An economic assessment of distributed solar PV generation in Sweden from a consumer perspective – The impact of demand response

2017 ◽  
Vol 108 ◽  
pp. 169-178 ◽  
Author(s):  
Emil Nyholm ◽  
Mikael Odenberger ◽  
Filip Johnsson
Keyword(s):  
Demand Response ◽  
Economic Assessment ◽  
Solar Pv ◽  
Consumer Perspective ◽  
Pv Generation ◽  
The Impact

scholarly journals Techno-Economic Assessment of Rooftop PV Systems in Residential Buildings in Hot–Humid Climates

2020 ◽  
Vol 12 (23) ◽  
pp. 10060
Author(s):  
Ammar Hamoud Ahmad Dehwah ◽  
Muhammad Asif ◽  
Ismail Mohammad Budaiwi ◽  
Adel Alshibani
Keyword(s):  
Residential Buildings ◽  
Economic Assessment ◽  
Climatic Conditions ◽  
Design Parameters ◽  
Solar Pv ◽  
Utilization Factor ◽  
Technical Performance ◽  
Pv Systems ◽  
Residential Units ◽  
The Impact

The application of renewable energy has been an integral part of the sustainability drive in the building sector and solar photovoltaic (PV) is one of the most effective technologies in this respect. The present study aims to investigate the prospects of solar PV in residential buildings in the hot–humid climatic conditions. The study discusses the utilization of building roofs for the application of PV in terms of potential hurdles and utilization factor (UF). Technical performance of PV systems has also been investigated in terms of power output as well as the energy saved as a result of the shading impact of panels for two types of residential units, apartments and villas. Investigation of 70 sample residential buildings reveals the average UF of 0.21 and 0.28 for apartments and villas, respectively. For the case study of apartment and villa residential units, roof UF has been found to be 13% and 15% with a respective PV output of 6079 kWh/year and 6162 kWh/year. Potential PV output at the city level has also been estimated. A sensitivity analysis has been conducted to evaluate the impact of various cost and design parameters on the viability of PV systems.

scholarly journals Virtual storage capacity using demand response management to overcome intermittency of solar PV generation

2017 ◽  
Vol 11 (14) ◽  
pp. 1741-1748 ◽  
Author(s):  
Nandha Kumar Kandasamy ◽  
King Jet Tseng ◽  
Soong Boon‐Hee
Keyword(s):  
Demand Response ◽  
Storage Capacity ◽  
Solar Pv ◽  
Virtual Storage ◽  
Pv Generation

scholarly journals XGBoost-Based Day-Ahead Load Forecasting Algorithm Considering Behind-the-Meter Solar PV Generation

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 128
Author(s):  
Dong-Jin Bae ◽  
Bo-Sung Kwon ◽  
Kyung-Bin Song
Keyword(s):  
Load Forecasting ◽  
Rapid Expansion ◽  
Gradient Boosting ◽  
Base Temperature ◽  
Electric Load ◽  
Solar Pv ◽  
Model Case ◽  
Extreme Gradient Boosting ◽  
Pv Generation ◽  
The Impact

With the rapid expansion of renewable energy, the penetration rate of behind-the-meter (BTM) solar photovoltaic (PV) generators is increasing in South Korea. The BTM solar PV generation is not metered in real-time, distorts the electric load and increases the errors of load forecasting. In order to overcome the problems caused by the impact of BTM solar PV generation, an extreme gradient boosting (XGBoost) load forecasting algorithm is proposed. The capacity of the BTM solar PV generators is estimated based on an investigation of the deviation of load using a grid search. The influence of external factors was considered by using the fluctuation of the load used by lighting appliances and data filtering based on base temperature, as a result, the capacity of the BTM solar PV generators is accurately estimated. The distortion of electric load is eliminated by the reconstituted load method that adds the estimated BTM solar PV generation to the electric load, and the load forecasting is conducted using the XGBoost model. Case studies are performed to demonstrate the accuracy of prediction for the proposed method. The accuracy of the proposed algorithm was improved by 21% and 29% in 2019 and 2020, respectively, compared with the MAPE of the LSTM model that does not reflect the impact of BTM solar PV.

Reliability modeling and performance evaluation of solar photovoltaic system using Gumbel–Hougaard family copula

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anas Sani Maihulla ◽  
Ibrahim Yusuf ◽  
Muhammad Salihu Isa
Keyword(s):  
Power Systems ◽  
Photovoltaic System ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Content Type ◽  
Reliability Indices ◽  
Pv Systems ◽  
Sensitivity Tests ◽  
Pv Generation ◽  
The Impact

PurposeSolar photovoltaic (PV) is commonly used as a renewable energy source to provide electrical power to customers. This research establishes a method for testing the performance reliability of large grid-connected PV power systems. Solar PV can turn unrestricted amounts of sunlight into energy without releasing carbon dioxide or other contaminants into the atmosphere. Because of these advantages, large-scale solar PV generation has been increasingly incorporated into power grids to meet energy demand. The capability of the installation and the position of the PV are the most important considerations for a utility company when installing solar PV generation in their system. Because of the unpredictability of sunlight, the amount of solar penetration in a device is generally restricted by reliability constraints. PV power systems are made up of five PV modules, with three of them needing to be operational at the same time. In other words, three out of five. Then there is a charge controller and a battery bank with three batteries, two of which must be consecutively be in operation. i.e. two out of three. Inverter and two distributors, all of which were involved at the same time. i.e. two out of two. In order to evaluate real-world grid-connected PV networks, state enumeration is used. To measure the reliability of PV systems, a collection of reliability indices has been created. Furthermore, detailed sensitivity tests are carried out to examine the effect of various factors on the efficiency of PV power systems. Every module's test results on a realistic 10-kW PV system. To see how the model works in practice, many scenarios are considered. Tables and graphs are used to show the findings.Design/methodology/approachThe system of first-order differential equations is formulated and solved using Laplace transforms using regenerative point techniques. Several scenarios were examined to determine the impact of the model under consideration. The calculations were done with Maple 13 software.FindingsThe authors get availability, reliability, mean time to failure (MTTF), MTTF sensitivity and gain feature in this research. To measure the reliability of PV systems, a collection of reliability indices has been created. Furthermore, detailed sensitivity tests are carried out to examine the effect of various factors on the efficiency of PV power systems.Originality/valueThis is the authors' original copy of the paper. Because of the importance of the study, the references are well-cited. Nothing from any previously published articles or textbooks has been withdrawn.

scholarly journals Monte Carlo analysis for solar PV impact assessment in MV distribution networks

2021 ◽  
Vol 23 (1) ◽  
pp. 23
Author(s):  
Dilini Almeida ◽  
Jagadeesh Pasupuleti ◽  
Shangari K. Raveendran ◽  
M. Reyasudin Basir Khan
Keyword(s):  
Monte Carlo ◽  
Distribution Network ◽  
Distribution Networks ◽  
Monte Carlo Analysis ◽  
Solar Pv ◽  
Probabilistic Framework ◽  
Load Demand ◽  
Pv Generation ◽  
Pv Penetration ◽  
The Impact

The rapid penetration of solar photovoltaic (PV) systems in distribution networks has imposed various implications on network operations. Therefore, it is imperative to consider the stochastic nature of PV generation and load demand to address the operational challenges in future PV-rich distribution networks. This paper proposes a Monte Carlo based probabilistic framework for assessing the impact of PV penetration on medium voltage (MV) distribution networks. The uncertainties associated with PV installation capacity and its location, as well as the time-varying nature of PV generation and load demand were considered for the implementation of the probabilistic framework. A case study was performed for a typical MV distribution network in Malaysia, demonstrating the effectiveness of Monte Carlo analysis in evaluating the potential PV impacts in the future. A total of 1000 Monte Carlo simulations were conducted to accurately identify the influence of PV penetration on voltage profiles and network losses. Besides, several key metrics were used to quantify the technical performance of the distribution network. The results revealed that the worst repercussion of high solar PV penetration on typical Malaysian MV distribution networks is the violation of the upper voltage statutory limit, which is likely to occur beyond 70% penetration level.

scholarly journals Risk-Averse Scheduling of Combined Heat and Power-Based Microgrids in Presence of Uncertain Distributed Energy Resources

2021 ◽  
Vol 13 (13) ◽  
pp. 7119
Author(s):  
Abbas Rabiee ◽  
Ali Abdali ◽  
Seyed Masoud Mohseni-Bonab ◽  
Mohsen Hazrati
Keyword(s):  
Electrical Energy ◽  
High Energy ◽  
Combined Heat And Power ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Solar Pv ◽  
Distributed Energy ◽  
Robust Scheduling ◽  
Battery Energy ◽  
The Impact

In this paper, a robust scheduling model is proposed for combined heat and power (CHP)-based microgrids using information gap decision theory (IGDT). The microgrid under study consists of conventional power generation as well as boiler units, fuel cells, CHPs, wind turbines, solar PVs, heat storage units, and battery energy storage systems (BESS) as the set of distributed energy resources (DERs). Additionally, a demand response program (DRP) model is considered which has a successful performance in the microgrid hourly scheduling. One of the goals of CHP-based microgrid scheduling is to provide both thermal and electrical energy demands of the consumers. Additionally, the other objective is to benefit from the revenues obtained by selling the surplus electricity to the main grid during the high energy price intervals or purchasing it from the grid when the price of electricity is low at the electric market. Hence, in this paper, a robust scheduling approach is developed with the aim of maximizing the total profit of different energy suppliers in the entire scheduling horizon. The employed IGDT technique aims to handle the impact of uncertainties in the power output of wind and solar PV units on the overall profit.

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