Investigating Load Regulation Characteristics of a Wind-PV-Coal Storage Multi-Power Generation System

There is a growing need to explore the potential of coal-fired power plants(CFPPs)to enhance the utilization rate of wind power(wind)and photovoltaic power(PV)in the green energy field.This study developed a load regulation model for a multi-power generation system comprising wind,PV,and coal energy storage using realworld data.The power supply process was divided into eight fundamental load regulation scenarios,elucidating the influence of each scenario on load regulation.Within the framework of the multi-power generation system with the wind(50 MW)and PV(50 MW)alongside a CFPP(330 MW),a lithium-iron phosphate energy storage system(LIPBESS)was integrated to improve the system’s load regulation flexibility.The energy storage operation strategy was formulated based on the charging and discharging priority of the LIPBESS for each basic scenario and the charging and discharging load calculation method of LIPBESS auxiliary regulation.Through optimization using the particle swarm algorithm,the optimal capacity of LIPBESS was determined to be within the 5.24-4.88 MWh range.From an economic perspective,the LIPBESS operating with CFPP as the regulating power source was 49.1% lower in capacity compared to the renewable energy-based storage mode.

Short-term prediction of photovoltaic power generation based on LMD-EE-ESN with error correction

Considering the instability of the output power of photovoltaic(PV)generation system,to improve the power regulation ability of PV power during grid-connected operation,based on the quantitative analysis of meteorological conditions,a short-term prediction method of PV power based on LMD-EE-ESN with iterative error correction was proposed.Firstly,through the fuzzy clustering processing of meteorological conditions,taking the power curves of PV power generation in sunny,rainy or snowy,cloudy,and changeable weather as the reference,the local mean decomposition(LMD)was carried out respectively,and their energy entropy(EE)was taken as the meteorological characteristics.Then,the historical generation power series was decomposed by LMD algorithm,and the hierarchical prediction of the power curve was realized by echo state network(ESN)prediction algorithm combined with meteorological characteristics.Finally,the iterative error theory was applied to the correction of power prediction results.The analysis of the historical data in the PV power generation system shows that this method avoids the influence of meteorological conditions in the short-term prediction of PV output power,and improves the accuracy of power prediction on the condition of hierarchical prediction and iterative error correction.

A Techno-Economical Characterization of Solar PV Power Generation in Rwanda:The Role of Subsidies and Incentives

Standalone Solar PV systems have been vital in the improvement of access to energy in many countries.However,given the large cost of solar PV plants’components,in developing countries,there is a dear need for such components to be subsidised and incentivised for the consumers to afford the produced energy.Moreover,there is a need for optimal sizing of the solar PV plants taking into account the solar information,energy requirement for various activities,and economic conditions in the off-grid regions in Rwanda.This study aims to develop optimally sized solar PV plants suited to rural communities in Rwanda.Likewise,it aims at characterizing the impacts of subsidies and incentives on the profitability and affordability of solar PV plants’energy in Rwanda.In the study,we have developed a model on basis of which the plant power(peak power)and costs of energy can be predicted given the load requirements using PVSyst.The model was validated using data corrected at eight different sites.Our generalized predictive model’s results matched the results obtained using field measurement data as inputs.The models have been able to replicate with a by degree of accuracy the peak powers and the plants’costs for different loads and were used to evaluate the economic viability of solar PV plants in Rwanda.It was found that with incentives and subsidies of 20%,the solar PV systems’costs,the Levelised Cost of Energy would drop from a maximum of 0.098 Euro to a minimum of 0.072 Euro,the payback period was reduced from a maximum of 7.5 years to a minimum of 6.0 years while the return on investments was seen to vary between 425.72 and 615.32 per cent over the plants’lifetime of 25 years.Overall our findings underscore the importance of government subsidies and incentives for solar PV energy generation projects to be significantly profitable.

High Efficiency PCS with Scan-Type MPPT Control for a Grid-Connected PV Power Generation System

For a standalone PV （photovoltaic） power generation system, the author previously proposed a new MPPT （maximum power point tracking） control method in which the I-V characteristics are scanned with a detection interval control that operates at specified intervals and monitors the maximum power point. The author has obtained satisfactory results using this new MPPT control method. This paper investigates the application of the new MPPT control method for a PCS （power conditioning system） in a grid-connected type PV power generation system. The experimental results clearly demonstrate that the developed PCS offers outstanding effectiveness in tracking the maximum power point in partially shaded environments.

Study on Improvement of MPPT Efficiency in PV Generation System with Partial Shadow

The maximum power point of PV （photovoltaic） generation moves depending on weather conditions and load. Therefore, it is significant to make sure that the panels can work at the maximum power point under MPPT （maximum power point tracking） control. However, it has the problems of low efficiency and unstable operation when panels are covered by the partial shadow. The result is that the output power may be substantially decreased. To overcome this issue, the authors propose a new plug-in operation point correction system. This system is put between PV panels and PCS （power conditioning system） in the existing PV generation system. In this paper, the experimental results describe that the output electric energy increases approximately 1.4 times as compared with the conventional system when the proposed correction system is inserted.

Calculation Method and Analysis for the Annual Power Generation of PV Faades in China

The application of PV facades emerges greatly in recent years and however its calculation methods and analysis remains insufficient under the weather conditions of China. In such demand, this paper investigates PV facade in terms of PV electricity generation in different arrangements and weather conditions of four major cities in China. The calculation models for PV facade are developed and validated by comparing the results with the measured data from the field experiments. A parametric study is carried out to provide a reference for the optimal design of the PV facades. The results show that with various cities, building orientations, building forms, materials and arrangements of PV modules, there is a distinct difference in the electrical output energy of PV facades. Weather conditions nlav a very important role in terms of PV generation nerformance of PV facades.

Availability, Performance and Reliability Evaluation for PV Distributed Generation

Nowadays, renewable energy resources play an important role in replacing conventional energy resources such as fossil fuel by integrating solar, wind and geothermal energy. Photovoltaic energy is one?of?the very promising renewable energy resources which grew rapidly in the past few years, it can be used to produce electric energy through photovoltaic process. The primary objective of the research proposed in this paper is to facilitate the increasing penetration levels of PV systems in the electric distribution networks. In this work, the PV module electrical model is presented based on the mathematical equations and was implemented on MATLAB to simulate the non-linear characteristics I-V and P-V curves with variable input parameters which are irradiance and temperature based on Riyadh region. In addition, the reliability evaluation of distribution networks, including distributed generators of solar photovoltaic (PV) with varying output power capacity is presented also. The Monte Carlo simulation algorithm is applied to test the distribution network which is RBTS Bus 2 and the same has been conducted on the original case of distribution network substation 7029 which is located at KSA Riyadh. The two distribution networks have been modified to include the PV’s distributed generators. The distributed generators contribute to supply a part of the load during normal mode and supply the entire load during component failure or failure of grid operation supply. The PV stochastic models have been used to simulate the randomness of these resources. Moreover, the study shows that the implementation and integration of renewable resources as distributed generations have improved the reliability of the distribution networks.

Impact of PV Distributed Generation on Loop Distribution Network

The rapid spreading of the Photovoltaic (PV) Systems as Distributed Generation (DG) in medium and low voltage networks created many effects and changes on the existing power system networks. In this work, two methods have been used and applied to determine the optimal allocation and sizing of the PV to be installed as DGs (ranging from 250 kW up to 3 MW). The first one is to determine the location according to the maximal power losses reduction over the feeder. The second one is by using the Harmony Search Algorithm which is claimed to be a powerful technique for optimal allocation of PV systems. The results of the two techniques were compared and found to be nearly closed. Furthermore, investigation on the effects on the feeder in terms of voltage levels, power factor readings, and short circuit current levels has been done. All calculations and simulations are conducted by using the MATLAB Simulation Program. Some field calculations and observations have been expended in order to substantiate the research findings and validation.

Solar PV Energy Generation Map of Karnataka, India

A massive plan has been drawn by the Karnataka state of India to initiate several solar power plants at different locations. In view of this, it is of great help to have reliable estimation on solar PV energy generation. Four solar PV power plants in Karnataka state are fully operational installed by Karnataka Power Corporation Limited (KPCL). They are located at Kolar, Belgaum and Raichur with 3 MW capacity each and at Mandya with 5 MW capacity. In the present study, using ground mounted weather station data solar power generation has been estimated and compared with actual generation for two consecutive years of 2012 and 2013 for one location initially, namely 3 MW Kolar Solar PV Plant. The procedure is repeated for rest of the plants. The simulated results have been corrected with ground mounted weather data. After such corrections, the simulated results have been compared with the actual energy generation of the four plants. Results showed a close match with a small deviation of about 5%. The model then applied throughout the state for every 0.25 degree station intervals in a grid manner. The annual energy generation obtained for the state varies from 1.53 to 1.73 MUs/MW. Central and south eastern part of the state are found to yield significantly higher solar power generation as compared to the northern part and south western part of Karnataka. Interestingly, north western part of Kodagu district has shown the least potential of 1.53 MUs/MW as compared to other parts. This can be attributed mainly due to low irradiation and high temperature condition at this location. The energy generated map from our study will be useful and helpful for both solar developers and decision makers of Karnataka state.

MPPT Control System for PV Generation System with Mismatched Modules

Nowadays, in a household PV （photovoltaic） generation system, it is generally connecting PV modules in series and then output to the power-conditioner. However, when PV modules are mismatched, it will lead to a wrong MPPT （maximum power point tracking） to all modules and a power decreasing of the whole system. Aiming at this problem, this paper presents the idea which improves the MPPT without changing the conventional power-conditioner, by adding a Buck type DC-DC （direct current） converter behind each module. Simulations of PSIM （power simulation） and experiments are taken to prove this theory. The result shows that, by this idea, the generated power of the conventional PV generation system can be greatly increased under the condition of mismatch.

Efficiency Improvement of PV Generation System by Using Improved P ＆ O Method of MPPT

The conventional P ＆ O （perturb-and-observe） method, which is the most widely used as MPPT （maximum power point tracking） control, has the problem of low efficiency and unstable operation when solar radiation changes drastically. Aiming at this problem, this paper improves the conventional P ＆ O method to reduce the bad effect of solar radiation by shortening the sampling interval of PV module＇s output power while keeping the operating period unchanged. Experiments are conducted to study efficiency gains of improved method when solar radiation changes drastically. The result shows that, by this method, the efficiency of MPPT control can be increased 17% in average when PV module simulator is used and 20% at maximum when actual PV module is used, compared with the conventional P ＆ O method.

Hot-Spot Detection System with Correction of Operating Point for PV Generation System

Currently, the production and the number of installations of PV （photovoltaic） modules have been increasing rapidly because of a feed-in tariff in Japan. Accordingly, the number of failures has also increased. Many failures are a result of the Hot-Spot phenomenon in which defective cell becomes hot when shadow occurs on the cell, On the other hand, if shadow occurs on normal cell, there are cases that P＆O method that is MPPT （maximum power point tracking） control method incorporated in conventional PV system cannot track maximum power point and generated power decreases. The correspondence is required rapidly if these trouble occur. However, conventional PV system monitors generated power, correspondence is impossible by monitoring generated power. Previously, the authors developed real time Hot-Spot detection system that incorporates into PCS （power conditioning system）. Thus, the authors developed plug-in type Hot-Spot monitoring system that includes ＂PV peak shift method＂ and confirmed effectiveness of the system in this time. ＂PV peak shift method＂ loads ＂Scan method＂ that is MPPT control method and measures I-V （current-voltage） characteristic by changing voltage of module from open to short by ＂Scan method＂ on a regular basis. The developed Hot-Spot monitoring system uses slope of I-V characteristic of PV module. Inserting developed system into already installed PV system, Hot-Spot can be easily monitored in real time and PV system can be operated at maximum power point.

The Hidden-Layers Topology Analysis of Deep Learning Models in Survey for Forecasting and Generation of the Wind Power and Photovoltaic Energy

As wind and photovoltaic energy become more prevalent,the optimization of power systems is becoming increasingly crucial.The current state of research in renewable generation and power forecasting technology,such as wind and photovoltaic power(PV),is described in this paper,with a focus on the ensemble sequential LSTMs approach with optimized hidden-layers topology for short-term multivariable wind power forecasting.The methods for forecasting wind power and PV production.The physical model,statistical learningmethod,andmachine learning approaches based on historical data are all evaluated for the forecasting of wind power and PV production.Moreover,the experiments demonstrated that cloud map identification has a significant impact on PV generation.With a focus on the impact of photovoltaic and wind power generation systems on power grid operation and its causes,this paper summarizes the classification of wind power and PV generation systems,as well as the benefits and drawbacks of PV systems and wind power forecasting methods based on various typologies and analysis methods.

Research on Multi-Scale Modeling of Grid-Connected Distributed Photovoltaic Power Generation

The complexity of distribution network model mainly depends on the model scale of grid-connected distributed photovoltaic (PV) power generation. Therefore, the simulation performance of multi-scale PV model is the key factor of the simulation accuracy in the specific operating scenarios of distribution network. In this paper, a multi-scale model of grid connected PV distributed generation system is proposed based on the mathematical model of grid-connected distributed PV power generation. It is analyzed that differences of simulation performance, such as adaptability of simulation step size, accuracy of output and the effect on voltage profile of distribution network, between PV models with different scales in IEEE 33 node example. Simulation results indicate that the multi-scale model is effective in improving the accuracy and efficiency of simulation under different operating conditions of distribution network.

PV Power Short-Term Forecasting Model Based on the Data Gathered from Monitoring Network

The degree of accuracy in predicting the photovoltaic power generation plays an important role in appropriate allocations and economic operations of the power plants based on the generating capacity data gathered from the geographically separated photovoltaic plants through network. In this paper, a forecasting model is designed with an optimization algorithm which is developed with the combination of PSO （Particle Swarm Optimization） and BP （Back Propagation） neural network. The proposed model is further validated and the experiment results show that the predication model assures the prediction accuracy regardless the day type transitions and other relevant factors, in the proposed model, the prediction error rate is worth less than 20% in all different climatic conditions and most of the prediction error accuracy is less than 10% in sunny day, and whose precision satisfies the management requirements of the power grid companies, reflecting the significance of the proposed model in engineering applications.

Comparison between the Energy Required for Production of PV Module and the Output Energy Througout the Product Life Time

Electrical energy consumption is growing and is necessary to improve the technologies related to energy production. We have carried out a pilot study about environmental impacts during the manufacturing process of PV （photovoltaic） modules and compared between the energy requirement for the production of PV cells and modules and generation throughout the life time of the finished good that is PV module. It was taken into account the generation of environmental aspects and impacts in the manufacture of monocrystalline silicon PV modules （consisting of three components： silicon cell, fiat tempered glass and aluminum frame）, and an analysis of a grid-connected PV system using an energetic alternative in residences was considered. Results show that, this kind of renewable energy is really clean and can be considered as a way to change the energy technology.

Distributed Solar PV System for Industrial Application

The paper presents the design and field test of a distributed solar PV system for industrial application （DGPVi）. DGPVi utilizes HyPV （hybrid PV） system which generates solar power for self-consumption in lighting and air conditioning in a production line of a factory when solar energy is available. It does not feed the excess PV power to the grid. HyPV will be switched to grid power supply when solar energy is not available. A 3 kWp DGPVi is installed in a factory for field demonstration. The test results show that the solar PV power generated can be utilized immediately. The solar energy generation efficiency （kWh/day per kWp PV installation） of DGPVi is close to that of grid-tied PV system without self-consumption and battery storage. The yearly return on investment of DGPVi is 2.0% at the present installation cost or 3.3% at further cost-down cost. The payback time will be 14.3 years at the present installation cost or 12.1 years at cost-down cost. The present study verifies the economic feasibility of DGPVi.

Model predictive control of grid-connected PV power generation system considering optimal MPPT control of PV modules

Because of system constraints caused by the external environment and grid faults,the conventional maximum power point tracking(MPPT)and inverter control methods of a PV power generation system cannot achieve optimal power output.They can also lead to misjudgments and poor dynamic performance.To address these issues,this paper proposes a new MPPT method of PV modules based on model predictive control(MPC)and a finite control set model predictive current control(FCS-MPCC)of an inverter.Using the identification model of PV arrays,the module-based MPC controller is designed,and maximum output power is achieved by coordinating the optimal combination of spectral wavelength and module temperature.An FCS-MPCC algorithm is then designed to predict the inverter current under different voltage vectors,the optimal voltage vector is selected according to the optimal value function,and the corresponding optimal switching state is applied to power semiconductor devices of the inverter.The MPPT performance of the MPC controller and the responses of the inverter under different constraints are verified,and the steady-state and dynamic control effects of the inverter using FCS-MPCC are compared with the traditional feedforward decoupling PI control in Matlab/Simulink.The results show that MPC has better tracking performance under constraints,and the system has faster and more accurate dynamic response and flexibility than conventional PI control.

Intelligent windows for electricity generation: A technologies review

Buildings are responsible for over 40% of total primary energy consumption in the US and EU and therefore improving building energy efficiency has significant potential for obtaining net-zero energy buildings reducing energy consumption. The concurrent demands of environmental comfort and the need to improve energy efficiency for both new and existing buildings have motivated research into finding solutions for the regulation of incoming solar radiation, as well as ensuring occupant thermal and visual comfort whilst generating energy onsite. Windows as building components offer the opportunity of addressing these issues in buildings. Building integration of photovoltaics permits building components such as semi-transparent façade, skylights and shading devices to be replaced with PV. Much progress has been made in photovoltaic material science, where smart window development has evolved in areas such as semi-transparent PV, electrochromic and thermochromic materials, luminescent solar concentrator and the integration of each of the latter technologies to buildings, specifically windows. This paper presents a review on intelligent window technologies that integrate renewable energy technologies with energy-saving strategies contributing potential solutions towards sustainable zero-energy buildings. This review is a comprehensive evaluation of intelligent windows focusing on state-of-the-art development in windows that can generate electricity and their electrical, thermal and optical characteristics. This review provides a summary of current work in intelligent window design for energy generation and gives recommendations for further research opportunities.

Short-term Distributed Energy Resource Scheduling for a DC Microgrid

A microgrid is associated with a low voltage distribution power network and inherits small modular generation systems and loads that have certain coordinated functions to provide the solution to supply premium power to remote or specific areas. Similar to conventional power systems, the energy management of distributed generation resources (DERs) is carried out to minimize the operation cost and maximize benefit of installation of DERS in a microgrid. This paper presents the process of implementing the short-term DER scheduling function for a dc microgrid. The optimal scheduling results for two operation modes are then reported.