Photovoltaic Panel Array Research Articles

Current Compensation for Faulted Grid-Connected PV Arrays Using a Modified Voltage-Fed Quasi-Z-Source Inverter

Large-scale photovoltaic (PV) systems are being widely deployed to meet global environmental goals and renewable energy targets. Advances in PV technology have driven investment in the electric sector. However, as the size of PV arrays grows, more obstacles and challenges emerge. The primary obstacles are the occurrence of direct current (DC) faults and shading in a large array of PV panels, where any malfunction in a single panel can have a detrimental impact on the overall output power of the entire series-connected PV string and therefore the PV array. Due to the abrupt and frequent fluctuations in power, beside the low-PV systems’ moment of inertia, various technical problems may arise at the point of common coupling (PCC) of grid-connected PV generations, such as frequency and voltage stability, power efficiency, voltage sag, harmonic distortion, and other power quality factors. The majority of the suggested solutions were deficient in several crucial transient operating features and cost feasibility; therefore, this paper introduces a novel power electronic DC–DC converter that seeks to mitigate these effects by compensating for the decrease in current on the DC side of the system. The suggested solution was derived from the dual-source voltage-fed quasi-Z-source inverter (VF-qZSI), where the PV generation power can be supported by an energy storage element. This paper also presents the system architecture and the corresponding power switching control. The feasibility of the proposed method is investigated with real field data and the PSCAD simulation platform during all possible weather conditions and array faults. The results demonstrate the feasibility and capability of the proposed scheme, which contributes in suppressing the peak of the transient power-to-time variation (dP/dt) by 72% and reducing its normalized root-mean-square error by about 38%, with an AC current total harmonic distortion (THD) of only 1.04%.

Toward A Micrometeorological Assessment Of Agrivoltaic Farms: A Feature Tracking Velocimetry-Based Analysis

We investigate the flow dynamics around a model of an array of photovoltaic panels via laboratory experiments conducted in a water channel. The model farm consists of transparent polycarbonate panels with varying tilt angles, simulating different configurations typical of agrivoltaic systems. Velocities are measured using a feature tracking velocimetry technique. Results reveal distinct flow structures depending on the tilt angle of the panels and the distance between them, with varying numbers of recirculation regions observed. An increase in the distance between panels stretches the recirculation regions along the streamwise direction. Turbulent kinetic energy is more intense with negative tilt angles, and upstream turbulence penetrates more between panels. These findings suggest different transport and heat transfer properties, particularly relevant for tracker PV arrays that adjust tilt angles throughout the day. Understanding these dynamics is crucial for optimizing the design and operation of agrivoltaic farms to maximize energy production while minimizing impacts on agricultural productivity and the surrounding environment.

Study of Wind Load Influencing Factors of Flexibly Supported Photovoltaic Panels

Flexible photovoltaic (PV) support structures are limited by the structural system, their tilt angle is generally small, and the effect of various factors on the wind load of flexibly supported PV panels remains unclear. In order to investigate the shape coefficients of the flexibly supported PV panel arrays, the grid-independent validation is carried out first, and then the case study validation is carried out to ensure the accuracy of the method in this paper. The CFD numerical simulation method is used to obtain the wind load variation of the PV panel array with different tilt angles, different spacing ratios, different wind angles, different heights above ground, different regions, and mountainous conditions. The distribution of wind pressure coefficients on the surface of PV panels with different inclination angles at different spacing ratios was investigated. The results show that the wind load shape coefficients with the increase in tilt angle and height above ground are basically a linear growth; the maximum value of PV shape coefficients appears in the wind angle at 30°, and 150° near the different tilt angles of the flexible PV array group shape coefficients distribution law is inconsistent. Different tilt angles of PV modules with the change rule of the spacing ratio of the wind load are inconsistent and have a greater impact on the wind load, so the PV panel array in all wind direction angles under the regional shape coefficients has a recommended value. The proposed value of the regional shape coefficients at all wind angles and the wind load calculation formula introducing height coefficients and spacing ratio coefficients are given.

Study on Fault Monitoring Technology of Photovoltaic Panel Based on Thermal Infrared and Optical Remote Sensing

Abstract. Rapid access to the operating status of Photovoltaic (PV) panels and troubleshooting can save management and maintenance costs for the development of PV power plants, which is important for PV power plant management and power generation capacity assurance. The use of remote sensing technology to identify the faults of photovoltaic panels has developed rapidly, however, current research usually relies only on a single optical data source to identify and count the area of PV panels in a PV electric field, although there are literature on PV panel fault detection, only the surface fault identification of PV panels is tested, while the internal faults (such as panel bad points or bad lines) cannot be identified because of the limitations of optical remote sensing. In this paper, a photovoltaic panel fault monitoring technology based on multi-source remote sensing is proposed. The optical and thermal infrared hybrid data combined with deep learning technology are used to achieve rapid and accurate fault identification and localization of PV panel arrays. It can not only automatically identify PV panels that are obscured by dust and foreign objects, but also locate PV panels that have bad dots or bad lines, which greatly improves the ability and effectiveness of remote sensing PV panel fault monitoring. The high-resolution unmanned air vehicle (UAV) optical image and thermal infrared image are applied in this experiment. The Mask RCNN algorithm is used to accurately locate and number the photovoltaic panel of the optical image. Then, the fault scene classification model is established for the multi-type fault characteristics of the optical image and thermal infrared image within the panel range, so as to identify five types of faults, such as dust cover, branch cover, bird droppings cover, internal bad points and bad lines of PV panel, which effectively solves the problem that the single optical remote sensing image cannot identify the internal component faults of the photovoltaic panel under normal conditions.

Numerical Experimental Validation of a Proposed MPPT Algorithm with Dynamic Hysteresis for PV Systems

In the last decades, the renewable energies have had a highly positive effect on the daily life. This due to the necessity of reducing the common fuel energies that have negatively impacted the environment. Among all the available renewable energies, the solar energy is one of the most common. This energy is obtained through Photovoltaic (PV) systems. Thus, in previous years, new techniques of Maximum Power Point Tracking (MPPT) to raise the quality of the energy provided by PV panels have been proposed. Since the energy provided by the PV cells depends on the external environmental conditions, as temperature or sun irradiance, the MPPT methods should be adequate to deal with these external changes by maintaining the desired power level. Hence, this paper proposes a recent hysteretic dynamic technique to extract the maximum power from a PV panel array by employing a Boost DC/DC converter to supply energy to an inductive load. Here, a comparative study between the results obtained with the well known Perturb and Observer (P&O) algorithm and by using our dynamic hysteretic MPPT method is analyzed, specifically when the PV panel is submitted to fast variations in temperature and irradiance. It will be proved through numerical experiments realized in MatLab/Simulink that our hysteretic MPPT algorithm provides a better achievement of the maximum power of the PV panel in comparison to the conventional Perturb and Observer method.

Assessment of the large-scale extraction of photovoltaic (PV) panels with a workflow based on artificial neural networks and algorithmic postprocessing of vectorization results

Having a complete and high-quality geospatial catalogue of existing large-scale photovoltaic (PV) panels is very important nowadays, due to the rapid increase in the use of this type of installations. This catalogue could be used to estimate, with a higher level of granularity, the energy that can be produced from solar radiation forecasts, to operate the electricity system efficiently by adjusting supply to demand, as well as for fiscal reasons. However, most existing works in the specialized literature focus on the extraction of PV panels in reduced, favourable scenes. In this study, a processing strategy to obtain PV panel arrays geometries from aerial orthoimages at a very large scale, is proposed. The processing strategy includes operations for PV panel array classification and semantic extraction, and algorithmic improvement and simplification of the vectorization results. The processing workflow was trained and tested on two datasets containing aerial images of 256 × 256 pixels with the studied polygonal feature at two different spatial resolutions (with more than 185,000 and 690,000 images for spatial resolutions of 0.5 m and 0.25 m, respectively). The image tiles were labelled at pixel level with PV panel information for both spatial resolutions and cover representative, extended urban and rural regions of Spain. The accuracies achieved in the PV panel arrays classification are superior to 0.999, while the semantic segmentation performance is superior to 0.90 in the Intersection over Union score. The assessment of the proposed procedure of fifteen new, unseen areas distributed over the Spanish territory (covering approximately 8125 km2) demonstrated its suitability (in the analysis, percentage of incompletely detected installations of only 11 % were achieved) and indicated that future works focused on the improvement of the initial predictions are should be carried out.

CFD simulations for layout optimal design for ground-mounted photovoltaic panel arrays

Photovoltaic (PV) power plants play an important role in regulating regional energy structures and reducing carbon emissions. The existence of PV power plants also alters the microclimate in surrounding environments, which requires an optimal design of their layout and structural parameters. PV power plants consist of arrays of ground-mounted PV panels. In this study, 3D computational fluid dynamics (CFD) simulations based on the shear-stress transport k–ω turbulence model were performed to study airflow around ground-mounted PV panel arrays. The accuracy of the CFD model was validated by comparing the simulated results with field data. Different scenarios were established by changing the wind velocity, arrangement of PV panel arrays (i.e., row and column spacing), and key structural parameters (i.e., panel inclination angle). The results showed that the highest drag coefficient (CD) and lift coefficients (CL) were found behind the first row of the arrays for straight winds (0° and 180°), while the minimum wind loads (lift and drag) are encountered by the middle of the array for oblique winds (45° and 135°). According to the wind resistance effect, the PV panel array with an inclination angle of 35°, a column spacing of 0 m, and a row spacing of 3 m had the best efficiency of wind block. As the increase of ambient wind velocity, the inclination angle should be reduced to rise the resistance efficiency and avoid possible damage to PV panels. This study provides scientific reference for an optimal design and construction of PV power plants in terms of wind resistance.

A novel optimization for liquefied natural gas power plants based on the renewable energy

As the world's energy demand grows, the liquefied natural gas industry is gaining popularity as a cleaner fossil fuel source. The existing economic dispatch models of the liquefied natural gas-fueled oxy-fuel combined cycle integrating the renewable energy sources and the energy storage system are not applicable because of lacking modeling and optimizing of the renewable energy sources and energy storage system. This paper proposed a novel economic dispatch model to maximize the generation benefits for determining the optimal configuration of photovoltaic array panels, wind turbines, and the energy storage battery. We established and decoupled the energy-mass coupling model of a liquefied natural gas-fueled oxy-fuel combined cycle, developed the photovoltaic array panel, the wind turbine, and the storage battery model, and calculated the time-of-use electricity price, levelized cost of energy, and levelized cost of storage energy. The model determined the optimal ratio of the photovoltaic array panel and the wind turbine, the installed capacity of the storage battery, and allocated the power of the renewable energy sources and the online grid properly. The results showed that within 120 h, the renewable energy sources reduced the grid load by 40.81%, and the total generation of the photovoltaic array panel and the wind turbine was only 24.86% and 37.39% of the installed capacity. And the energy storage battery is in dynamic balance, with a net discharge capacity of 298.23 MW. The levelized cost of energy was the key factor affecting photovoltaic array panels/ wind turbines installed capacity. The installed percentage of wind turbines did not affect the energy storage systems capacity but the total economic benefit.

A Novel MPPT Technique based on Hybrid Radial Movement Optimization with Teaching Learning Based Optimization for PV system

Because of its pure and plentiful accessibility, solar power is a remarkable resource of energy for the generation of electrical power. The solar photovoltaic mechanism transforms sunlight striking the photovoltaic solar panel or array of photovoltaic panels directly into non-linear DC power. Due to the nonlinear characteristics of solar photovoltaic panels, power must be tracked for their effective usage. When the photovoltaic arrays are shaded, the problem of nonlinearity becomes more pronounced, resulting in large power loss and intensive heating in a few areas of the photovoltaic arrangement. The tracking challenge is made more difficult by the fact that bypass diodes, which are used to completely eradicate the shading effect, generate numerous power peak levels on the power vs. voltage (P-V) curve. Traditional methods for tracing the global peak point are unable to examine the entire P-V curve as they frequently get stuck at the local peak point. Recently, machine learning or optimization algorithms have been used to determine the global peak point. Because these algorithms are random, they search the entire search area, reducing the possibility of being caught in the local maximum value. This article proposes a hybrid of two optimization approaches: radial movement optimization and teaching-learning optimization (HRMOTLBO). The proposed MPPT method was thoroughly investigated and tested in a wide range of photovoltaic partial shading combinations. The recommended HRMOTLBO MPPT approach outperforms and is more reliable than a recent Jaya-based MPPT approach in terms of tracing time and power variation under dynamic and static partial shading conditions. Experimental as well as simulation outcomes demonstrate that the proposed MPPT successfully traces the global peak point in less time and with fewer fluctuations during various partial shading conditions.

Sustainable phytoextraction of metal-polluted agricultural land used for commercial photovoltaic power generation

Metal pollution of agricultural soils is currently an issue of major concern in China and many soils require remediation. Photovoltaic (PV) power generation is a useful source of renewable energy but solar power plants often require large areas of land. Combining PV power generation with phytoextraction on contaminated arable land is therefore a novel and potential option if these processes can work effectively together. A three-year-long continuous field study was conducted to test the feasibility of phytoextraction using a metal hyperaccumulator species growing under arrays of PV panels. Meteorological data were collected and the growth and cadmium (Cd) and zinc (Zn) uptake of the Cd/Zn hyperaccumulator Sedum plumbizincicola were determined. Shading by the PV panels reduced the annual solar irradiance by 58.4% but this showed no inhibitory effect on plant growth or metal uptake by S. plumbizincicola. Phytoextraction under the PV panels gave high removal efficiencies of Cd and Zn and the hyperaccumulator took up Cd and Zn at rates of 3.40 and 96.2 kg ha−1, respectively, for three seasons. It is concluded that soil phytoextraction and PV electricity generation can be combined to realize soil remediation and energy production.

Optimization of Photovoltaic Panel Array Configurations to Reduce Lift Force Using Genetic Algorithm and CFD

Aerodynamic lift force acting on the solar structure is important while designing the counterweight for rooftop-mounted solar systems. Due to their unique configuration, the load estimated for solar structures using international building codes can be either higher or lower than the actual. Computational Fluid Dynamics(CFD) simulations haveproven to be an efficient tool for estimating wind loads on solar panels for design purposes and identifying critical design cases. Computational Fluid Dynamics (CFD) simulations usually require high computation power, and slight changes in geometry to find optimum configuration can be time-consuming. An optimization method to minimize lift force effects on solar photovoltaic (PV) arrays installed on rooftops usesthe Computational Fluid Dynamics (CFD)and genetic algorithms proposed in this paper. The tilt angle and pitch between two rows of solar panels were parameterized, and a genetic algorithm was used to search for aconfiguration resulting in minimum wind lift force acting on the solar photovoltaic plant. Only combinations with a performance ratio >80% were considered. Three different rooftopphotovoltaic (PV) plant layout configurations were analyzed in this research. Two rows of photovoltaic (PV) panel arrays wereconsidered for optimization in the 2D domain using ANSYS Fluent. Results showed that the difference in wind-liftforce between optimized configurations against that with maximum lift force configuration for all three cases above was fifty percent.

Numerical simulation of the dust particles deposition on solar photovoltaic panels and its effect on power generation efficiency

The deposition of dust particles on the surface of solar photovoltaic panels leads to a decrease in power generation efficiency, so it is necessary to study the interaction mechanism between dust particles and solar photovoltaic panels. Aiming at the problem that the simplified two-dimensional model cannot reflect the actual photovoltaic power station in the traditional research, a geometric model of the distribution form of the 3 × 3 solar photovoltaic panel array is constructed. The shear stress transport k−ω turbulence model is used to predict the flow field changes around solar photovoltaic (PV). A discrete particle model is used to predict the particle deposition rate of photovoltaic panels. The effects of different wind speeds, particle sizes, and wind angles on particle deposition were analyzed. With the increase of wind speed, the deposition amount of the photovoltaic panels in the last two rows gradually decreased, while the photovoltaic panels in the first row showed a trend of first decreasing and then increasing. As the particle size increases, the particle deposition amount increases gradually. When the particle size is less than 60 μm, the deposition amount on the photovoltaic panel is less than 0.03g. When the particle size is greater than 60 μm, the deposition amount of particles increases exponentially. The maximum deposition amount is 3.98g, and the maximum deposition rate is 0.796% for 160 μm particles. Wind angle has different effects on the deposition on different rows of photovoltaic panels. When the wind Angle is 0°, the deposition amount of the first row of photovoltaic panels is the largest, the deposition amount is 4.66g, and the deposition rate is 0.932%. When the wind angle is 45°, the deposition amount on the second and third rows of photovoltaic panels is the largest, the deposition amount is 3.21g, and the deposition rate is 0.642%. Finally, the changes in the maximum output power of photovoltaic panels after 60 days of exposure were predicted using an improved dust particle occlusion model.

Designing a solar system that improved the solar system's performance in instances of partial shadowing

The great and decisive influence of the decision of nature or the natural factors of the earth, especially the strength of the solar radiation emitted by the sun and the temperature, remains an important condition and a factor that must be when talking about the exploitation or use of solar energy. From the beginning of the manufacture of solar cells to this day, the solar cell, which is the smallest component of the solar module or structure, has faced many challenges and difficulties, including design, manufacturing and cost challenges in addition to natural and abnormal factors. Among those challenges are natural and unnatural factors such as partial shading or full shading of the solar cell or the solar cells within the solar structure in the solar system, which directly affects the process of producing solar cells from electrical energy. As a result, these natural and unnatural challenges prevent the optimal and full exploitation of solar energy. Through this research paper, a new strategy was found, which is a simple electronic system to enhance the performance of solar cell production within the solar structure in the solar system, and this strategy includes the establishment of a new existing solar system. On a boosting system linked with the solar structure through which this electronic system can be connected to be an integral part of a solar system, to enhance the solar system's effectiveness in the production of electrical energy. The new solar system works in any conditions (natural and abnormal) and any type of shading (partial or total) for the solar panel or structure, through this new system, The quantity of electrical energy generated by the new solar system is equal to twice the energy of solar cells or arrays solar system within the solar structure under normal circumstances. In addition, the use of solar radiation tracking techniques is not important, as it is the strategic comparison used to determine the maximum power point tracking (MPPT) technology under various circumstances to produce good solar energy in poor lighting conditions by concentrating on the impacts of shadowing on the array of solar photovoltaic panels, a strategy that did not succeed in maintaining the productivity of the solar array from electrical energy in natural conditions, but the proposed model or the new methodological strategy helped to maintain the productivity of the solar cells or solar array from electrical energy in addition to increasing the production of electrical energy under the bad exposure conditions of the solar system. The proposed model is chosen in view of the fact that it may be able to reproduce different ranges of non-standard PV frames standardized by a new solar system with good multidimensional uses. The study may be presented here as a suitable source for future business of power generation (PV).

Techno-economic analysis of a solar-powered humidification-dehumidification desalination system under fogging effect

Different techniques are utilized to overcome the problem of freshwater shortage around the world. Humidification-dehumidification technology is among the promising methods, especially when powered by cost-effective solar energy sources or when used in remote desert areas with abundant solar resources. In this study, a solar energy-powered humidification-dehumidification system is assembled and tested. Two solar energy systems are supplying the humidification-dehumidification system with heat and electricity, namely an evacuated tube solar collector and an array of photovoltaic panels, respectively. The studied system utilizes three fogging nozzles, each with a 10-µm diameter, that allow efficient energy conversion. Also, the system was tested under the influence of a single nozzle with a larger diameter for comparison purposes. The fogging technique reduced the power consumption while boosting the total system productivity. The system was able to achieve a maximum gained output ratio of 4.4 at saline water and air temperatures of 80 and 53.44 °C, respectively. The rate of freshwater production ranged between 1.7 and 3.85 L/h. At the highest tested saline water to air ratio, the system with three 10-µm nozzles enhanced the gained output ratio by 23.68 and 67.33 %, compared to the single nozzle configuration with 20 and 30-µm diameter, respectively. An economic evaluation showed a best-averaged price of 0.0543 USD/L of freshwater.

CFD simulations for airflow around ground-mounted photovoltaic panel arrays

CFD simulations for airflow around ground-mounted photovoltaic panel arrays

Feasibility Assessment of Photovoltaic Systems to Save Energy Consumption in Residential Houses with Electric Vehicles in Chile

Distributed local generation from photovoltaic (PV) systems are gaining more interest, due to reduced component costs, as well as becoming a great solution for the charging of electric vehicles (EV) and the protection of the electrical grid infrastructure. This work aims to size and analyze the economic feasibility of a PV system to support the energy demand presented by the daily charge of an EV, either with or without a battery energy storage system (BESS), for a residential home in Viña del Mar, Chile. Eight different scenarios are dimensioned, with and without BESS, varying the PV installed power according to the surface available on the roof, and the results are supported by using the PVsyst software to determine the energy generated, self-consumption, and the energy both injected and received from the grid. Five different cases are also dimensioned, varying the storage capacity of the BESS, to analyze how profitability varies in each case. The real data on energy consumption, and prices of electricity both injected and received from the grid, were collected from the electricity bills and the distribution company, respectively. The sizing of both the PV panel array and the BESS was performed based on the highest average daily consumption throughout the year. Meteorological data, such as global irradiation and environmental temperature, are obtained from the Explorador Solar platform. Lastly, PV systems with BESS do not achieve profitability; however, for BESS with lower storage capacities, it would be possible to increase its profitability to acceptable ranges. Photovoltaic systems without BESS present better levels of profitability since a lower capital expenditures is required and the payback is shorter. This work contributes to improve the use of solar energy and provides a guide to extend the work to different regions of Chile.

Wind load characteristics of photovoltaic panel arrays mounted on flat roof

To quantify design wind load of photovoltaic panel array mounted on flat roof, wind tunnel tests were conducted in this study. Results show that the first and the last two rows on the roof are the most unfavorable ones regarding to the wind load. Influences of array spacing, panels’ tilt angle and parapet height on wind load of the panels are studied. Most unfavorable lift force of panels decreases with increase of array spacing for middle located panels. The aerodynamics are similar to flow over repeated hills. Middle located unit got greater turbulence, which leading to unfavorable C fp_min. While the changing amplitude of most unfavorable wind pressure is small increase with array spacing. C fp_max and C fp_min of panel units shows quite strong dependence on tilt angle. There is significant pressure equalization for small tilt angle cases. The local flow separation is responsible for C fp_min of larger tilt angle cases. Parapet height of 2 h (h is the panel height projected on the vertical plane) is the critical height for C fp_max and C fp_min. Increasing parapet height can significantly reduce the wind load of panel units. Design pressure coefficient of the basic working condition with different area sizes at different location are proposed.

Robust mixed H2/H∞ fuzzy tracking control of photovoltaic system subject to asymmetric actuator saturation

This paper focuses on mixed [Formula: see text] fuzzy maximum power point tracking (MPPT) of photovoltaic (PV) system under asymmetric saturation and variations in climatic conditions. To maximize the power from the PV panel array, the DC–DC boost converter is controlled by its duty ratio which is practically saturated between 0 and 1. MPPT based on conventional control presents the problems of oscillations around maximum power point (MPP) and divergence under rapid climatic changes. In order to attenuate the effect of atmospheric condition variation and take into account asymmetric saturation of the duty ratio, we propose a novel robust saturated controller based on both [Formula: see text] performances and Takagi-Sugeno (T-S) representation of PV-boost nonlinear system. Within this approach, the nonlinear PV-boost system and its reference are first described by T-S fuzzy models. Second, the saturation effect is represented by a polytopic model. Then, a fuzzy integral state feedback controller is designed to achieve stable MPPT control. Based on Lyapunov function, the mixed [Formula: see text] stabilization conditions are derived in terms of linear matrix inequalities (LMIs). The optimization of the attraction domain of closed-loop system is solved as a convex optimization problem in LMI terms. Finally, the efficiency of the proposed controller under irradiance and temperature variations is demonstrated through the simulation results. The comparison with some existing controllers shows an improvement of MPPT control performance in terms of power extraction.

Off-grid PV/URFC power plant fueled with biogas from food waste: An energetic and economic analysis

This paper presents the design, energy management and economic analysis of an off-grid power plant for a strip mall. The main goal is to achieve a 100% renewable operation, by using a photovoltaic panel array coupled to a battery and a unitized regenerative solid oxide fuel cell fed both with self-generated hydrogen and biogas produced from food waste in an on-site anaerobic digester. The power plant has been modeled by means of a self-made Matlab/Simulink® simulator and the plant operation has been simulated against different radiation and load demand scenarios. Results are compared both in terms of energetic and economic performance. In particular, it is observed that the annualized capital costs for unitized regenerative solid oxide fuel cell cover from 50% up to 58% of the total investment cost and from 71% up to 75% of the total replacement costs. Depending on the scenario and the specific tipping fee, tipping costs vary from a minimum of 9,793 $/y to a maximum 47,335 $/y. For all the analyzed scenarios, the cost of energy is higher than the grid electricity price, but the 100% renewable operation of the plant and the on-site waste conversion to biogas make this solution worth of investigation.

Cost Optimization of a Zero-Emission Office Building

The cost-effectiveness of energy efficiency measures meant to achieve a zero-emission office building is investigated and compared to business as usual energy efficiency measures. The laboratory for zero emission buildings, the ZEB Lab, located in Trondheim, Norway, is an office building designed and built to compensate its lifecycle emissions with the use of a large array of building-integrated photovoltaic panels, pursuing a zero-emissions ambition level. Three design alternatives are investigated by downgrading the building insulation level to the values recommended by the currently enforced Norwegian building code, the byggteknisk forskrift TEK17. A sensitivity analysis of the variation of the installed area of the photovoltaic panels is performed to evaluate if smaller areas give better cost performances. Net present values are calculated by using three scenarios of future increase of electricity price for a time horizon of 20 years. Results show that business as usual solutions give higher net present values. Optimized areas of the photovoltaic panels further increase the net present values of the business as usual solutions in the highest electricity price scenario. The zero-emission ambition level shows a higher net present value than that of the business as usual solutions for a time horizon of at least 36 years.