Capacity Of Photovoltaic Systems Research Articles

Sensitivity analysis of distributed photovoltaic system capacity estimation based on artificial neural network

Residential solar photovoltaic (PV) system installations are expected to continue increasing due to their growing cost competitiveness and supportive government policies. However, excessive installations of unknown behind-the-meter solar panels present a challenge for accurate load prediction and reliable operations of power networks. To address such growing concerns of distribution network operators (DNOs), this research proposes a novel model for distributed PV system capacity estimations. Innovative extracted features from 24-hour substation net load curves were fed into a deep neural network to estimate the PV capacity linked to the substation feeder. A comprehensive study into the sensitivity of the model’s accuracy to specific temporal scales of data collection, number of households served by a substation, and proportion of PV-equipped properties was conducted. This study revealed that a model developed to be used exclusively in summer achieved a 18.1% decrease in estimation root mean squared error (RMSE) compared to an all-year model, whilst using only a third of the training data amount. Similarly, compared to an all-year model, RMSE decreased by 26.9% when only data from Mondays to Thursdays were used to train and test the model. Also, for the all-year model, the most accurate estimations occur when 20% to 80% of households have PV systems installed and estimation percentage error tend to remain constant at around 10% when more than 20% of households have PV systems installed. A machine learning-ready dataset of substations with known PV capacity and experiment results are both useful to inform DNOs on the potential of the proposed method in reducing grid operation costs.

Feasibility study of rooftop solar photovoltaic system for 33/11 kV primary substation at Al Suwairah

<span>This article presents an overview of the technical and financial feasibility analysis of integrating a photovoltaic (PV) source with the conventional power system to supply the auxiliary load at the Al Suwairah 33/11 kV primary substation (PSS) in Suhar, Sultanate of Oman. This study estimates the required electrical energy for the primary substation's auxiliary load. A method is implemented to utilize the available area in the primary substation for determining the solar photovoltaic system's capacity. PVSyst software is employed to determine the ideal system capacity. The proposed solar PV system's payback period and overall annual savings have been evaluated using a series of simulated analyses. The proposed PV can inject 172.5 MWh/year with an average performance ratio of 0.826. The economic evaluation by the photovoltaic system (PVSyst) considering the present auxiliary load at the Al Suwarah PSS has suggested a total payback period of 8.9 years which is quite feasible. The cost of power generated by the proposed system is 49.2% less than the cost of power supplied from the utility service provider.</span>

Hosting capacity improvement for solar systems based on model predictive controller of volt-watt-var smart inverter functions

ABSTRACT Photovoltaic (PV) system adoption is accelerating quickly, raising worries among electricity network service providers about how to accommodate more PV while keeping system operating indices within acceptable bounds. This idea, which is typically about Hosting Capacity (HC), has recently gotten more interest. Modern smart inverters provide control possibilities in Volt-Var and Volt-Watt based on system voltage level management. In this paper, the impact of various connection standards that encompass these tactics on the capacity of solar PV systems to store energy and their usability in the delivery of low-voltage systems is thoroughly examined. Modeling of smart inverters has been validated using MATLAB SIMULINK with various Volt-Var and Volt-Watt control functions. Volt-Watt-Var control has been designed based on Model Predictive Control (MPC) and comparing the results with a PID controller. The proposed MPC control has been applied on the IEEE-9 bus with combined controls. The impact of various connection requirements on photovoltaic Hosting Capacity (PVHC) is investigated to determine the best connection strategy(s) to handle the problem of voltage encroachment. In addition, the paper gives a deeper knowledge of HC enhancement using sophisticated inverter control features within a low-voltage distribution network of converters, besides it shows the effects of over-voltage and under-voltage on the system parameters.

Increasing Energy Self-Consumption in Residential Photovoltaic Systems with Heat Pumps in Poland

Currently, the use of air-source heat pumps (ASHP) in combination with a photovoltaic (PV) installation is a very promising option for a necessary and urgent energy transformation in European countries. It is extremely important to develop solutions that will help maximize the use of energy generated from renewable energy sources. Such issues include the problem of insufficient use of generated electricity in PV on-grid microinstallations in residential buildings. This paper’s aim is to analyse the results of a one-year-round operation of a PV array grid-connected hybrid installation with ASHP for domestic hot water preparation in a residential building in Cracow, Poland, in the context of increasing self-consumption of PV energy. Models of systems are built and simulated in the Transient System Simulation software in release 18.05.0001. Simulations were carried out for different scenarios involving different building electricity consumption profiles, PV system capacity and specified runtime management of ASHP. The novelty of this study lies in the evaluation of the impact of a certain range of conditions on the energy performance of the system and in particular on increasing self-consumption. The results showed that the use of ASHP, with specified runtime management, results in an increase in monthly self-consumption values from 7% to 18%, and annual values up to 13%. Moreover, determining the appropriate size of the used PV system depending on whether it is present ASHP in the installation is crucial to increasing the value of this parameter. Overall, this study provides valuable insights into the potential benefits of PV panels and ASHP operating together, particularly on self-consumption values.

Development of a Solar-Tracking System for Horizontal Single-Axis PV Arrays Using Spatial Projection Analysis

Uniaxial trackers are widely employed as the frame for solar photovoltaic (PV) panel installation. However, when used in sloping terrain scenarios such as mountain and hill regions, it is essential to apply a solar-tracking strategy with the sloping factors considered, to eliminate the shading effects between arrays and reduce the electricity production loss due to terrain changes. Based on a uniaxial tracker on the sloping terrain of a PV farm located in Ningxia, this study established a uniaxial solar-tracking strategy for sloping terrain by integrating a spatial projection model with a dynamic shadow assessment method. In the proposed strategy, the optimal tilt angle of the PV array and related desirable adjustment are identified taking into consideration major parameters such as the shadow area ratio S and the average solar irradiance intensity G. A tool underpinned by Matlab Simulink has also been developed to realize the proposed solar-tracking strategy. With the input of a simulated ramp signal β and the dynamically changed time parameters, the tracking angle of PV arrays over the simulated duration is accurately predicted, followed by a series of experimental validations conducted on the winter solstice and a typical sunny day (15 September). Moreover, the study also explored the terrain impacts on solar tracking by comparing the sloping terrain and flat terrain applications. The analytic and experimental results indicate that (a) the maximum value of the G(β) function could serve as the input to identify the optimal tracking angle; (b) the application of the flat terrain tracking (FTT) strategy in sloping terrain would result in a reduction of average solar irradiance intensity harvested by the PV arrays with varying degrees; (c) in the context of an east–west −7° sloping terrain, compared with the FTT strategy, the sloping terrain tracking (STT) strategy enabled anti-shading tracking, and then increased the daily PV electricity yield by 0.094 kWh/kWp, which is around 1.48% of the daily energy production; (d) given a measurement with annual scale, the STT strategy could cause a 1.26% increase in the energy harvesting with a flat uniaxial PV array on a −7° slope terrain, achieving an annual increase of 25.16 kWh/kWp. The experimental comparative analysis validated the precision of the proposed solar-tracking model, which has far-reaching significance for achieving automatic solar-tracking of PV modules, as well as improving the capacity and efficiency of PV systems.

Utilization and Verification of Inverse Distance Weighting (IDW) Interpolation Technology for Predicting Solar Radiation of Photovoltaic System

Purpose: Weather conditions around solar photovoltaic (PV) systems have a direct effect on the amount of generated power. Therefore, highly correlated meteorological environmental variables are used to accurately predict the power generation capacity of PV systems. However, it is difficult to install observation equipment due to high installation costs and maintenance. Therefore, public data from the Korea Meteorological Administration are often used. However, uncertainty may arise due to the large distance between the stations of the Korea Meteorological Administration. Therefore, in this study, inverse distance weighting (IDW) was used to predict the solar radiation of an arbitrary area to improve the uncertainty caused by the large distance between the meteorological stations. Method: In this study, IDW was used as a spatial statistical technique to predict the monthly average of daily accumulation solar radiation in South Korea. Moreover, four cases of the automated synoptic observing system (ASOS) were used as study cases to evaluate the prediction technology. The actual solar radiation observed and the predicted solar radiation was compared and analyzed in each study case, and the accuracy was evaluated as an indicator of the mean absolute percentage error (MAPE). Additionally, the MAPE was compared with the prediction results of the multiple regression model. Result: Although the results differ for each case, the average MAPE was approximately 11.06% using the inverse distance weighting interpolation method, and the predicted value by the multiple regression method yielded an average MAPE of approximately 16.12%.

3D-PV-Locator: Large-scale detection of rooftop-mounted photovoltaic systems in 3D

While photovoltaic (PV) systems are being installed at an unprecedented rate, it is challenging to keep track of them due to their decentralized character and large number. In this paper, we present the 3D-PV-Locator for large-scale detection of roof-mounted PV systems in three dimensions (3D). The 3D-PV-Locator combines information extracted from aerial images and 3D building data by means of deep neural networks for image classification and segmentation, as well as 3D spatial data processing techniques. It thereby extends existing approaches for the automated detection of PV systems from aerial images by also providing their azimuth and tilt angles. We evaluate the 3D-PV-Locator using a large dataset gathered from the official German PV registry in a real-world study with more than one million buildings. In terms of azimuth and tilt angles, our evaluation shows that the 3D-PV-Locator and the official registry coincide for about two thirds of the observations and are within neighboring classes for 84 and 99 percent of the observations, respectively. In terms of detected PV system capacity, we show that the 3D-PV-Locator clearly outperforms existing approaches. It performs particularly well for the groups of small and medium-sized PV systems (3.6–33.1 percent error reduction) and PV systems tilted beyond 40° (25.6–38.1 percent error reduction). The 3D PV system data generated by the 3D-PV-Locator can inform several practical applications, such as improved forecasting of solar generation, the optimized planning and operation of distribution networks, improved integration of electric vehicles, and others. All datasets and pre-trained models associated with this paper are available online.

Dynamic participation in local energy communities with peer-to-peer trading.

Background: Energy communities and local electricity markets (e.g., as peer-to-peer trading) are on the rise due to increasingly decentralized electricity generation and favorable adjustment of the legal framework in many European countries. Methods: This work applies a bi-level optimization model for dynamic participation in peer-to-peer electricity trading to determine the optimal parameters of new participants who want to join an energy community, based on the preferences of the members of the original community (e.g., environmental, economic, or mixed preference). The upper-level problem chooses optimal parameters by minimizing an objective function that includes the prosumers' cost-saving and emission-saving preferences, while the lower level problem maximizes community welfare by optimally allocating locally generated photovoltaic (PV) electricity between members according to their willingness-to-pay. The bi-level problem is solved by transforming the lower level problem by its corresponding Karush-Kuhn-Tucker (KKT) conditions. Results:The results demonstrate that environment-oriented prosumers opt for a new prosumer with high PV capacities installed and low electricity demand, whereas profit-oriented prosumers prefer a new member with high demand but no PV system capacity, presenting a new source of income. Sensitivity analyses indicate that new prosumers' willingness-to-pay has an important influence when the community must decide between two new members. Conclusions:The added value of this work is that the proposed method can be seen as a basis for a selection process between a large number of potential new community members. Most important future work will include optimization of energy communities over the horizon several years.

PV Pre-cooling system for the Engineers Association Branch in Latakia

This study presents pre-cooling technology using a solar photovoltaic energy system where the increasing in air-conditioning demand during summer results in a rise in the amount of electrical energy consumed from the electric network, as well as an increase in electricity bills. Air conditioners are operated in governmental facilities during official working hours, at the time of the peak demand for electricity, when electric costs are the highest. In order to shift the cooling demand out of the peak period into a lower electric cost period, reducing the energy consumption of the building and the value of the electricity bills, this study was conducted on the technology of pre-cooling using solar photovoltaic energy system. The Engineers Association Branch in Latakia was conducted as a case study. The results showed that applying the Photovoltaic (PV) pre-cooling system led to a significant decrease in the cooling demand during thek hours, and reduces the daily consumption of the electric power from the electric system, as the demand was decreased from 85 kWh to 21,250 kWh. Besides, the value of the electricity bills was decreased by 83%. Pre-cooling lowered the PV system capacity that was needed to operate the building's air conditioning equipment by 50%. A reduction of 42.5 kg of CO2 emissions per day could be achieved using PV-pre-cooling system.

Sizing Algorithm for a Photovoltaic System along an Urban Railway Network towards Net Zero Emission

A reliable transportation system is essential for the development of a community. Especially in urban transportation, rail transportation is a faster, more comfortable way to travel for the commuters. These benefits can be valued further when the rail transportation system is with zero emissions. Electric trains can be considered a zero-emission transportation method. However, a rail transportation system operates with net-zero emissions when electricity is generated from zero-emission-based sources. Photovoltaic systems have already been integrated into railway stations and spare land owned by railways to achieve net-zero emissions. Furthermore, medium-voltage DC network and microgrid concepts have been proposed to incorporate more renewable energy sources into railway electrification systems. However, the energy generated from those systems is not enough to realise net-zero emissions, as the power requirements of an urban railway electrification system are high. Accordingly, this article investigates the possibility of implementing a photovoltaic system along the railway tracks to meet the energy demands of an urban railway electrification system so that net-zero emissions can be achieved. Other significant advantages of the proposed photovoltaic system are lower feeder losses due to distributed photovoltaic systems integrated into the railway electrification system, lower conversion losses due to the direct integration of the photovoltaic system into the railway electrification system, and the nonrequirement of additional space to install the photovoltaic system. In this paper, a photovoltaic system capacity sizing algorithm is proposed and presented by considering a railway electrification system, the daily schedule of trains, and historical photovoltaic weather data. This proposed photovoltaic system capacity sizing algorithm was evaluated considering a section of the urban railway network of Sri Lanka and a three-year, 2017-2020, photovoltaic weather data. The results indicated that the potential for photovoltaic generation by installing photovoltaic systems along a railway track is much higher than the requirement, and it is possible to meet the required train scheduling options with proper sizing. Furthermore, in the three-year analysis, it is possible to achieve 90% of the energy required for the railway electrification system with effective train scheduling methods.

Designing a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysis and Adjustment Based on RSM and ANFIS Approaches

One of the most favorable renewable energy sources, solar photovoltaic (PV) can meet the electricity demand considerably. Sunlight is converted into electricity by the solar PV systems using cells containing semiconductor materials. A PV system is designed to meet the energy needs of King Abdulaziz University Hospital. A new method has been introduced to find optimal working capacity, and determine the self-consumption and sufficiency rates of the PV system. Response surface methodology (RSM) is used for determining the optimal working conditions of PV panels. Similarly, an adaptive neural network based fuzzy inference system (ANFIS) was employed to analyze the performance of solar PV panels. The outcomes of methods were compared to the actual outcomes available for testing the performance of models. Hence, for a 40 MW target PV system capacity, the RSM determined that approximately 33.96 MW electricity can be produced, when the radiation rate is 896.3 W/m2, the module surface temperature is 41.4 °C, the outdoor temperature is 36.2 °C, the wind direction and speed are 305.6 and 6.7 m/s, respectively. The ANFIS model (with nine rules) gave the highest performance with lowest residual for the same design parameters. Hence, it was determined that the hourly electrical energy requirement of the hospital can be met by the PV system during the year.

Optimal Configuration with Capacity Analysis of PV-Plus-BESS for Behind-the-Meter Application

As the cost of photovoltaic (PV) systems and battery energy storage systems (BESS) decreases, PV-plus-BESS applied to behind-the-meter (BTM) market has grown rapidly in recent years. With user time of use rates (TOU) for charging and discharging schedule, it can effectively reduce the electricity expense of users. This research uses the contract capacity of an actual industrial user of 7.5 MW as a research case, and simulates a PV/BESS techno-economic scheme through the HOMER Grid software. Under the condition that the electricity demand is met and the PV power generation is fully used, the aim is to find the most economical PV/BESS capacity allocation and optimal contract capacity scheme. According to the load demand and the electricity price, the analysis shows that the PV system capacity is 8.25 MWp, the BESS capacity is 1.25 MW/3.195 MWh, and the contract capacity can be reduced to 6 MW. The benefits for the economical solution are compared as follows: 20-year project benefit, levelized cost of energy (LCOE), the net present cost (NPC), the internal rate of return (IRR), the return on investment (ROI), discounted payback, total electricity savings, renewable fraction (RF), and the excess electricity fraction. Finally, the sensitivity analysis of the global horizontal irradiation, electricity price, key component cost, and real interest rate will be carried out with the most economical solution by analyzing the impacts and evaluating the economic evaluation indicators. The analysis method of this research can be applied to other utility users to program the economic benefit evaluation of PV/BESS, especially an example for Taiwan’s electricity prices at low levels in the world.

Energy balance and performance assessment of PV systems installed at a positive-energy building (PEB) solar energy research centre

The energy balance and performance of all Photovoltaic (PV) systems installed at Fotovoltaica/UFSC solar energy laboratory (www.fotovoltaica.ufsc.br) in Florianópolis, Brazil (27° S; 48° W) were demonstrated over time, from Aug/2017 to Feb/2020. The laboratory was designed as a zero-energy building (ZEB) with PV systems installed on rooftops and façades, not maximising annual generation, but to achieve a compromise between aesthetic appeal and the energy output. Further PV systems were installed on the same site in the shapes of a carport, an electric bus (eBus) shelter and charging station, and different ground-mounted PV systems fixed at latitude tilt and single-axis tracking. Monthly analyses were carried out during the period, such as the solar irradiation availability on site, changes in the number of building occupants, the increase of installed capacity of PV systems, and energy generation and consumption. With 111 kWp, the total PV generation in the period could supply 148% of building energy needs and 97% of the Fotovoltaica/UFSC Laboratory (building plus eBus). However, there were some downtime events in certain PV systems due to R&D activities, which affected total energy production. If systems had operated at their optimal performance all the time, the laboratory could have generated 38% more energy, which means 134% of building plus eBus consumption. Therefore, the Fotovoltaica/UFSC Laboratory can be considered not only a ZEB, but a positive-energy building (PEB). The issues discussed in this paper apply not only to the particular case-study presented; they demonstrate the potential of BIPV in enabling energy positive buildings.

Power system stability improvement using Battery Energy Storage System (BESS) in isolated grid

Rural areas and islands distant from main power grids mostly rely on diesel fuel for electricity generations, which assembles an isolated network. In eastern Indonesia, these isolated grids began to hybridize with solar photovoltaic (PV) systems to reduce the generation costs. However, the penetration of solar PV systems has risen one crucial problem related to the power system stability due to its output intermittency and variability. The Battery Energy Storage System (BESS) can be utilized as a frequency regulator so that the system stability can be maintained well. Besides, BESS can also function as an energy arbitrage so that the target of generation costs saving can also be achieved. This study analyzes the effectiveness of BESS utilization to reduce the stability issues of an isolated grid consisting of diesel generators and PV systems in eastern Indonesia by using PowerFactory software. The scenario of the daily operating pattern of each component is simulated as well by considering the optimal solar PV system and BESS capacity.

Generation Capacity Expansion Planning Considering Hourly Dynamics of Renewable Resources

As more generation capacity using renewable sources is accommodated in the power system, methods to represent the uncertainty of renewable sources become more important, and stochastic models with different methods for uncertainty representation are introduced. This paper investigates the impacts of hourly variability representation of random variables on a stochastic generation capacity expansion planning model. In order to represent the hourly variability as well as uncertainty of the random parameters such as wind power availability, solar irradiance, and load, AutoRegressive-To-Anything (ARTA) stochastic process is applied. By using autocorrelations and marginal distributions of the random parameters, a stochastic process with hourly intervals is generated, where generated random sample paths are used for scenarios. A mathematical formulation using stochastic programming is presented, and a modified IEEE 300-bus system with transmission line constraints is employed to the mathematical model as a test system. Optimal generation capacity solutions obtained using GAMS/CPLEX are compared to the ones from the model only capturing the uncertainty and seasonal variability of the random parameters. The comparison results indicate that the economic value of solar photovoltaic (PV) generation may be overestimated in the case where the hourly variability is not reflected; thus, ignoring the hourly variability may lead to higher building costs and higher capacity of solar PV systems.

Evaluation Method for Hosting Capacity of PV System in Distribution System with Micro Hydropower Generator

According to the Korean government’s policy to demonstrate and expand renewable energy sources, distributed generators such as photovoltaic (PV) and wind power (WP) systems are energetically installed and operated in distribution systems. However, there are many issues related to power quality problems including an over-voltage phenomenon when the PV systems were interconnected and operated. In order to overcome these problems the electric power company has installed the step voltage regulator (SVR) in primary feeders interconnected with PV systems, and also has established technical guidelines for distributed generators to stabilize the customer voltages. However, despite such voltage regulators and technical guidelines, it is difficult to maintain the customer voltages within the allowable voltage limit. In order to actively host a large-capacity PV system, this paper proposes an optimal voltage control algorithm of micro hydropower generator (MHG) to keep customer voltages within the allowable voltage limit and presents an evaluation algorithm for hosting capacity of PV system based on a sensitivity analysis method. Furthermore, this paper performs PSCAD/EMTDC modeling based on the proposed algorithm and analyzes characteristics of customer voltages based on various scenarios related to the location and capacity of the PV system and MHG. From the simulation results, it is confirmed that the proposed methods can contribute to the stabilization of the customer voltages and improve the hosting capacity of the PV system in a distribution system.

Photovoltaic Equalizer Based on Single-Input Multi-Output Push-Pull Converter

Component mismatch often happens in the module-series photovoltaic system(including centralized, string, multi-strings PV system) due to partial shadowing, which causes a large loss of power generation. Photovoltaic equalizer can process the differential power under the condition of mismatching through parallel power electronic converter without changing the existing photovoltaic system architecture, so that all the modules can work near their maximum power points, which can greatly improve the power generation of the system under the condition of mismatching. This paper proposes a photovoltaic equalizer based on single-input multi-output push-pull converter. The topology has the advantages of simple structure and less switching devices. Firstly, the paper introduces the partial shadowing problem of photovoltaic modules and the principle of photovoltaic equalizer. Then, the topological structure and working principle of the proposed photovoltaic equalizer system are analyzed in detail. Finally, the simulation and verification of the designed photovoltaic equalizer are carried out. The simulated results show that the proposed equalizer can greatly improve the generation capacity of photovoltaic system under mismatching conditions, and the maximum increment can be up to 41%.

Analysis and Sizing of Mini-Grid Hybrid Renewable Energy System for Islands

This paper aims to investigate the techno-economic feasibility analysis of stand-alone diesel system, stand-alone PV/storage system, PV/diesel hybrid system, PV/diesel/storage hybrid system for the Pratas island in Taiwan. The power supply of outlying islands in Taiwan still use fossil fuel generators. The fuel cost is higher than that of on shore of Taiwan, and it has a great impact on the environment. This problem can be mitigated by hybrid energy systems. Through the investigation to know the existing generator set and Photovoltaic (PV) operating status, load consumption, etc., the study collects the required data for statistical meteorological analysis and economic analysis, and uses Hybrid Optimization Models for Energy Resources (HOMER) to simulate techno-economics of the stated hybrid energy systems. The analysis contains the capital cost, net present cost (NPC), cost of energy (COE) and fuel saving in different capacities for each power supply system with different constraints. From the simulation results, the lowest COE is 0.3569 $/kWh that can be found at the PV/diesel hybrid system configuration scheme with a total PV system capacity of 200 kWp, the renewable fraction (RF) is 15.3% and the excess electricity fraction is 2.6%, which is lower than the generally acceptable 5%. Although the COE of PV/diesel/storage hybrid is higher than that of stand-alone diesel system, the annual total CO2 emissions is reduced by 31.63%, which is of great benefit to environmental protection.

Simulation Analysis of Harmonic Characteristics of Photovoltaic Power Generation System Based on MATLAB

Abstract Photovoltaic (PV) power generation system, as a kind of clean energy power, is increasingly applied in the power grid. However, due to the uncertainty and fluctuation of PV system, it has negative influence on the power quality, such as power factor deterioration, voltage waveform distortion and electromagnetic interference. In this paper, by doing the equivalent impedance transformation of the high voltage transmission and distribution system with photovoltaic power supply, the influence of photovoltaic power generation on amplification of harmonic voltage and harmonic current of high voltage transmission side is analyzed. The capacity of PV system varies with the range of harmonics. Finally, the optimal operation mode of photovoltaic power generation is put forward innovatively based on harmonic characteristics under different operating conditions and capacity. It aims to guide the harmonic suppression of photovoltaic power generation system.

Prefeasibility techno-economic assessment of a hybrid power plant with photovoltaic, fuel cell and Compressed Air Energy Storage (CAES)

This paper presents a hybrid power generation system comprising of Photovoltaic (PV) panels, Molten Carbonate Fuel Cell (MCFC), Gas Turbine (GT), Thermal Energy Storage (TES), Battery (Bat) and a Compressed Air Energy Storage (CAES) system. The CAES pressure was considered to be regulated using a water reservoir system located at a suitable height place. The described system was designed to supply the electricity needs of 500 households with peak electricity demand of 500 kW. A set up MCFC/GT with power generation rate of 500 kW was considered in the calculations, and the PV system capacity was considered to be changed from 100 kW to 600 kW. The optimal configuration and operational conditions of the system were conducted based on the Levelized Cost of Electricity (LCOE) definition as well as the total annual emission that is occurred by the auxiliary fossil fuel boiler and MCFC systems. The results showed that the overall system efficiency would be increased by about 25%, when the CAES is used and the compressor is switched off. Also, the optimal operational pressure of MCFC was found to be 6 bar for 2000 number of PVs, 1500 kWh of battery storage and CAES capacity of 685 m3.