Economic Analysis of Grid-Connected PV System Regulations: A Hungarian Case Study

The energy demand of mankind is constantly growing, thus the utilization of various renewable energy sources, which also reduces negative environmental effects, is becoming more and more important. Because of the achievement of climate protection targets, photovoltaic (PV) energy has an increasing role in the global energy mix. This paper presents the technical and economic aspects of different photovoltaic system configurations designed to suit the Hungarian renewable energy regulations. In this study, five alternative PV configurations were examined for systems with a capacity from 50 kW to 500 kW, related to low- and medium-voltage installations. This article also introduces and explains the Hungarian economic PV and Feed-in-Tariff (FiT) regulations, where three different investment alternatives are analyzed with the help of economic indicators. This study could help stakeholders in the market (e.g., the Hungarian industry sector and local governments) understand the possible directions of technical and economic PV development. According to the results, the payback periods in all the studied economic-technical cases were below 10 years. The experimental results show that each investment option may be a good decision from an economic and technical point of view under the Hungarian regulations in force in 2019.

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Optimisation of Energy Accumulation for Renewable Energy Sources

Renewable Energy and Power Quality Journal ◽

10.24084/repqj19.258 ◽

2021 ◽

Vol 19 ◽

pp. 205-210

Author(s):

Milan Belik ◽

Keyword(s):

Renewable Energy ◽

Model Building ◽

Residential Buildings ◽

Renewable Energy Sources ◽

Photovoltaic System ◽

Energy Sources ◽

Pv System ◽

Energy Accumulation ◽

Wind Power Station ◽

Future Production

This project focuses on optimisation of energy accumulation for various types of distributed renewable energy sources. The main goal is to prepare charging – discharging strategy depending on actual power consumption and prediction of consumption and production of utilised renewable energy sources for future period. The simulation is based on real long term data measured on photovoltaic system, wind power station and meteo station between 2004 – 2021. The data from meteo station serve as the input for the simulation and prediction of the future production while the data from PV system and wind turbine are used either as actual production or as a verification of the predicted values. Various parameters are used for trimming of the optimisation process. Influence of the charging strategy, discharging strategy, values and shape of the demand from the grid and prices is described on typical examples of the simulations. The main goal is to prepare and verify the system in real conditions with real load chart and real consumption defined by the model building with integrated renewable energy sources. The system can be later used in general installations on commercial or residential buildings.

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Research Survey on Different MPP Tracking Optimization Algorithms for Solar Photovoltaic System (SPS)

Turkish Journal of Computer and Mathematics Education (TURCOMAT) ◽

10.17762/turcomat.v12i6.5767 ◽

2021 ◽

Vol 12 (6) ◽

pp. 2666-2671

Author(s):

R. Mohan Kumar, Dr. C. Kathirvel

Keyword(s):

Renewable Energy ◽

Direct Method ◽

Renewable Energy Sources ◽

Photovoltaic System ◽

Solar Irradiation ◽

Operating Efficiency ◽

Solar Photovoltaic ◽

Solar Pv ◽

Pv System ◽

Solar Pv System

Due to increase in global warming, it is required to choose an alternative renewable energy source for the electricity generation. Among various renewable energy sources (RES), photo-voltaic energy is one of the most accessible source of energies. But the conversion rate of solar PV cell is about 25 % to 40 % of solar irradiation level. In Solar Photovoltaic (PV) system, to improve and maximize the operating efficiency level, Maximum Power Point Tracking (MPPT) techniques were required. Because of the change in the level of solar irradiance, and the nature of dynamic temperature, this MPP tracking will be highly important to make the solar PV system (SPS) to operate at higher efficiency level. This MPPT method is mainly categorized into three different types such as direct method, indirect method and intelligent method. This paper will gives and overview about various MPPT methods employed for solar PV system. Various controlling algorithms were discussed in this section for a better understanding.

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Renewable Energy for Federal Land Management Agencies in Southern Nevada

ASME 2008 2nd International Conference on Energy Sustainability, Volume 2 ◽

10.1115/es2008-54230 ◽

2008 ◽

Author(s):

Todd France ◽

Eric Wiemers ◽

Stephen E. Butterworth ◽

Yahia Baghzouz ◽

Robert F. Boehm

Keyword(s):

Renewable Energy ◽

Energy Demand ◽

Las Vegas ◽

Renewable Energy Sources ◽

Electrical Energy ◽

Federal Agencies ◽

Pv System ◽

Southern Nevada ◽

Study Results ◽

Federal Land

The National Park Service, the U.S. Fish and Wildlife Service, and the USDA Forest Service governmental agencies in southern Nevada have collaborated with the Center for Energy Research at the University of Nevada, Las Vegas to explore the feasibility of becoming energy neutral by 2010. The three federal agencies have set a goal to offset their combined annual energy demand (currently supplied by local utility companies) with an equal amount of power produced by renewable energy sources. The study results indicate that the three federal agencies above consume just over 3,000 megawatt-hours of electrical energy per year in and around the Las Vegas Valley. Upon researching various types of renewable energy, it was determined that wind, geothermal, and biomass technologies either failed to have sufficient resources available in southern Nevada or conflicted with the resource management philosophies of the federal agencies. Solar energy is the most abundant feasible source of renewable energy within the study area, and it was determined that a 1.5 megawatt fixed photovoltaic (PV) system is best suited for this project.

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Techno-Economic Analysis of a Novel Hydrogen-Based Hybrid Renewable Energy System for Both Grid-Tied and Off-Grid Power Supply in Japan: The Case of Fukushima Prefecture

Applied Sciences ◽

10.3390/app10124061 ◽

2020 ◽

Vol 10 (12) ◽

pp. 4061 ◽

Cited By ~ 3

Author(s):

Naoto Takatsu ◽

Hooman Farzaneh

Keyword(s):

Renewable Energy ◽

Energy Demand ◽

Renewable Energy Sources ◽

Economic Assessment ◽

Energy System ◽

Modeling Framework ◽

Integrated Simulation ◽

Hybrid Renewable Energy System ◽

Renewable Energy System ◽

Hybrid Renewable Energy

After the Great East Japan Earthquake, energy security and vulnerability have become critical issues facing the Japanese energy system. The integration of renewable energy sources to meet specific regional energy demand is a promising scenario to overcome these challenges. To this aim, this paper proposes a novel hydrogen-based hybrid renewable energy system (HRES), in which hydrogen fuel can be produced using both the methods of solar electrolysis and supercritical water gasification (SCWG) of biomass feedstock. The produced hydrogen is considered to function as an energy storage medium by storing renewable energy until the fuel cell converts it to electricity. The proposed HRES is used to meet the electricity demand load requirements for a typical household in a selected residential area located in Shinchi-machi in Fukuoka prefecture, Japan. The techno-economic assessment of deploying the proposed systems was conducted, using an integrated simulation-optimization modeling framework, considering two scenarios: (1) minimization of the total cost of the system in an off-grid mode and (2) maximization of the total profit obtained from using renewable electricity and selling surplus solar electricity to the grid, considering the feed-in-tariff (FiT) scheme in a grid-tied mode. As indicated by the model results, the proposed HRES can generate about 47.3 MWh of electricity in all scenarios, which is needed to meet the external load requirement in the selected study area. The levelized cost of energy (LCOE) of the system in scenarios 1 and 2 was estimated at 55.92 JPY/kWh and 56.47 JPY/kWh, respectively.

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A Sizing Method for PV–Battery–Generator Systems for Off-Grid Applications Based on the LCOE

Energies ◽

10.3390/en14071988 ◽

2021 ◽

Vol 14 (7) ◽

pp. 1988

Author(s):

Ioannis E. Kosmadakis ◽

Costas Elmasides

Keyword(s):

Renewable Energy ◽

Energy Demand ◽

Renewable Energy Sources ◽

Temporal Distribution ◽

Electrical Energy ◽

Optimal Number ◽

Diesel Generator ◽

Levelized Cost Of Electricity ◽

Sufficient Power ◽

Battery Energy

Electricity supply in nonelectrified areas can be covered by distributed renewable energy systems. The main disadvantage of these systems is the intermittent and often unpredictable nature of renewable energy sources. Moreover, the temporal distribution of renewable energy may not match that of energy demand. Systems that combine photovoltaic modules with electrical energy storage (EES) can eliminate the above disadvantages. However, the adoption of such solutions is often financially prohibitive. Therefore, all parameters that lead to a functionally reliable and self-sufficient power generation system should be carefully considered during the design phase of such systems. This study proposes a sizing method for off-grid electrification systems consisting of photovoltaics (PV), batteries, and a diesel generator set. The method is based on the optimal number of PV panels and battery energy capacity whilst minimizing the levelized cost of electricity (LCOE) for a period of 25 years. Validations against a synthesized load profile produced grid-independent systems backed by different accumulator technologies, with LCOEs ranging from 0.34 EUR/kWh to 0.46 EUR/kWh. The applied algorithm emphasizes a parameter of useful energy as a key output parameter for which the solar harvest is maximized in parallel with the minimization of the LCOE.

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Optimal Planning and Operation of a Residential Energy Community under Shared Electricity Incentives

Energies ◽

10.3390/en14082045 ◽

2021 ◽

Vol 14 (8) ◽

pp. 2045

Author(s):

Pierpaolo Garavaso ◽

Fabio Bignucolo ◽

Jacopo Vivian ◽

Giulia Alessio ◽

Michele De Carli

Keyword(s):

Renewable Energy ◽

Power Distribution ◽

Energy Demand ◽

Renewable Energy Sources ◽

Energy System ◽

Distribution Networks ◽

Building Envelope ◽

Net Energy ◽

Technical Equipment ◽

Optimal Planning

Energy communities (ECs) are becoming increasingly common entities in power distribution networks. To promote local consumption of renewable energy sources, governments are supporting members of ECs with strong incentives on shared electricity. This policy encourages investments in the residential sector for building retrofit interventions and technical equipment renovations. In this paper, a general EC is modeled as an energy hub, which is deemed as a multi-energy system where different energy carriers are converted or stored to meet the building energy needs. Following the standardized matrix modeling approach, this paper introduces a novel methodology that aims at jointly identifying both optimal investments (planning) and optimal management strategies (operation) to supply the EC’s energy demand in the most convenient way under the current economic framework and policies. Optimal planning and operating results of five refurbishment cases for a real multi-family building are found and discussed, both in terms of overall cost and environmental impact. Simulation results verify that investing in building thermal efficiency leads to progressive electrification of end uses. It is demonstrated that the combination of improvements on building envelope thermal performances, photovoltaic (PV) generation, and heat pump results to be the most convenient refurbishment investment, allowing a 28% overall cost reduction compared to the benchmark scenario. Furthermore, incentives on shared electricity prove to stimulate higher renewable energy source (RES) penetration, reaching a significant reduction of emissions due to decreased net energy import.

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Forecasting and Modelling the Uncertainty of Low Voltage Network Demand and the Effect of Renewable Energy Sources

Energies ◽

10.3390/en14082151 ◽

2021 ◽

Vol 14 (8) ◽

pp. 2151

Author(s):

Feras Alasali ◽

Husam Foudeh ◽

Esraa Mousa Ali ◽

Khaled Nusair ◽

William Holderbaum

Keyword(s):

Renewable Energy ◽

Low Voltage ◽

Renewable Energy Sources ◽

Golden Ratio ◽

Clean Energy ◽

Energy Sources ◽

Percentage Error ◽

Ann Model ◽

Demand Forecast ◽

Pv System

More and more households are using renewable energy sources, and this will continue as the world moves towards a clean energy future and new patterns in demands for electricity. This creates significant novel challenges for Distribution Network Operators (DNOs) such as volatile net demand behavior and predicting Low Voltage (LV) demand. There is a lack of understanding of modern LV networks’ demand and renewable energy sources behavior. This article starts with an investigation into the unique characteristics of householder demand behavior in Jordan, connected to Photovoltaics (PV) systems. Previous studies have focused mostly on forecasting LV level demand without considering renewable energy sources, disaggregation demand and the weather conditions at the LV level. In this study, we provide detailed LV demand analysis and a variety of forecasting methods in terms of a probabilistic, new optimization learning algorithm called the Golden Ratio Optimization Method (GROM) for an Artificial Neural Network (ANN) model for rolling and point forecasting. Short-term forecasting models have been designed and developed to generate future scenarios for different disaggregation demand levels from households, small cities, net demands and PV system output. The results show that the volatile behavior of LV networks connected to the PV system creates substantial forecasting challenges. The mean absolute percentage error (MAPE) for the ANN-GROM model improved by 41.2% for household demand forecast compared to the traditional ANN model.

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Modelling of an Optimized Microgrid Model by Integrating DG Distributed Generation Sources to IEEE 13 Bus System

European Journal of Electrical Engineering and Computer Science ◽

10.24018/ejece.2021.5.2.309 ◽

2021 ◽

Vol 5 (2) ◽

pp. 18-25

Author(s):

Bisma Imtiaz ◽

Imran Zafar ◽

Cui Yuanhui

Keyword(s):

Renewable Energy ◽

Distributed Generation ◽

Energy Demand ◽

High Reliability ◽

Renewable Energy Sources ◽

Energy Sources ◽

Efficient Manner ◽

Matlab Simulink ◽

Control Scheme ◽

Power Quality Improvement

Due to the rapid increase in energy demand with depleting conventional sources, the world’s interest is moving towards renewable energy sources. Microgrid provides easy and reliable integration of distributed generation (DG) units based on renewable energy sources to the grid. The DG’s are usually integrated to microgrid through inverters. For a reliable operation of microgrid, it must have to operate in grid connected as well as isolated mode. Due to sudden mode change, performance of the DG inverter system will be compromised. Design and simulation of an optimized microgrid model in MATLAB/Simulink is presented in this work. The goal of the designed model is to integrate the inverter-interfaced DG’s to the microgrid in an efficient manner. The IEEE 13 bus test feeder has been converted to a microgrid by integration of DG’s including diesel engine generator, photovoltaic (PV) block and battery. The main feature of the designed MG model is its optimization in both operated modes to ensure the high reliability. For reliable interconnection of designed MG model to the power grid, a control scheme for DG inverter system based on PI controllers and DQ-PLL (phase-locked loop) has been designed. This designed scheme provides constant voltage in isolated mode and constant currents in grid connected mode. For power quality improvement, the regulation of harmonic current insertion has been performed using LCL filter. The performance of the designed MG model has been evaluated from the simulation results in MATLAB/ Simulink.

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Optimal Configuration and Sizing of Seaport Microgrids including Renewable Energy and Cold Ironing—The Port of Aalborg Case Study

Energies ◽

10.3390/en15020431 ◽

2022 ◽

Vol 15 (2) ◽

pp. 431

Author(s):

Nur Najihah Abu Bakar ◽

Josep M. Guerrero ◽

Juan C. Vasquez ◽

Najmeh Bazmohammadi ◽

Muzaidi Othman ◽

...

Keyword(s):

Renewable Energy ◽

Renewable Energy Sources ◽

Storage System ◽

Maximum Load ◽

Optimal Operation ◽

Economic Feasibility ◽

Photovoltaic System ◽

Design Stage ◽

Component Size

Microgrids are among the promising green transition technologies that will provide enormous benefits to the seaports to manage major concerns over energy crises, environmental challenges, and economic issues. However, creating a good design for the seaport microgrid is a challenging task, considering different objectives, constraints, and uncertainties involved. To ensure the optimal operation of the system, determining the right microgrid configuration and component size at minimum cost is a vital decision at the design stage. This paper aims to design a hybrid system for a seaport microgrid with optimally sized components. The selected case study is the Port of Aalborg, Denmark. The proposed grid-connected structure consists of renewable energy sources (photovoltaic system and wind turbines), an energy storage system, and cold ironing facilities. The seaport architecture is then optimized by utilizing HOMER to meet the maximum load demand by considering important parameters such as solar global horizontal irradiance, temperature, and wind resources. Finally, the best configuration is analyzed in terms of economic feasibility, energy reliability, and environmental impacts.

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Energy Efficiency – Indoor Air Quality Dilemma in Educational Buildings: A Possible Solution

Environmental and Climate Technologies ◽

10.2478/rtuect-2020-0020 ◽

2020 ◽

Vol 24 (1) ◽

pp. 357-367

Author(s):

Liva Asere ◽

Andra Blumberga

Keyword(s):

Energy Efficiency ◽

Renewable Energy ◽

Air Quality ◽

Indoor Air Quality ◽

Indoor Air ◽

Renewable Energy Sources ◽

Energy Sources ◽

Pv System ◽

Educational Buildings ◽

Electricity Tariff

AbstractThe energy efficiency – indoor air quality dilemma is well known and the main drawback to operate the mechanical ventilation is electricity costs as concluded from previous studies. Educational buildings are one of the places where future taxpayers spend a lot of time. This paper aims to study an alternative solution on how to reduce energy efficiency – indoor air quality dilemma in educational buildings by adopting systems that use renewable energy sources. A typical education building in Latvia is taken as a case study by changing it from a consumer to prosumer. This building type has a specific electricity usage profile that makes the choice of photovoltaics (PV) power quite challenging so the various power options have been analysed and used for an electricity solution. Also, the more decentralised preference is chosen – disconnect from a public heating provider and using a local system with a pellet boiler. Educational buildings using PV can reduce the electricity tariff, but the payback periods are still not very satisfactory without subsidies. The average electricity tariff per month varies between scenarios and the best one is for the scenario with 30 kW installed power. The educational building partly using 16 kW PV system reduces not only its bill for electricity but also reduces CO2 emissions by around 36 tons. The education buildings as energy prosumers using renewable energy sources are reducing GHG emissions by having high indoor air quality.

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