turbine (WT), photovoltaic (PV), diesel generator (DG), and energy storage system for supplying energy to DC and AC load demand with maximum reliability. The operation of the proposed energy system based on energy control and energy optimization is modeled. The energy optimization and energy control are implemented by heuristic and nonlinear quadratic programming approaches via optimal power flow on the resources side. The energy control is done based on the weight sum method in different operation states of the system. Also, the impact of the energy storage system on the hybrid energy resources is considered as backup resources. The energy control modeling is implemented via mathematical simulation and numerical analysis in the two operation states in the summer and winter seasons for verifying the proposed approaches. Finally, the results of the energy control show optimal states of the energy system in supplying demand with considering the energy storage system.

A solar energy-based shore side power system for a ferry service across the Suez Canal

ABSTRACT For more sustainable shipping operation in coastal areas and port cities, shore side power (SSP) systems are attracting widespread interest as a solution to reduce ship auxiliary engine emissions, noise and vibration. The potential of these systems can be further improved by integrating renewable energy into the electricity grid. However, the majority of prior research has focused on investigating SSP systems for large ports in large shipping hub countries. Therefore, in this study, SSP technology is investigated for an inland waterway in Egypt on the Suez Canal utilising real ferries operational data. Green electricity from solar sunshade structures is generated for the SSP system utilising the Egyptian excellent solar energy potential. For this study, the ferry diesel generator, battery and solar systems are modelled in MATLAB/Simulink environment to investigate the proposed SSP system. Results indicate that the proposed SSP system could eliminate annually 1420 tonnes of emissions as well reduce the grid CO 2 emissions by 1204 tonnes through the green electricity supplied to the grid. Moreover, the cash flow and net present value analyses have shown good profitability with a payback period between 7.4 and 12 years.

New Benders decomposition and rolling horizon optimisation approaches to design isolated microgrids for Amazon region

Brazil is on the last mile of total electrification. However, the current challenge is in the Amazon region, where electrification has not been achieved through renewable energy. This paper presents a hybrid off-grid energy system for the Amazon region that considers the following technologies: battery system, diesel generator, micro-hydro, photovoltaic and wind turbine. We selected the states of Amazonas, Roraima and Tocantins, and we studied three scenarios. Benders decomposition and rolling horizon techniques are applied to find the optimal design and management strategy of a microgrid. We propose a novel approach to optimise energy storage for a whole year with hourly time step. A feasible design is proposed consisting of diesel generator, micro-hydro, photovoltaic, wind turbine, and battery system with diesel production as low as 0.7%. A 100% renewable microgrid is feasible for the Amazon region with an energy cost of 0.19 USD/kWh. The results are promising as they show competitive energy costs.

Risk‐averse optimal operation of an on‐grid photovoltaic/battery/diesel generator hybrid energy system using information gap decision theory

AbstractThis paper focuses on risk‐averse‐based optimal operation of a grid‐connected hybrid energy system (HES) composed of photovoltaic (PV), diesel generator, and battery storage system (BSS). For this goal, information gap decision theory (IGDT) is used to model load demand uncertainty. The aim of the optimal operation is to minimize cost of PV/diesel/BSS by optimal determination of the power purchased from the electricity grid. Since in the risk‐averse strategy, load demand has an undesirable impact on the objective function, the decision maker attempts to maximize the uncertainty radius in a way that any deviation of the uncertain parameter leads to an objective function value which is not worse than the critical value. Over the case studies (considering different radiations), simulation results indicate that in the risk‐neutral strategy, at high, medium, and low radiations, the operation cost is 28.88, 36.10, and 42.63$, respectively. In the risk‐averse strategy, when the radiation is high, by increase of the deviation factor from 0.1 to 0.25, the optimal uncertainty radius increases from 6.98% to 15.72% (increase of around 125%) and the operation cost increases from 31.768 to 36.101$. When the radiation is low, by increase of the deviation factor from 0.1 to 0.25, the uncertainty radius increases from 8.64% to 16.9% (increase of around 96%) and the operation cost increases from 46.895 to 53.291$.