Photovoltaic Electricity Production Research Articles

Future scenario generation and reduction methods for solar photovoltaic electricity production analysis

Abstract A morphing-clustering-based method of generation and reduction future scenario for solar photovoltaic electricity production analysis is studied. Present historical annual weather data are transformed into future scenarios and timeframes by a morphing method with a general circulation model. The Copula methodology is applied to model the forthcoming decade’s annual meteorological data and generate abundant intra-day hourly scenario samples. The comparative analysis of the photovoltaic power output variations between future and present in reduction typical scenarios is conducted by the K-means clustering method with appropriate clustering parameter optimization. The simulation results show that the annual mean variations in global horizontal radiation, dry bulb temperature, and wind speed are projected to increase by approximately from 20.1 to 36.5 W/m2, 1.6 to 2.3°C, and 0.1 to 0.6 m/s, respectively in the forthcoming scenario of shared socioeconomic pathways 2-4.5. It is seen that solar photovoltaic electricity production anticipates a positive increase from 2.5% to 17.9%.

Techno-economic analysis of an islanded energy system based on geothermal/biogas/wind/PV utilizing battery technologies: A case study of Woulde, Adamawa's region, Cameroon

The present paper performs a techno-economic and an environmental analysis of an islanded energy system based on Geothermal/Biogas/Wind/PV hybrid energy system using two battery technologies for electricity generation in the city of Woulde in Cameroon. The innovation of the present paper is threefold: (i) a geothermal plant was modeled, and coupled to various power sources and battery technologies; (ii) an environmental analysis of the hybrid system was performed; and (iii) a solar dual-axis tracker (DAT) was incorporated in the system. The study findings suggested that the integration of a DAT reduced the battery requirements. The results demonstrated that integrating the DAT in the architecture minimized the levelized cost of energy, i.e. from US$ 0.271/kWh to US$ 0.260/kWh for lead-acid (LA) batteries, and from US$ 0.269/kWh to US$ 0.256/kWh for lithium-ion (LI) batteries. It was revealed that the net present cost varied from US$ 61.3 million to US$ 58.9 million for LA batteries, and from US$ 61.0 million to US$ 58.0 million for LI batteries. For both energy storage technologies, the use of a DAT improved the photovoltaic electricity production (about 32.0 % more power). The solutions also revealed that the monthly electricity production of the biogas generator increased with the use of a DAT (about 227.74 % and 7.16 % more power with LA and LI batteries respectively). Concerning the monthly electricity production of the geothermal generator, it decreased with the use of a DAT (about 15.30 % and 7.96 % less power with LA and LI batteries respectively). In addition, the integration of a DAT in the hybrid system increased the emissions of Carbon dioxide and Carbon monoxide. The computation of the excess of electricity revealed a variation from 6,439.0 kWh/year (for fixed system) to 1,676.0 kWh/year (for the system incorporating a DAT) when the LA storage technology was used. For LI technology, it was shown that the excess of electricity increased from 657.0 kWh/year (for fixed system) to 2,420.0 kWh/year (for the system incorporating a DAT). It was also found no unmet load in the different architectures implemented, which simply indicated that the energy produced by the scenarios covered the electricity needs. It was also demonstrated that the electricity production was largely dominated by the geothermal plant for all the scenarios, followed by the PV panels, biogas, and wind turbine generators. It was also found that the wind turbine electricity generation was mainly recorded during the months of January, February, March, and December.

Confirmation of the power gain for solar photovoltaic systems in alpine areas and across scales

Introduction: High Alpine regions show a great potential for solar photovoltaic electricity production in winter due to the reflective properties of snow and the larger number of sun hours compared to lower urban and peri-urban regions. In countries with a pronounced deficit in domestic electricity production such as Switzerland, utility-scale projects of Alpine-PV power plants are now flourishing. The harsh environmental conditions and the complexity of the high-Alpine topography however challenge the conventional design practices. In this context, the main question the article addresses is the representation of test-scale measurement in the performances of Alpine-PV, utility-scale power plants.Methods: This article focuses on the comparison between long term tests and the first Alpine-PV utility-scale power plant in Switzerland.Results: The results show that the main performance indicators such as the Alpine-to-Midlands final yield ratio or the winter fraction, do scale. However, absolute final yield values are consistently lower at the utility scale.Discussion: The paper discusses the possible impacts of the complex Alpine topography as constraint for the design of the larger extent of utility-scale power plants as well as the influence of scale on the snow induced losses.

Experimental investigation of photovoltaic panel surface temperatures and electricity production in summer

Experimental investigation of photovoltaic panel surface temperatures and electricity production in summer

Achieving Decentralized, Electrified, and Decarbonized Ammonia Production.

The rapid reduction in the cost of renewable energy has motivated the transition from carbon-intensive chemical manufacturing to renewable, electrified, and decarbonized technologies. Although electrified chemical manufacturing technologies differ greatly, the feasibility of each electrified approach is largely related to the energy efficiency and capital cost of the system. Here, we examine the feasibility of ammonia production systems driven by wind and photovoltaic energy. We identify the optimal regions where wind and photovoltaic electricity production may be able to meet the local demand for ammonia-based fertilizers and set technology targets for electrified ammonia production. To compete with the methane-fed Haber-Bosch process, electrified ammonia production must reach energy efficiencies of above 20% for high natural gas prices and 70% for low natural gas prices. To account for growing concerns regarding access to water, geospatial optimization considers water stress caused by new ammonia facilities, and recommendations ensure that the identified regions do not experience an increase in water stress. Reducing water stress by 99% increases costs by only 1.4%. Furthermore, a movement toward a more decentralized ammonia supply chain driven by wind and photovoltaic electricity can reduce the transportation distance for ammonia by up to 76% while increasing production costs by 18%.

The Imperative of Establishing the Mediterranean–Dead Sea Channel: Meeting the Demands of Escalating PV Electricity Production

The current landscape of electricity generation in Israel is significantly influenced by a marked increase in solar power output, primarily from photovoltaic (PV) facilities and plants. The rapid growth of solar energy within Israel’s self-sustained energy grid presents challenges for maintaining frequency stability and voltage equilibrium, limiting feasible solar electricity generation to approximately 12–14%. To expand these limits, integrating electrical storage solutions becomes imperative. An optimal proposal, tailored to Israel’s geographic location, involves constructing a conduit linking the Mediterranean and the Dead Sea. This initiative would include the installation of reservoirs and hydroelectric stations along the descent to the Dead Sea. Implementing such hydroelectric stations can help mitigate the impacts on frequency and voltage stability caused by the fluctuating nature of solar electricity production. Additionally, it can facilitate peak consumption management in the evening through hydroelectric generation, capable of delivering up to 320–330 MW of electrical power even in initial project phases. Furthermore, this strategic conduit offers additional benefits, such as enhancing PV electricity generation potential to 25–30% without exacerbating frequency control issues, producing an average of (150–180) × 103 m3 of desalinated water daily, and counteracting the steady decline of the Dead Sea, which currently recedes by about 1 m annually. Moreover, there are ancillary benefits from extensive desert area landscaping and the establishment of recreational health centers and resorts. A thorough analysis is imperative to estimate the potential increase in solar electricity generation, considering the unpredictable nature of PV outcomes. Additionally, it is crucial to explore the feasibility of using the Dead Sea for brine discharge from electrical hydro-storage plants as a key aspect of this comprehensive evaluation.

Achieving Net Zero Carbon Performance in a French Apartment Building?

Containing global warming to 1.5 °C implies staying on a given carbon budget and therefore being able to design net zero carbon buildings by 2050. A case study corresponding to a French residential building is used to assess the feasibility of achieving this target. Starting from an actual construction built in 2016, various improvement measures are studied: lowering heating energy needs, implementing bio-sourced materials and renewable energy systems (geothermal heat pump, solar domestic hot water production, and photovoltaic electricity production). Dynamic thermal simulation is used to evaluate energy consumption and overheating risk in hot periods. Greenhouse gas emissions are quantified using a consequential life cycle assessment approach, considering that during a transition period, exporting electricity avoids impacts corresponding to marginal production on the grid. Avoided impacts decrease and become zero when the grid is ultimately “decarbonized”. From this point, the building should be net zero emissions, but there remain unavoidable emissions. Residual GhG (greenhouse gas) emissions account for 5.6 kgCO2 eq/m2 annually. The possibility of offsetting these emissions is investigated, considering sequestration in forests or vegetation systems. A net zero emission level can be achieved, but on a national level, it would require that the whole sequestration potential of forest growth be devoted to offset emissions of new construction. A circular economy for construction products and equipment and considering water use will be needed to further decrease environmental impacts.

Firm Photovoltaic Power Generation: Overview and Economic Outlook

Grid‐connected photovoltaic electricity production steadily grows at the margin of conventional power generation, but its management becomes more complex. To overcome this challenge, a transformation of variable renewable energy (VRE) resources into firm power generation is proposed. Drawing on insights from the International Energy Agency Photovoltaic Power System Task 16 case studies, it becomes evident that achieving nearly 100% VRE power grids that reliably meet demand year‐round can be economically viable through optimal VRE transformation. This transformation involves various traditional methods, e.g., storage, VRE blending, geographical dispersion, and load flexibility. However, overbuilding VRE capacity and controlled curtailment, acting as implicit energy storage, are now seen as essential prerequisites for this transformation. Nevertheless, aligning this vision with the current market rules poses a dilemma as it doesn't necessarily align with VRE producers’ interests. This predicament calls for a reconsideration of VRE market regulations. Current designs based on marginal energy production signals do not suffice. Instead, it is advocated for market rules grounded in the capacity of firmly enabled VREs rather than their energy output. Ultimately, the economic model should harmonize with the variability of VRE resources, rather than forcing VRE resources to adapt to existing market structures.

Energy and Stochastic Economic Assessments of Photovoltaic Systems in the East Midlands

This study implements techno-economic evaluations of different photovoltaic (PV) systems in the East Midlands of the UK. Three application case studies, including an office building, a domestic building, and a poultry shed, are achieved. The building electricity consumption is obtained according to hourly automatic meter readings, and the PV electricity production is predicted based on the Engineering Equation Solver 8.4 software. Meanwhile, the 25-years’ complete economic profitability investigations of the three PV systems are conducted on the basis of the Monte Carlo method; the sensitivity analyses of payback period and net present value are also carried out by using the @RISK 8 software. Furthermore, the payback period and yearly savings are investigated and compared between the Smart Export Guarantee (SEG) and feed-in tariff (FiT) schemes. Technical investigation outcomes conclude that the three PV systems are able to satisfy electrical energy requirements in summer, and the additional electricity could be exported to the grid in this period. In winter, however, the systems have less electricity output resulting in power shortage and input from the grid. Economic study results exhibit that the net present values of the office building, domestic building, and poultry shed are £9108.4, £1717.91, and £7275.86, respectively, corresponding to the payback periods of 6.15 years, 9.12 years, and 9.41 years. This implies that there is an acceptable payback period (<10 years) for the PV system installation; meanwhile, the FiT scheme has the shorter payback period compared with the SGE scheme.

Intraseasonal and synoptic modulation of diurnal surface solar radiation over Reunion island in the South-West Indian Ocean

Understanding the space-time variability of Surface Solar Radiation (SSR) is mandatory for the prediction and, eventually, the skillful forecasting of photovoltaic energy production. This paper addresses the modulation of local-scale SSR over Reunion, a tropical island in the South-West Indian Ocean, by the leading modes of climate variability influencing both regional-scale and local-scale atmospheric convection and its associated cloud cover. Analyses focus on synoptic (tropical cyclones [TCs], synoptic convective regimes, including Tropical-Temperate Troughs [TTTs]) and intraseasonal (Madden-Julian Oscillation [MJO]) timescales. The SSR intra-daily variability is first assessed by a diurnal classification of SARAH-E satellite SSR data, and it is then related to the climate conditions mentioned above. SSR anomalies are found larger (smaller) on the windward (leeward) side of Reunion and in the summer (winter) season. The island-scale “cloudy” conditions can typically last 1 or 2 days. Nearby TCs can strongly reduce SSR by up to 50% on average, depending on their distances from Reunion, their sizes, and particularly, their longitudinal positions, which is observed for the first time. Nearby TCs are associated with significant negative SSR anomaly when located west of Reunion but with less significant or even positive anomaly when located east of the island. Synoptic convective regimes (the intraseasonal MJO) have a relatively weaker impact on SSR, with a value up to 13% (5%) of the mean value. Potential interactions between these SSR modulators are also investigated to understand better and eventually predict the mechanisms likely to modulate SSR (and thus photovoltaic electricity production) at sub-seasonal timescales.

Experimental and numerical analysis of a CO2 dual-source heat pump with PVT evaporators for residential heating applications

Multi-source energy systems are a promising solution to lower the environmental impact of the heating and cooling sector and enhance the exploitation of renewable energy sources. In this context, dual-source solar-assisted heat pumps exploit solar energy and air as the low-temperature heat sources. However, the efficiency of solar-based systems is strictly related to weather conditions, location, and time. Therefore, there is a need for accurate models to be used in dynamic simulations of these systems and perform detailed performance analyses and study the involved energy flows.This paper presents an experimental and numerical investigation of a direct-expansion solar-assisted heat pump (DX-SAHP) operating with CO2 as the refrigerant. The heat pump prototype can work with an air-finned coil heat exchanger or photovoltaic-thermal (PVT) solar collectors as the evaporator. The solar-mode configuration allows the exploitation of the heat from solar radiation to evaporate the refrigerant and to improve the photovoltaic electricity production due to the cooling of the cells up to 8%.A numerical heat pump model, integrated with novel gas-cooler and PVT collectors models, has been developed and implemented as a TRNSYS type for dynamic simulations of the system. The model has been validated with continuous measurements during the heat pump operation in solar and air modes. The proposed model can be used for performing seasonal simulations of a heat pump operating with a transcritical CO2 cycle. Moreover, the outcomes of the analysis show how the configuration of a CO2 heat pump with a direct-expansion air-finned coil heat exchanger or PVT can be used to enhance the performance of the heat pump and increase the electrical efficiency of the photovoltaic cells.

A user-friendly and accurate machine learning tool for the evaluation of the worldwide yearly photovoltaic electricity production

While traditional methods for modelling the thermal and electrical behaviour of photovoltaic (PV) modules rely on analytical and empirical techniques, machine learning is gaining interest as a way to reduce the time, expertise, and tools required by designers or experts while maintaining high accuracy and reliability. This research presents a data-driven machine learning tool based on artificial neural networks (ANNs) that can forecast yearly PV electricity directly at the optimal PV inclination angle without geographic restrictions and is valid for a wide range of electrical characteristics of PV modules. Additionally, empirical correlations were developed to easily determine the optimal PV inclination angle worldwide. The ANN algorithm, developed in Matlab, systematically and quantitatively summarizes the behaviour of eight PV modules in 48 worldwide climatic conditions. The algorithm’s applicability and robustness were proven by considering two different PV modules in the same 48 locations. Yearly climatic variables and electrical/thermal PV module parameters serve as input training data. The yearly PV electricity is derived using dynamic simulations in the TRNSYS environment, which is a simulation program primarily and extensively used in the fields of renewable energy engineering and building simulation for passive as well as active solar design. Multiple performance metrics validate that the ANN-based machine learning tool demonstrates high reliability and accuracy in the PV energy production forecasting for all weather conditions and PV module characteristics. In particular, by using 20 neurons, the highest value of R-square of 0.9797 and the lowest values of the root mean square error and coefficient of variance of 14.67 kWh and 3.8%, respectively, were obtained in the training phase. This high accuracy was confirmed in the ANN validation phase considering other PV modules. An R-square of 0.9218 and values of the root mean square error and coefficient of variance of 31.95 kWh and 7.8%, respectively, were obtained.The results demonstrate the algorithm’s vast potential to enhance the worldwide diffusion and economic growth of solar energy, aligned with the seventh sustainable development goal.

A correct perspective for hydrogen from engineered diagenesis

Wind and solar photovoltaic electricity production have already reached very low levels of levelized cost of energy (LCOE). Electrolyzers have already reached high efficiencies which are further improving, while costs are dramatically reducing. They are commercial products. Green hydrogen (H2) is the product of excess wind and solar electricity, specifically electricity that will be otherwise wasted, without the huge energy storage needed presently almost completely missing. By growing the installed capacity of wind and solar power plants, there will be a non-dispatchable production by wind and solar more often in excess, but sometimes also in defect, of the grid demand, in presence of limited energy storage. H2 is one of the key energy storage technologies needed to ensure grid stability. Production of H2 above what is needed to stabilize the grid significantly helps in applications such as land, and sea but especially air transport where the storage of energy onboard in a fuel is preferable to the storage of energy as electricity into a battery. The engineered diagenesis for H2 is unlikely better than green hH2. Apart from being a nice idea to be proven workable, with a technology readiness level (TRL) presently of zero, and thus impossible to be objectively compared with commercial products, the engineered diagenesis for H2, even if possible, also does not help with non-dispatchable renewable energy production. The concept may also have negative environmental aspects similar to fracking which have not been considered yet, and also bear huge economic costs in addition to environmental. Here we review the pros and cons of this novel technology, which once proven workable, which is not the case yet, should be considered as a possible way to complement rather than replace green H2 production.

Dye-Sensitized Titanium Dioxide Photocatalysis – a Novel Solution for Personal Air Filtration

Ambient air pollution is attributed to 4.2 million deaths annually and accounts for nearly 30% of the global top 6 leading causes of death. According to the World Health Organization, 99% of the world population lives in areas with dangerously high levels of pollutants, most being in low-income countries. Although current solutions exist, none are both cheap and efficient at filtering out Particulate Matter (PM) and Volatile Organic Compounds (VOCs) outdoors. Photocatalysis, a process known to occur in photovoltaic semiconductors, has proven to degrade pollutants, but only under Ultraviolet Light, which accounts for just 3-5% of sunlight. In this experiment, the dye-sensitization method was tested to increase the filtration efficiency of a semiconductor, Titanium Dioxide (TiO2), under visible light. The dyes tested were Flavonoids, which are natural antioxidants found in fruits that have also been previously used to improve the efficiency of photovoltaic electricity production, from Blackberry, Blueberry, Raspberry and Parsley. Each filter was coated in a solution of Dye-sensitized TiO2. The filters’ efficiencies were then evaluated by passing contaminated air through each filter into a testing chamber where the resulting quality of the air was analyzed with an air quality monitor. The Parsley-TiO2 filter was the most efficient, removing nearly all VOCs, PM2.5, PM10 and PM1, and the estimated cost to create the filter was approximately $2. This filter could save millions of lives, due to its low cost of production, and could potentially be applied in impoverished areas of polluted cities like Beijing and New Delhi.

Temporal resolution of photovoltaic electricity production with school energy consumption: a London primary school case study

In line with the UK goal to reach carbon neutrality by 2050, the combination of photovoltaic electricity and the electrification of heating systems is considered an effective way to reduce greenhouse gas emissions, while 88% of schools in the UK are gas-heated. This paper analyses the electricity consumption at a 15 and 30 min resolution of different scenarios for the retrofitting of a primary school in London, UK, with an electrified heating system and the electricity production of different PV installations. High temporal resolution allows consideration of economic balances, in light of rising costs of energy in the UK in 2022, and the possibilities PV can have on decarbonizing heating systems in UK primary schools. Practical application - The high temporal resolution allows to provide a project economic balance with close to reality figures. It also allows schools to rely on energy produced on site with less price fluctuation and to have the educational benefit of the PV installation. The high temporal resolution also provides data on what types of activities are the most energy consuming and can inform behaviour/time schedules changes.

Optimal site selection for establishing solar power plant based on solar radiation using GIS

Although many nations employ solar energy as a backup energy source, not every site is equally conducive to the production of solar power. This is caused by the unequal dispersion of solar energy as well as a number of environmental conditions. The framework incorporates a number of Geographic Information Systems (GIS) features, including model builder and area classification. The framework used to derive the five sub-criteria weights determines the ideal locations for plant in the area based on the quantum of potential photovoltaic electricity production (PVOUT) that could possibly produce from Slope, exposure to sunlight, near to highways and closeness to a residential area. Finding the best locations for solar plant side identification in the “Anantapur” district using multicriteria decision analysis (MCDA).

Life cycle assessment of photovoltaic electricity production by mono-crystalline solar systems: a case study in Canada.

Photovoltaic (PV) system is widely recognized as one of the cleanest technologies for electricity production, which transforms solar energy into electrical energy. However, there are considerable amounts of emissions during its life cycle. In this study, life cycle assessment (LCA) was used to evaluate the environmental and human health impacts of PV electricity production in Canada. The PV potential varies considerably among the provinces, with higher values in Manitoba (MB), Saskatchewan (SK), Alberta (AB), and southern Ontario (ON). A grid-connected slanted-roof mono-crystalline silicon (mono-Si) PV system with a capacity of 3 kWp (the peak power of the system in kilowatts) in Toronto, Ontario, was considered as the case study system. Ten impact categories were considered including (1) acidification, (2) carcinogenic, (3) ecotoxicity, (4) eutrophication, (5) fossil fuel depletion, (6) global warming, (7) non-carcinogenic, (8) ozone depletion, (9) respiratory effects, and (10) smog. Among the four components of the PV system, i.e., mono-Si panel, mounting system, inverter, and electric installation, the mono-Si panel production was the highest contributor in seven out of ten impact categories, including acidification (68%), eutrophication (60%), fossil fuel depletion (81%), global warming (77%), ozone depletion (88%), respiratory effects (74%), and smog (70%). For the other three processes, the electric installation contributed most to ecotoxicity at 58%, followed by the mounting system in the carcinogenic category (29%), and the inverter in the non-carcinogenic category (31%). By normalizing the impacts based on the reference scores in Canada, it was found that the ecotoxicity and carcinogenic categories had dominant contributions to the overall impact by 53% and 42%, respectively. The global warming potential impact was estimated as 79 gr CO2 eq /kWh, which is close to the mean value of 79.5 gr CO2 eq /kWh, reported in the literature. The sensitivity analysis indicated that a 10% increase in the panel and mounting system area will increase the ozone depletion and carcinogenic categories by 8.1% and 2.8%, respectively.

The Study of Architectural Geometry and Shape in the Energy Balance of Glazed Roofs

Triggered by the global call for low-carbon design, the idea of “productivity for a building envelope” has permeated the role of building to produce alternative (renewable) energy alongside weather and solar protection, and the authors hypothesized that the geometrical shape and configuration of a roof is a significant contributor to low-carbon design. Bibliometric networks such as VOS Viewer revealed a gap among most research works which have yet to discover “roof geometry” as a design determinant for photovoltaic electricity production. In this study, the authors tested their hypothesis by studying and comparing the balancing of solar energy harvesting and energy consumption and saving due to the uncontrolled admittance of daylight, glare, and solar heat gain of different geometric shapes of roofs in the subtropical climate. Twelve recent signature public buildings in Shenzhen city are studied for the tendency of architectural geometry of roof shapes. These roof shapes are then simplified and classified into three distinct geometries—square, pyramidal, and curvilinear—for comparative study of the best-performing low-carbon architectural geometry. The results of the simulations using the “Daysim” and “Energy-Plus” models show the desirability of an optimized design. The preliminary findings shed light on the preferred use of specific roof shapes for enhanced PV output. The curvilinear geometry has been shown to be the most effective of all. This study targeted the roof potentials by multiple criteria and a parametric evaluative protocol for building design known as the energy balance paradigm. This research paves the way in (1) changing the impression of the roof as a mere weather protector to that of a “productive roof” in response to the global call for carbon neutrality, (2) raising the awareness of architectural geometry (i.e., the building envelope), focusing on the roof form and its shape in response to low-carbon design requirements, and (3) identifying multiple criteria for the low-carbon design of architectural roof geometry.

Energy Analysis of a NZEB Office Building with Rooftop PV Installation: Exploitation of the Employees’ Electric Vehicles Battery Storage

Near zero energy buildings are increasing worldwide, exploiting low-carbon technologies in heating and electricity self-production. Commercial buildings are increasingly considered as candidates for the installation of smart micro-grids, which may profit from the added storage capacity of the batteries of employees electric vehicles, stationed during daytime in their charging lots. Smart exploitation of the interaction of these electricity sources and sinks may prove essential to address the complex electricity network demand patterns in today’s fast changing energy mixture. The interaction of an efficient office building’s energy system with a big rooftop photovoltaic installation and the aggregate storage capacity of 40 electric cars that are connected in the building’s charging lots is studied by means of transient simulation in TRNSYS environment. The 18-zone building’s heating, ventilation, and air conditioning system, the cars’ batteries, and photovoltaic systems’ interactions are analyzed on a monthly, seasonal, and hourly basis, against the respective demand curves of the Greek network. The results suggest that the specific system’s size may profitably support the operation of a smart micro-grid. The total annual electricity consumption of the building is computed to reach 112,000 kWh, or 20 kWh/m2y. The annual electricity needs of the 40 electric cars, amounting to 101,000 kWh, can be fully met with 30% of the photovoltaic electricity production. Thus, the building becomes a net exporter of electricity to the network, with maximum exported electricity occurring daily between 12:00 and 14:00, which is favorable to meeting the demand curve. Thus, the establishment of smart micro-grids in commercial buildings with large rooftop photovoltaic panels’ capacity and a significant number of electric cars in the employees’ car fleet is quite effective in this direction.

The role of demand energy profile on the optimum layout of photovoltaic system in commercial buildings

Solar photovoltaic (PV) is a promising and effective energy generation resource to produce on-site electricity that covers part of buildings’ demand on urban scales. Design optimization is identified as a proper approach to improve PV systems' techno-economic feasibility and tackle the challenges of exchanging electricity with the grid. This study uses a multi-objective optimization approach to find the optimum PV system design that generates electricity based on the aggregated demand pattern of commercial buildigs. The goal is to improve the correlation between the PV electricity production and demand patterns by optimizing the PV panels’ range of orientations and the number of panels on each orientation. The PV system is optimized to in a way to maximize self-consumption (SC) and self-sufficiency (SS), and minimize payback period (PB) and load variance over the grid. The optimization objectives are examined in four different scenarios for commercial buildings located in the downtown Los Angeles, California. The results show that the demand pattern of commercial neighborhoods is somehow flat and has no spikes. Thus, the production pattern of optimum PV systems will be normally distributed around noon, with slightly higher production in the afternoon. While the system size is dependent on the objectives considered in the optimization, considering multiple objectives simultaneously leads to beneficial and reasonable results. The SS values obtained in all optimization scenarios range between 4.4 and 44.1 %, the SC ranges between 84.9 and 100 %, the PB is between 8.55 and 14.7 years, and the RMSD ranges between 1652 and 2418 KW/h. In addition to PV system optimization, the results indicate the importance of finding the optimum energy storage system for a better match between the demand and supply profiles.