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The installation of photovoltaic (PV) systems has risen significantly as the global demand for renewable energy increases. Inequitable photovoltaic (PV) adoption exacerbates the energy burden on non-adopting households. Intervention in the PV deployment process is currently the dominant concept to address this challenge. Subsidizing low-income households to scale up PV adoption lacks sustainability, and curbing PV scale by reducing adopters' benefits from PV has been shown to solidify this inequity. This study attempts to provide new ideas for solutions to eliminate the consequences of inequitable PV adoption without interfering with the scale of PV. We build a sequential game between a profit-maximizing power plant and a profit-maximizing electricity retailer to describe the optimal decisions of the relevant decision-makers in the face of unfair PV adoption. In addition, we construct an evolutionary game model of the electricity market to model the causes of and responses to long-term PV inequity. Our results show that PV results in a decrease in the wholesale price of electricity. However, the electricity retailer may not pass on the price decrease to households, which in turn leads to an increase in the cost of electricity for households that do not adopt PV, which is a new energy equity problem (i.e., price inequity). Subsequently, eliminating time-of-use tariff strategies for PV households and subsidizing the retailer in the early stages of PV deployment could decrease price inequity. In addition, we find that excessive adjustment decisions by the boundedly rational power plant and retailer can lead to electricity market instability and exacerbate the difficulty of decreasing long-run inequality while reducing their focus on the direction of profitability can help to eliminate long-run inequality. • Inequitable PV adoption creates a new energy inequity: price inequity. • PV adoption increases electricity costs for non-adopting households. • Energy inequity can be mitigated without hindering PV deployment. • Bounded rationality in power markets hinders long-term inequity reduction. [ABSTRACT FROM AUTHOR]

Thermal photovoltaic systems (PVT) absorb the sun's energy and convert it into electricity. Increasing the solar cell temperature reduces its efficiency. In the present research, the porous medium and impinging air jet is used for PV cooling to lessen the solar cell temperature. Different arrangements of impinging jet systems (single and multiple) have been considered to evaluate the electrical efficiency of PV. The effects of Re , solar radiation intensity, porosity coefficient, Darcy number, dimensionless porous layer thickness, jet and injection location, jet velocity and angle on PVT efficiency have been inspected. The results show that the porous medium has a positive effect on reducing the PV temperature and increasing the electrical efficiency of PV by increasing the effective thermal conductivity coefficient and reducing the convection resistance. The effect of the characteristics of the porous medium on the electrical efficiency of PV is influenced by porous layer thickness. Porous medium with variable porosity can improve the electrical efficiency of PV up to 6 % compared to uniform porosity. Impingement jet in single and multiple arrangement between 3 and 26 % to improve the electrical efficiency of PV. The impinging jet has a high potential in removing heat from PV. In the integration of PV with multiple jets, more efficiency can be obtained than the single jet mode. Also, by using the data of this survey and the adaptive Neuro-fuzzy inference system (ANFIS) model and Gaussian process regression (GPR) from machine learning algorithms, the electrical efficiency has been estimated and the GPR method has been able to approximate the electrical efficiency well. • The combination of jets and porous foam gradient resulted in an improvement of electrical efficiency and thermal efficiency. • Impingement jet in both single and multiple arrangements improved PVT efficiency • Impingement jet has more uniform temperature distribution on the PV surface • Machine learning algorithms such as ANFIS and GPR were used to estimate electrical efficiency • Using data from this survey and the GPR method provided good approximations of electrical efficiency. [ABSTRACT FROM AUTHOR]

In this work, the Design and Operation of Integrated Technologies (DO-IT) framework is developed, a comprehensive tool to support short- and long-term technology investment and operation decisions for integrated energy generation, conversion and storage technologies in buildings. The novelty of this framework lies in two key aspects: firstly, it integrates essential open-source modelling tools covering energy end uses in buildings, technology performance and cost, and energy system design optimisation into a unified and easily-reproducible framework. Secondly, it introduces a novel optimisation tool with a concise and generic mathematical formulation capable of modelling multi-energy vector systems, capturing interdependencies between different energy vectors and technologies. The model formulation, which captures both short- and long-term energy storage, facilitates the identification of smart design and operation strategies with low computational cost. Different building energy demand and price scenarios are investigated and the economic and energy benefits of using a holistic multi-energy-vector approach are quantified. Technology combinations under consideration include: (i) a photovoltaic-electric heat pump-battery system, (ii) a photovoltaic-electric heat pump-battery-hot water cylinder system, (iii) a photovoltaic-electrolyser‑hydrogen storage-fuel cell system, and (iv) a system with all above technology options. Using a university building as a case study, it is shown that the smart integration of electricity, heating, cooling and hydrogen generation and storage technologies results in a total system cost which is >25% lower than the scenario of only importing grid electricity and using a fuel oil boiler. The battery mitigates intra-day fluctuations in electricity demand, and the hot-water cylinder allows for efficiently managing heat demand with a small heat pump. In order to avoid PV curtailment, excess PV-generated electricity can also be stored in the form of green hydrogen, providing a long-term energy storage solution spanning days, weeks, or even seasons. Results are useful for end-users, investment decision makers and energy policy makers when selecting building-integrated low-carbon technologies and relevant policies. • Building demand, technology and energy system optimisation models are integrated. • The framework uses open-source tools to model complex multi-energy-vector systems. • The novel formulation is generic while capturing both short- and long-term energy storage. • Smart integration of electrical, thermal and hydrogen systems leads to minimum cost. • Demand patterns and resource prices greatly impact PV, heat pump and hydrogen synergies. [ABSTRACT FROM AUTHOR]

Solar photovoltaic capacities have experienced remarkable gains worldwide. The accelerated deployment of photovoltaic (PV) systems has emphasized the need for methods and tools that can assist in planning and investment decisions of utility-scale photovoltaic systems to ensure a sustainable energy transition. This study bridges the gap between research and current solar PV project evaluation practices by proposing a geographic information system (GIS)-based approach for analyzing land eligibility and performing techno-economic assessments of utility-scale photovoltaic systems. To tackle the issue of country-specific cost elements, the model incorporates a levelized cost of electricity (LCOE) breakdown often used by governmental and intergovernmental organizations. The proposed GIS-based model can assist in mapping the distribution of eligible land for utility-scale solar systems while considering exclusion constraints, estimating PV capacity and generation potentials, as well as determining the average LCOE of utility-scale solar photovoltaic systems at a spatial resolution of 100 m. The GIS-based approach is demonstrated through the case study of Poland. The model estimates that 3.61% of the total area of Poland is suitable for the installation of utility-scale solar PV systems. Implementing PV installations in these areas would result in solar capacities ranging from 394.64 to 563.77 GW. Furthermore, the findings of the case study indicate that the LCOE would range from €0.043/kWh to €0.049/kWh, with a national average of €0.045/kWh. The proposed approach can be utilized to develop national and regional strategies focused on large-scale PV installations, facilitating the attainment of renewable energy goals. The study fills a significant gap in the literature as it provides a GIS-based tool for planning the sustainable development of utility-scale PV systems at the regional scale. In addition, it is the first to comprehensively assess the capacity and generation potential of utility-scale solar photovoltaics in Poland at the NUTS-2 level. • A GIS-based model for utility-scale PV system planning and investment. • The approach accounts for country-specific cost elements. • The GIS-based approach is demonstrated through the case study of Poland. • 3.61% of available land is suitable for utility-scale solar PV systems. • The LCOE ranges from €0.043/kWh to €0.049/kWh. [ABSTRACT FROM AUTHOR]

• A test-bench for PV-CHP hybrid system has been build. • Input profiles (PV and load) are emulated with accuracies between 0.1% and 14%. • The CHP and gas burner should have modulated power supply for higher efficiency. • Hardware and metering generates additional deviations from forecast schedules. • A battery needs a faster control added to the MPC for higher accuracy. In order to reduce the global warming to less than two degrees, a large increase in renewable energy resources like photovoltaic systems is necessary. A business case based on feed-in tariffs does not exist in every countries and self-consumption is limited due to the unsteady nature of solar radiation on earth. A combination with other systems such as batteries, heat-pumps or even combined heat and power plants can enhance the use of generated power by photovoltaic systems, particularly in private households and small businesses. Rule-based controllers and optimization algorithms (model predictive control) can both realise the efficient operation of a photovoltaic system in combination with storage systems and a combined heat and power plant. However, different controllers and energy management systems have hitherto only been compared theoretically. A comparison of such controllers in a real, controllable hardware environment has not yet been carried out. In this study, a test-bench is introduced to test different control algorithms for photovoltaic systems in combination with storage systems and a micro- combined heat and power plant. The operation has been tested for a one day period. Key performance parameters have been derived and compared for a rule-based control, an optimized control and simulation results including a forecast. The results show that the operational costs can be reduced by 7.3% for the chosen test-period using the optimized algorithm in the laboratory compared to the same system with a rule-based control. The results also indicate that even under perfect forecast conditions the hardware, metering and energy management cause latencies and inaccuracies leading to deviations, which are not accounted for in simulations. Hence, the accuracy of the forecast methods need not be higher than the deviations introduced by the hardware. These deviations often lead to unwanted charging and discharging events of the battery. A faster way of processing data and a second order or low level control is needed for short term reaction and higher efficiency. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Method is proposed to evaluate batteries combining applications for consumers. • Electricity demand input data have 1 min resolution across 100 dwellings. • The lithium-ion battery model includes ageing throughout the battery lifetime. • Couple of storage applications are classified as complementary or substitutive. • Results show the importance of the electricity demand for combining applications. Abstract Batteries are expected to play an important role in the transition to decarbonised energy systems by enabling the further penetration of renewable energy technologies while assuring grid stability. However, their hitherto high capital costs is a key barrier for their further deployment. In order to improve their economic viability, batteries could provide several applications offering revenues. The techno-economic evaluation of batteries simultaneously serving several applications has proven to be challenging due to the trade-offs between energy and power applications. Focusing on residential batteries, we develop an optimisation method for designing optimal value propositions and we test it for four different applications both individually and jointly: PV self-consumption, demand load-shifting, avoidance of PV curtailment and demand peak shaving. Our results show that the combination of all applications currently helps batteries to get closer to profitability, from a net present value (NPV) per unit of capital expenditure (CAPEX) of −0.63 ± 0.04 for PV self-consumption only to −0.36 ± 0.10, with the combination of demand peak-shaving and PV self-consumption adding most value (0.21 ± 0.04). We also find that the annual household's electricity consumption determines the value of energy storage applications. The proposed method allow us to classify storage applications as complementary and substitutive depending on whether their combined application increases their economic attractiveness or not. These results thus offer valuable insight for stakeholders interested in the deployment of energy storage in combination with energy efficiency, heat pumps and electric vehicles such as consumers, utility companies and policy makers. [ABSTRACT FROM AUTHOR]

Highlights • Thermal and electrical performances were measured using indoor test cell for crystalline silicon based PV-vacuum glazing. • Maximum PV cell temperature was achieved 97 °C under 1 sun exposure (1000 W/m2) • Overall heat transfer coefficient was 0.8 W/m2 K for this glazing. • Solar factor was calculated for this PV-vacuum glazing. Abstract Combined semi-transparent PV-vacuum glazing provides low overall heat transfer coefficient, reduces solar heat gain, generates clean electricity and admits comfortable daylight. In this work, thermal and electrical performances of a multicrystalline silicon based PV-vacuum glazing were characterised using indoor test cell. For this particular combined system, PV covered 32% of the glazing area. Two different combinations of PV-vacuum glazing systems were manufactured where for the first case vacuum glazing faced test cell external environment (VPS) and for the second case vacuum glazing faced test cell internal environment (SPV). SPV type was found to have superior performance as PV cell achieved lower temperature than VPS type after 125 min exposure under 1000 W/m2 constant intensity from a simulator. For this type PV-vacuum glazing, overall heat transfer coefficient (U -value) was 0.8 W/m2 K and the solar factor was 0.42. U -value of this PV-vacuum glazing was 66% lower and the solar factor was 46% lower than PV double-glazing. Close power drop from PV due to elevated temperature was observed for both PV-double and PV-vacuum glazing. [ABSTRACT FROM AUTHOR]

This paper presents a study into the utilization of Gaussian Processes (GPs) for probabilistic forecasting of residential electricity consumption, photovoltaic (PV) power generation and net demand of a single household. The covariance function that encodes prior belief on the general shape of the time series plays a vital role in the performance of GPs and a common choice is the squared exponential (SE), although it has been argued that the SE is likely suboptimal for physical processes. Therefore, we thoroughly test various (combinations of) covariance functions. Furthermore, in order bypass the substantial learning and inference time accompanied with GPs, we investigate the potential of dynamically updating the hyperparameters using a moving training window and assess the consequences on predictive accuracy. We show that the dynamic GP produces sharper prediction intervals (PIs) than the static GP with significant lower computational burden, but at the cost of the ability to capture sharp peaks. In addition, we examine the difference in accuracy between a direct and indirect forecasting strategy in case of net demand forecasting and show that the latter is prone to producing wider PIs with higher coverage probability. [ABSTRACT FROM AUTHOR]

Solar energy is an important measure to reduce fossil fuel use and carbon emissions from the energy supply in industries requiring heat below 150 °C. A robust methodology was developed to compare two solar conversion technologies (solar thermal and photovoltaics via resistance heating) to determine which provided lower cost heat, highly flexible for various plant sizes, investments, currencies, locations, and process temperatures. At current PV investments, solar thermal plants must be installed turn-key below 400 €/m 2 ap in northern European climates and 500 €/m 2 ap in southern to remain economically competitive. Photovoltaic heat is already the lower cost heat provider for many applications in northern latitudes above 100 °C. In future PV cost scenarios, solar thermal must reduce investments below 250 €/m 2 ap to remain competitive in Europe and 400 €/m 2 ap in higher solar resource regions. When opportunity costs are considered, photovoltaics are better utilized to offset local electrical, not thermal, demand. Despite this fact, future efforts must be given to solar thermal cost reduction in order to remain competitive against all other renewable heat producers. [ABSTRACT FROM AUTHOR]

A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system's reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. The methodology developed can be used to extend the analysis to other locations. • Utility customer reliability is studied in various system and geospatial conditions • Monte Carlo simulation to assess the reliability of residential systems with DER • Analysis of residential systems in the top 100 populous counties of the USA • Sensitivity of indices to system parameters and geospatial variables are studied [ABSTRACT FROM AUTHOR]

• Degradation rates of installed PV modules in Germany are analyzed. • PV modules which were more than 15 years old were studied. • Method of evaluation decreasing productivity of PV after years. • Power degradations in the analysed installations was 0.12%/year for one installation and 0.2%/year for second-one installation. In the last twenty years, photovoltaic installations have become a popular form of renewable energy sources, both in Europe and around the world. One of the European pioneers in this field was Germany. Photovoltaic installations are inevitably associated with a decrease in productivity during operation years based on power degradation of photovoltaic cells. This article analyzes the decrease in energy productivity of installations over 16 years using the example of two rooftop photovoltaic installations and proposes a modified methodology for calculating the decreasing effect. The tested installations are located in the south-west of Germany, in the town of Sinsheim. The first installation, I-1, has a capacity of 37.8 kWp (Suntech panels, 150 Wp), and the second one, I-2, has a capacity of 18.48 kWp (Suntech panels, 165 Wp). In the first two years, the actual productivity calculated from the theoretical productivity estimated for the installation (modified Performance Ratio value) was 95.8% for I-1 and 96.8% for I-2. However, in the years 2020–2021 (the last two years of the installation's operation), the actual productivity calculated from the theoretical productivity estimated for the installation was 93.9% for I-1 and 93.8% for I-2. The reported yearly power degradation rate in the analyzed installations was 0.11%/year for I-1 and 0.2%/year for I-2, which is lower than in the literature examples. [ABSTRACT FROM AUTHOR]

We established an entitative photovoltaic (PV) module for measuring the electric power in this study. The generating electric efficiency was calculated according to the electric power. Using the heat transfer mechanism generated during the operation of PV module, thermal energy conservation law and lumped capacitance method were combined with Matlab/Simulink to establish the dynamic model of PV module. The ambient temperature, wind speed, and solar radiation of the environmental factors were the inputs used for predicting the time-varying temperature of different layers inside the module. Based on the solar cell temperature, electric power and electric efficiency could be obtained. The electric power of solar cell declined as the solar cell operating temperature increased. In this study, we used entity module to validate the accuracy of the model. The environmental factors of mounting site were applied to design the backsheet material and to improve the output performance of entity solar module. The PV dynamic model and entity validation showed that electric power and electric efficiency errors are smaller than 1.3%. The PV dynamic model can accurately predict the output performance according to the environmental factors of the site. The PV backsheet was made of glass with higher thermal conductivity to replace traditional tedlar-polyester-tedlar (TPT). Electric power and electric efficiency are increased by 2.353%. The output performance of solar module was improved effectively. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method to improve the efficiency of the perturbation and observation (P&O) maximum power point tracking (MPPT) algorithm. The proposed method can improve the dynamic tracking response of P&O, reduce the steady state oscillation of P&O and eliminate the possibility of the algorithm to lose its tracking direction. To estimate the optimal duty ratio of the boost converter at the maximum power point, an optimal duty ratio estimation algorithm based on a four-parameter model of a photovoltaic (PV) module is proposed. Furthermore, the ratio of the power-voltage curve slope to the current in the PV module is defined as K pvi . Because K pvi has a small variation range at different irradiations, a piecewise linear function dependent on K pvi is developed to generate the optimal step size of P&O. Finally, K pvi is utilized to avoid drift phenomenon in case of fast change in irradiation. To prove its effectiveness, the proposed P&O algorithm is compared with conventional P&O and adaptive P&O using the sudden step change test, Ropp test, and four one-day irradiation and temperature profile tests in Simulink. The proposed algorithm is also benchmarked by MPPT efficiency ( η MPPT ) calculation. The results show that the η MPPT of the proposed P&O is increased by 0.65% in one-day irradiation and temperature profile with light cloud test. In addition, the η MPPT of the proposed P&O can be further improved up to 1.27% and 1.24% in one-day profile with heavy cloud test and one-day profile with dark cloud test, respectively. Moreover, it needs neither additional sensors nor expensive microcontrollers. [ABSTRACT FROM AUTHOR]

Heating electrification powered by distributed renewable energy generation is considered among potential solutions towards mitigation of greenhouse gas emissions. Roadmaps propose a wide deployment of heat pumps and photovoltaics in the residential sector. Since current distribution grids are not designed to accommodate these loads, potential benefits of such policies might be compromised. However, in large-scale analyses, often grid constraints are neglected. On the other hand, grid impact of heat pumps and photovoltaics has been investigated without considering the influence of building characteristics. This paper aims to assess and quantify in a probabilistic way the impact of these technologies on the low-voltage distribution grid, as a function of building and district properties. The Monte Carlo approach is used to simulate an assortment of Belgian residential feeders, with varying size, cable type, heat pump and PV penetration rates, and buildings of different geometry and insulation quality. Modelica-based models simulate the dynamic behavior of both buildings and heating systems, as well as three-phase unbalanced loading of the network. Additionally, stochastic occupant behavior is taken into account. Analysis of neighborhood load profiles puts into perspective the importance of demand diversity in terms of building characteristics and load simultaneity, highlighting the crucial role of back-up electrical loads. It is shown that air-source heat pumps have a greater impact on the studied feeders than PV, in terms of loading and voltage magnitude. Furthermore, rural feeders are more prone to overloading and under-voltage problems than urban ones. For large rural feeders, cable overloading can be expected already from 30% heat pump penetration, depending on the cable, while voltage problems start usually at slightly higher percentages. Additionally, building characteristics show high correlations with the examined grid performance indicators, revealing promising potential for statistical modeling of the studied indicators. Further work will be directed to the assessment of meta-modeling techniques for this purpose. The presented models and methodology can easily incorporate other technologies or scenarios and could be used in support of policy making or network design. [ABSTRACT FROM AUTHOR]

With the increasing technological maturity and economies of scale for solar photovoltaic (PV) and electrical energy storage (EES), there is a potential for mass-scale deployment of both technologies in stand-alone and grid-connected power systems. The challenge arises in analyzing the economic projections on complex hybrid systems utilizing PV and EES. It is well known that PV power is of diurnal and stochastic nature, and surplus electrical energy is generally available in midday during high irradiance levels. EES does not produce energy as it is not a conventional generator source. Commonly, the cost of a generating asset or the power system is evaluated by using levelized cost of electricity (LCOE). In this paper, a new metric levelized cost of delivery (LCOD) is proposed to calculate the LCOE for the EES. A review on definitions in LCOE for PV hybrid energy systems is provided. Four years of solar irradiance data from Johannesburg and the national load data from Kenya are obtained for case studies. The proposed cost calculation methods are evaluated with two types of EES, namely Vanadium redox flow battery (VRB) and Lithium-ion (Li-ion) battery. It shows that the marginal LCOE and LCOD indices can be used to assist policymakers to consider the discount rate, the type of storage technology and sizing of components in a PV-EES hybrid system. [ABSTRACT FROM AUTHOR]

Integrated photovoltaic (PV) and agricultural greenhouses (PVGs) have seen a rapid expansion in recent years in China. However, declining Feed-in Tariffs and underutilization of PV greenhouses also cause public concern regarding their actual economic performance. In this study, we address the economic and social performance of five PVGs based on a case study. The conclusions show that PVGs could achieve a good economic performance. Their Annual Return on Investment (AROI) varies from about 9% to 20% with a discounted payback period of 4–8 years depending on the different crops produced in PV greenhouses. Furthermore, PVGs also bring considerable social benefits, such as providing new jobs, raising taxes and avoiding substantial CO 2 emissions. Sensitivity and uncertainty analysis reveals that crop price is the most sensitive influencing factor. The importance of the electricity feed-in tariff is much less than what we expected. This implies that PV agricultural companies should pay more attention to crop planting and that policy-makers should also shift the focus of incentives from PV power generation to agricultural crop production. [ABSTRACT FROM AUTHOR]

Despite impressive declines in average prices, there is wide dispersion in the prices of U.S. solar photovoltaic (PV) systems; prices span more than a factor of four. What are the characteristics of the systems with low-prices? Using detailed characteristics of 42,611 small-scale (<15 kW) PV systems installed in 15 U.S. states during 2013, we identify the most important factors that make a system likely to be low-priced (LP). Comparing LP and non-LP systems, we find statistically significant differences in nearly all characteristics for which we have data. Logit and probit model results robustly indicate that LP systems are associated with: markets with few active installers; experienced installers; customer ownership; large systems; retrofits; and thin-film, low-efficiency, and Chinese modules. We also find significant differences across states, with LP systems much more likely to occur in some states, such as Arizona, New Jersey, and New Mexico, and less likely in others, such as California. Our focus on the left tail of the price distribution provides implications for policy that are distinct from recent studies of mean prices. While those studies find that PV subsidies increase mean prices, we find that subsidies also generate LP systems. PV subsidies appear to simultaneously shift and broaden the price distribution. Much of this broadening occurs in a particular location, northern California. [ABSTRACT FROM AUTHOR]

Residential buildings are responsible for a substantial and steadily growing share of the global electricity consumption, approximately 30%. The ability to control the timing and magnitude of the aggregate electricity consumption of buildings is acquiring critical relevance. Buildings play a pivotal role in defining the shape and composition of the final electricity demand, and have an impact on the existing and projected electrical system infrastructure. This paper proposes distributed electrical storage using electrical batteries at the residential level, as an economical and technically feasible way to introduce a degree of responsiveness with the demand of residential buildings without compromising the comfort of users. The objective of the paper is to devise the operative principles governing the relation between the grid operator and a community of low exergy (lowEx) buildings, under the assumption that the grid operator is interested in controlling the form of the aggregate electricity consumption in that community. This paper presents a pricing policy aimed to stimulate a power-aware consumption, and consequently peak-shave the total electricity profile. The introduced pricing scheme separately addresses energy and power, and provides an incentive for buildings to invest in decentralized generation and storage technologies. The paper presents a methodology to determine the optimal amount of decentralized electrical storage and PV necessary to meet the objectives of the grid operator and allowing users to obtain a profit from the dynamic electricity tariff. A model is used to determine the optimal battery and PV investment from the perspective of the user. The analyses show that the introduced electricity tariff triggers an equilibrium, in which users invest between 20% and 25% of the total incurred cost in battery and PV. The PV and the battery input power were found to be mainly related to the objective of reducing the energy cost. On the other hand, the battery capacity and output power were found to be associated with the peak reduction objective. Users invest less than 10% of the total battery investment share in the battery input power. This fact indicates that contrary to a battery usage driven by the price volatility, which is proposed in many models, the battery is mainly used as power-to-energy buffer. Energy is slowly stored in the battery and rapidly released at critical peak hours. [ABSTRACT FROM AUTHOR]

• Linearized multi-objective robust optimization. • Mathematical modeling for decision-making in newly established electricity markets. • Improving the upper approximation method for quadratic functions. • In non-robust and robust planning, retailer costs are reduced by 5.57 % and 5.32 %, respectively. • After robust optimization, the power consumed by the electrolyzer decreased by 14.19 %. Using renewable energy sources (RES) and green hydrogen has increased dramatically as one of the best solutions to global environmental issues. Applying demand response programs (DRPs) in this context could enhance the system's efficiency. Evaluating different DRPs' performances and assessing economic impacts on different parts of the electricity market is essential. The inherent uncertainty of RES and prices is inevitable in electricity markets. As a result of the lack of information, it is crucial to mitigate the risks as much as possible, such as risks related to changes in demand, unit outages, or other traders' bid strategies. This research introduces a robust multi-objective optimization method to reach the most confident plan for the retailer based on uncertainty in RES and price. The integration of different DRPs is assessed according to the cost to retailers and benefits for consumers using a multi-objective model to survey the impacts of different parts' decisions on each other. The trade-off among DRPs is considered in this model, and they are traded using a new model to illustrate the daily effect of these programs in monthly operations. This paper uses hydrogen storage (HS) integrated with PV as a distributed energy resource. As the Iranian electricity market has just been established, this research proposes a framework for decision-making in new electricity markets to join future smart energy systems. The mid-term pricing evaluates the system's performance for more accurate monthly results. Also, the operation cost of the hydrogen storage is modeled to assess its performance in non-robust and robust scheduling. Mixed-integer linear programming (MILP) has been used to model this problem in GAMS. A developed linearizing method is considered with a controllable amount of errors to reduce the volume and time of the computation. Finally, the cost of consumers in non-robust and robust market planning in the presence of DRPs is reduced by 8.77 % and 9.66 %, respectively, and HS has a compelling performance in peak-shaving and load-shifting. [ABSTRACT FROM AUTHOR]

The recent development of new and innovative home battery systems has been seen by many as a catalyst for a solar energy revolution, and has created high expectations in the sector. Many observers have predicted an uptake of combined PV/battery units which could ultimately disconnect from the grid and lead to autonomous homes or micro-grids. However, most of the comments in social media, blogs or press articles lack proper cost evaluation and realistic simulations. We aim to bridge this gap by simulating self-consumption in various EU countries, for various household profiles, with or without battery. Results indicate that (1) self-consumption is a non-linear, almost asymptotic function of PV and battery sizes. Achieving 100% self-consumption (i.e. allowing for full off-grid operation) is not realistic for the studied countries without excessively oversizing the PV system and/or the battery; (2) although falling fast, the cost of domestic Li-Ion storage is most likely still too high for a large-scale market uptake in Europe; (3) home battery profitability and future uptake depend mainly on the indirect subsidies for self-consumption provided by the structure of retail prices; (4) the self-sufficiency rate varies widely between households. For a given household, the volume of self-consumption cannot be predicted in a deterministic way. Along with these results, this study also provides a database of synthetic household profiles, a simulation tool for the prediction of self-consumption and a method for the optimal sizing of such systems. [ABSTRACT FROM AUTHOR]

Demand Response (DR) applications along with strategically deployed solar photovoltaic (PV) and ice storage systems at the building level can help reduce building peak demand and energy consumption. Research shows that no work has been carried out to study the impact of integrated control of PV and ice storage on improving building operation and energy savings in demand responsive buildings. This can enable building operators to take advantage of different electricity prices and enable utilities to spread the demand over whole day. This research presents a model to study coordinated control of building end-use loads including cooling, lighting and plug loads, together with PV and ice storage integrated with packaged air conditioning (AC) units. This is used to study their impacts on peak demand and energy consumption in a simulated medium-sized office building located in Virginia/Maryland, U.S. area. Research findings provide an improved understanding of the contribution of DR, solar PV and ice storage systems towards reducing building peak electricity demand and energy consumption while being sensitive to occupant thermal and lighting needs. [ABSTRACT FROM AUTHOR]

This paper aimed to study the socio-economic performance of a novel solar photovoltaic/loop-heat-pipe (PV/LHP) heat pump water heating system for application in three different climatic regions, namely, cold area represented by London, warm area represented by Shanghai, and hot (subtropical) area represented by Hong Kong. This study involved prediction of the annual fossil-fuel energy saving, investment return period and carbon emission reduction of the new system against the traditional gas-fired and electrical boilers based water heating systems. An established dynamic model developed by the authors was utilised to predict the system’s energy performance throughout a year in the three climatic regions. A life-cycle analytical model was further developed to analyse the economic and environmental benefits of the new system relative to the traditional systems. Analyses of the modelling results drew out several conclusive remarks: (1) the system could achieve the highest energy efficiency when operating at the hot (subtropical) climatic region (represented by Hong Kong), enabling the heat output of as high as 922 kW h/m 2 yr and water temperature of above 45 °C, while the grid power input is only 59 kW h/m 2 yr; (2) the system is worth for investment when operating at the high energy charging tariff area (represented by London), with the cost payback periods of 8 and 5 years relative to the traditional gas-fired and electrical boilers based systems, respectively; (3) the system could obtain the most promising environmental benefits when operating in Shanghai where the energy quality (embodied carbon volume of per kW h energy) is relatively poor, enabling reduction in life-cycle carbon emissions of around 4.08 tons/m 2 and 17.87 tons/m 2 respectively, relative to the gas-fired and electrical boilers. Answer to such a question on which area is most suitable for the system application is highly dependent upon the priority order among the three dominating factors: (1) energy efficiency, (2) economic revenue, and (3) environmental benefit, which may vary with the users, local concerns and policy influence, etc. The research results will be able to assist in decision making in implementation of the new PV/thermal technology and analyses of the associated economic and environmental benefits, thus contributing to realisation of the regional and global targets on fossil fuel energy saving and environmental sustainability. [ABSTRACT FROM AUTHOR]

Highlights: [•] Energy systems need to decarbonise, provide security and remain affordable. [•] There is uncertainty over which technologies will best enable this to happen. [•] A strategy to deal with uncertainty is to assess a technologies ability to show resilience, flexibility and adaptability. [•] Scale is important and smaller scale technologies are like to display the above characteristics. [•] Smaller scale technologies are therefore more likely to enable a sustainable, secure, and affordable energy transition. [ABSTRACT FROM AUTHOR]

Highlights: [•] A simulation model is proposed considering PV, PHEV, storage, and demand response. [•] Various demand response programs are evaluated such as TOU, RTP, and curtailment. [•] We allow customers to schedule their PHEV charging, minimize the electricity bill. [•] The utility can minimize the peak by PHEV charging by changing electricity prices. [ABSTRACT FROM AUTHOR]

Abstract: This paper introduced the concept, potential application and benefits relating to a novel solar photovoltaic/loop-heat-pipe (PV/LHP) heat pump system for hot water generation. On this basis, the paper reported the process and results of characterizing the performance of such a system, which was undertaken through dedicated thermo-fluid and energy balance analyses, computer model development and operation, and experimental verification and modification. The fundamental heat transfer, fluid flow and photovoltaic governing equations were applied to characterize the energy conversion and transfer processes occurring in each part and whole system layout; while the energy balance approach was utilized to enable inter-connection and resolution of the grouped equations. As a result, a dedicated computer model was developed and used to calculate the operational parameters, optimise the geometrical configurations and sizes, and recommend the appropriate operational condition relating to the system. Further, an experimental rig was constructed and utilized to acquire the relevant measurement data that thus enabled the parallel comparison between the simulation and experiment. It is concluded that the testing and modelling results are in good agreement, indicating that the model has the reasonable accuracy in predicting the system’s performance. Under the given experimental conditions, the electrical, thermal and overall efficiency of the PV/LHP module were around 10%, 40% and 50% respectively; whilst the system’s overall performance coefficient (COPPV/T ) was 8.7. Impact of the operational parameters (i.e. solar radiation, air temperature, air velocity, heat-pump’s evaporation temperature, glazing covers, and number of the absorbing heat pipes) to the performance of the system (in terms of efficiencies of the PV/LHP module and the system’s overall performance coefficient COPPV/T ) was investigated individually. The results indicated that lower solar radiation, lower air temperature, higher air velocity and smaller cover number led to enhanced electrical efficiency but reduced thermal efficiency of the module; whereas lower heat-pump’s evaporation temperature and larger number of heat absorbing pipes gave rise to both thermal and electrical efficiencies of the module. The research results would assist in developing a high efficient solar (space or hot water) heating system and thus contribute to realisation of the energy saving and associated carbon emission targets set for buildings globally. [Copyright &y& Elsevier]

Rapid deployment of solar photovoltaics (PV), electric heat pumps (HP) and electric vehicles (EV) is needed to decarbonize the economy. However, the integration of these technologies into the power system creates challenges for the distribution grid infrastructure. It is therefore vital to analyse to which extent grid reinforcement is needed to enable decarbonization strategies while also studying alternative flexibility measures. In this GIS-based study, we model the impact of the deployment of PV, HP and EV on a low-voltage distribution grid network serving 170'000 households in Switzerland, and analyse scenarios for their penetration in the years 2035 and 2050. Using a detailed grid model in collaboration with a distribution system operator, we find that PV leads to 18.5% and 13.7% more voltage violation issues compared to HP and EV respectively, which on the other hand, cause slightly more line overloading, 0.5% and 2.5%, respectively. We also find that grid reinforcement costs markedly depend on the type of urban setting ranging between 51–213 CHF/kW p , 46–1'385 CHF/kW and 34–143 CHF/kW for PV, HP and EV, respectively, with the higher limit corresponding to rural areas. The total distribution grid reinforcement costs can amount up to 11 billion CHF until 2050 i.e. 2'900 CHF per household in Switzerland. Interestingly, we find that batteries, even with current costs, have the potential to defer grid reinforcement for up to 15% of the transformer stations with the highest specific grid reinforcement costs. Our study aims to inform various stakeholders about the required grid investments to enable the massive deployment of low carbon technologies. • Distribution grid impacts due to deployment of PV, heat pumps and EV charging assessed. • Scenarios are built for PV, HP and EV penetration in 2035 and 2050. • Grid reinforcement costs in rural areas higher compared to urban and suburban areas. • Variations in grid reinforcement costs are explained by technology additions (R 2 > 94%). • Batteries with current costs can defer reinforcement in up to 15% transformer stations. [ABSTRACT FROM AUTHOR]

• Hydrogen-solar-storage integrated microgrid for airport electrification. • Airport energy dispatch strategy incorporated with flight schedules. • Five energy supply scenarios with techno-economic lifecycle assessment. • Sensitivity analysis of key parameters on future energy system design. • Airport microgrid presents economic and environmental benefits. Can aviation really become less polluting? The electrification of airport energy system as a micro-grid is a promising solution to achieve zero emission airport operation, however such electrification approach presents the engineering challenge of integrating new energy resources, such as hydrogen supply and solar energy as attractive options to decarbonize the present system. This paper explores the techno-economic benefits of integrating hydrogen supply, electric auxiliary power unit (APU) of aircraft, electric vehicles, photovoltaic energy (PV), and battery storage system into electrified airport energy system. The hydrogen fuel cell generation provides great flexibility to supply aircraft at remote stands, and reduces the carbon emissions caused by traditional fuel-powered APU. A mixed integer linear programming optimization method based on life cycle theory is developed for capacity sizing of hydrogen energy system, PV and battery storage, with optimization objective of minimizing the total economic costs as well as considering environmental benefits of the proposed airport microgrid system. Case studies are conducted by five different energy integration scenarios with techno-economic and environmental assessments to quantify the benefits of integrating hydrogen and renewable energy into airport. Compared with the benchmark scenarios, the integration of hydrogen energy system reduced the total annual costs and carbon emissions of airport energy system by 41.6% and 67.29%, respectively. Finally, sensitivity analysis of key system parameters such as solar irradiance, grid emission factor, elctricity price, carbon tax, unit investment cost of hydrogen energy system have been investigated to inform the design of hydrogen-solar-storage integrated energy system for future airport electrification. [ABSTRACT FROM AUTHOR]

This paper analyses optimal electricity investments (PV and battery storage) to decarbonise heat supply in residential buildings under different heat pump and energy retrofitting scenarios in a detailed representation of the Swiss power and heating system. The sensitivity of PV and storage deployment, including lithium-ion (LiB) and vanadium redox flow batteries (VRFB), with respect to distribution network capacity is also investigated. We propose an open-source dispatch sector coupling model (GRIMSEL-AH) to minimise energy system costs (social planner perspective) for heating and electricity supply in Switzerland with hourly and daily time resolution for electricity and heating respectively. Moreover, our representation of the Swiss energy system includes various types of consumers and urban settings which are represented with monitored electricity demand data for each sector and simulated heat demand data at the building level for the residential sector. We find that under a "business as usual" heat pump deployment and retrofitting rate, the optimal electricity investments correspond to 27.8 GW p of PV combined with 16.9 GW (33.8 GWh) for LiB and 1.9 GW (7.6 GWh) for VRFB. For this case, 57% (13.3 TW th /year) of the residential heat demand is covered by heat pumps with a total installed capacity of 19.7 GW th by 2050 (capacity exogenously set with its operation optimised). With increasing heat pump deployment, retrofitting rates are found to have a large impact on the investment in storage and a 100% heat pump scenario for the residential sector appears to be feasible. Our results show that heat pumps do not only decarbonise heat but also provide extra flexibility to the power system, since they increase local PV self-consumption, resulting in higher PV deployment. The model and the methodology presented in this study can be applied to other countries. • Open-source sector coupling modelling framework with flexible heat pump operation. • Impact of heat pump and energy retrofitting scenarios on electricity investments. • Retrofitting rates have a significant impact on the storage investment. • Heat pumps provide extra flexibility by increasing local PV self-consumption. • Trade-offs between storage and distribution grid upgrade are discussed. [ABSTRACT FROM AUTHOR]

• Assessment of profitability and optimal sizing of residential PV and battery storage. • Consideration of heterogeneous household load profiles (e.g., size, employment status, energy efficiency). • Consideration of heterogeneous financial (metrics, parameters, source of financing) and fiscal dimensions (tax treatments, tax rates), within the German regulatory framework. • Battery energy storage increases the profitability of residential PV in many of the considered cases. • Optimal coupling of batteries (as opposite to stand-alone PV) range from 0% to 94% of the analyzed load profiles, following the variation of such finance-related dimensions (e.g., discount rates, debt versus equity financing). • Financial and fiscal aspects may be determinant to understand the diffusion and sizing of renewable energy technologies, especially among heterogeneous investors. The German government, in order to reach its renewable energy targets, has promoted the deployment of solar PV. Small residential PV installations coupled with battery energy storage systems are gaining momentum, as self-consumption has grown in attractiveness. We conducted an economic analysis to assess the profitability and optimal configuration of these technologies from the perspective of heterogeneous households that are subject to the current German regulatory framework. In this regard, we consider heterogeneous potential for self-consumption of electricity (e.g. household size, energy efficiency), as well as heterogeneous financial (i.e., metrics, parameters, sources of financing) and fiscal (i.e., tax treatment, tax rate) aspects. We find that the usage of alternative financial metrics (i.e., payback period, real internal rate of return and net present value), as criterion to evaluate profitability, remarkably affects rankings of system configurations. Secondly, fiscal aspects are crucial to assess profitability and marginally relevant for optimal system configuration, while financial aspects are greatly important for both matters. Our results on optimal battery coupling (as opposite to stand-alone PV) show that rates of adoption range between 0% and 94% of the analyzed load profiles, following the variation of such finance-related dimensions (e.g. discount rates, inflation, debt versus equity financing). We conclude that such findings on the impact of such factors, are greatly relevant to design cost-efficient and effective policies that aim to foster energy transitions, both in Germany and elsewhere, especially in a time of very low interest rates. [ABSTRACT FROM AUTHOR]

• An optimization tool combining renewable generation and storage is applied to an exhibition centre. • Strategies to minimize costs of seasonal energy demand via peak shaving are proposed. • The energy demand disaggregation addresses metering shortfalls of commercial sites. • Up to 20% cost savings and between 35 and 60% carbon emission savings can be achieved. • A PV-battery setup is not cost competitive yet, but maximizes carbon savings. To move from centralised fossil fuel-based energy systems, synergies between distributed renewable generation, storage and demand-side strategies can be exploited to lower environmental impact and costs. This paper proposes an optimisation model for the techno-economic assessment of energy management strategies with a short-term investment horizon aimed at business managers and decision-makers in the commercial sector. The main novelty is the selection of a combination of on-site technologies and peak shaving strategies to minimise energy costs under time-of-use electricity tariffs, and the adaptation of a general methodology for a specific socio-technical context under seasonal loads. The "Fiera del Levante" exhibition centre in the city of Bari is selected due to the high seasonality of its electricity demand. The optimal solution uses a combined system with photovoltaics, diesel-fired and gas-fired combined-heat-and-power, including part-load operation and electric storage. The cost minimisation scenario reports up to 20% cost savings and 35% carbon emission savings with a 1MWp photovoltaic plant, compared to the baseline. This presents a five-year return on investment of 75%, and levelized cost of energy of €0.14 kWh−1. When coupled with a lithium-ion battery, solar energy brings up to 60% carbon emission savings through load shifting strategies, though this reduces the five-year return on investment by 9%. This hybrid setup is not financially competitive in the Italian retail market, but a hypothetical 25% rise of the grid import prices would make it economically viable. The proposed model is flexible and can be adapted to commercial end-users, providing decision-support in urban energy systems under local conditions. [ABSTRACT FROM AUTHOR]

• Develop a coordinated control to optimize building-cluster-level performance. • Maximize renewable energy sharing among building electricity prosumers. • Use smart electric vehicle charging to improve match between demand and supply. • Compare developed control with two existing controls using data from real buildings. • Significantly increase renewable self-utilization rates and reduce electricity bills. Distributed renewable energy systems are now widely installed in many buildings, transforming the buildings into 'electricity prosumers'. Existing studies have developed some advanced building side controls that enable renewable energy sharing and that aim to optimize building-cluster-level performance via regulating the energy storage charging/discharging. However, the flexible demand shifting ability of electric vehicles is not considered in these building side controls. For instance, the electric vehicle charging will usually start once they are plugged into charging stations. But, in such charging period the renewable generation may be insufficient to cover the EV charging load, leading to grid electricity imports. Consequently, the building-cluster-level performance is not optimized. Therefore, this study proposes a coordinated control of building prosumers for improving the cluster-level performance, by making use of energy sharing and storage capability of electricity batteries in both buildings and EVs. An EV charging/discharging model is first developed. Then, based on the predicted future 24 h electricity demand and renewable generation data, the coordinated control first considers the whole building cluster as one 'integrated' building and optimizes its operation as well as the EV charging/discharging using genetic algorithm. Next, the operation of individual buildings in the future 24 h is coordinated using nonlinear programming. For validation, the developed control has been tested on a real building cluster in Ludvika, Sweden. The study results show that the developed control can increase the cluster-level daily renewable self-consumption rate by 19% and meanwhile reduce the daily electricity bills by 36% compared with the conventional controls. [ABSTRACT FROM AUTHOR]

• Energy yield simulation of vertical bifacial PV array in 12 European locations. • Comparison with a conventional PV array (monofacial, equator-oriented, tilted). • Evaluation of market revenues based on historic day-ahead market prices. • Evaluation of LCOE and net present value. • Evaluation of system cost reduction from a macroeconomic perspective for Germany. Thanks to the two diurnal generation peaks, vertical bifacial photovoltaic power plants (VBPV) with a north-south axis represent an option to meet the challenges of a mismatch between electricity demand and the generation profile of conventional photovoltaic systems (C-PV). Despite this promising characteristic, it is hardly possible to assess the technical and economic properties of VBPV on the basis of existing studies. The present work is a contribution to close this gap. Among other things, the conducted analyses included electricity generation, market revenues, levelized costs of electricity (LCOE) and the cost-reducing effect of VBPV in a national electricity system. C-PV was used as a benchmark in all analyses. Electricity generation was simulated at twelve European sites in four countries. It has been found that above a latitude of 50° VBPV generates more electricity than C-PV. Due to the higher investments, VBPV had higher LCOE at all locations investigated. The results also showed that VBPV can generate higher revenues in electricity markets with a high share of C-PV capacity, but that these additional revenues are not yet sufficient to compensate for the higher investments. With an optimising electricity market model, it was also found that VBPV can contribute to reducing system costs in an electricity system with high shares of C-PV capacity. Against the background of the increasing importance of PV for the electricity supply of most European countries, these findings are of particular importance. In summary, it can be said that VBPV has significant potential at both the business and macro-economic level and that decision makers should promote the market entry of this technology. [ABSTRACT FROM AUTHOR]

• A novel structural design for single-axis tracking is presented. • The performance analysis is carried out using the sun-earth relationships and a predicted radiation model. • The proposed single-axis tracking structure is superior to the existing ones at almost all latitudes. • The annual radiation incident upon the proposed tracked panel is 96.40% of that upon a dual-axis tracked panel. Existing structural designs of various single-axis tracking systems have potentially limited energy production. This paper presents the design and performance analysis of a single-axis tracking system with a novel tracking structure. Tracking mathematic expressions based on the sun-earth geometric relationships and a predicted solar radiation model are presented. The ratio of annual solar radiation incident upon the proposed tracked panel relative to that upon a dual-axis tracked panel is 96.40%. The simulation results show that it has significant advantages over the existing single-axis tracking structures at almost all latitudes. The proposed tracking structure is a competitive choice and will provide a new perspective on enhancing solar energy yield. [ABSTRACT FROM AUTHOR]

• It summarizes the building integrated solar concentrating systems according to different functions. • It introduces the demands, types, applications and structures of the building integrated solar concentrating systems. • It presents prospects/directions/policies around the world towards the building integrated solar concentrating systems. In the building sector, concerns towards the vast energy consumption has promoted the development of renewable energy technologies. In this regards, the solar concentration devices show a promising concept for building applications. However, the solar concentrators for application in buildings have many restrictions, which are different from the traditional solar concentrators. The main objective of this paper is to present a concise review on the building integrated concentrating devices, that have their own characteristics and multiple functions. This paper made a classification based on device's functions, i.e. building integrated concentrated photovoltaic systems (BICPV), building integrated concentrating solar thermal (BICST) and building integrated concentrating solar daylighting (BICSD) and the combination of functions, i.e. BICPV/T, BICPV/D, BICST/D and BICPV/T/D. At the same time, this paper presented an elaborate introduction of the demands, types and applications of the building integrated concentrating devices and prospects/ directions/ policies about these technologies around the world. The review would provide important information for the actual engineering of building integrated concentrating devices. [ABSTRACT FROM AUTHOR]

• A game model among governments, banks and PV companies is built. • Empirical analysis for the impact of subsidies and loans on PV company. • The "Credit Limitation Policy" is a quasi-natural experiment to test loan access. • Loan limitation undermines PV companies' performance. • Governments' subsidies have little impact on company performance. China's Photovoltaic (PV) industry plays a critical role in the global PV industry. Between 2013 and 2015, Chinese PV companies were restricted in their access to debt financing. However, to date there has been a lack of studies investigating this "Credit Restriction Policy". This paper innovatively builds a dynamic game model to analyze the behavior of governments, banks and the PV companies in the process of financing PV companies and is the first attempt to use the quasi-natural experiment in the PV industry to investigate the impact of loan restriction on firm performance. The game analysis shows that both the governments' support behavior and companies' loan decisions have nothing to do with the cost of governments' support to companies. Using the panel data for China's listed PV companies from 2007 to 2017, the empirical results reveal that restricting access to bank loan undermines PV companies' performance, but government subsidies have little impact on the operating performance of PV companies. The results suggest that while restriction of financial access has negative impact on PV companies, government's administrative intervention is not desirable and instead government should improve the institutions for bank lending. [ABSTRACT FROM AUTHOR]

• A novel grid-cell approach to estimate global solar energy potential. • Solar potentials constrained by land-use, technology conversion and net energy. • A new solar-to-electric efficiency parametrization for CSP power plants. • Power plants design optimised by maximising the Energy Return on Investment. • Solar potential is established between 1089 and 165 EJ/year at EROImin from 5 to 9. The amount of energy striking the earth's surface in one hour is higher than global annual societies energy use, yet the fraction of incoming solar radiation that can be harvested is significantly constrained. A global grid-cell methodology was adopted to assess the available global solar energy potential taking into account four constraints: land-use, solar irradiation, solar-to-electric technology, and net energy. Net energy is the amount of energy that is delivered to end-users, after subtraction of the energy inputs needed for capital infrastructure and operation. Both photovoltaic and concentrated solar power technologies are considered. The resulting constrained solar potential worldwide was estimated at 1098 exajoules per year, of which 98%, 75%, and only 15% can be extracted if the system needs to deliver an energy return on energy invested set at 5, 7.5, and 9, respectively. The resulting global solar potential is substantially lower than most previous estimates. Depending on how high the energy return needs to be relative to the energy investment needed to maintain a sustainable society, the achievable potential will be significantly constrained. The effect is especially significant in lower solar radiation regions. The European Union holds only 2% of the global solar net energy potential. [ABSTRACT FROM AUTHOR]

• Management of solar energy and seawater desalination using water storage systems. • Development of dynamic reverse osmosis model implemented in TRNSYS environment. • Dynamic analysis of a real case based on hourly water demand of Pantelleria Island. • Economic and sensitivity analysis to select the main design/operating parameters. • Low pay-back periods for specific costs of the water higher than 7 €/m3. This paper presents a novel methodology for the management of the solar energy and seawater desalination, using water storage systems. The investigated plant includes photovoltaic panels, supplying a reverse osmosis unit for freshwater production. This novel methodology, based on the use of a water storage basin, allows one to avoid electric storage systems, determining a stable water production and maximizing the water self-consumption. The water storage basin allows one to obtain a significantly different trend of the freshwater availability with respect to the photovoltaic production, mainly occurring during the central hours of the day. The plant is dynamically simulated in TRNSYS environment. The proposed plant is assumed to operate in small Mediterranean islands, rich in solar energy and seawater availability, featured by a scarce freshwater availability and dramatically high freshwater costs. As main case study, Pantelleria Island (South Italy) is selected. The system energy performance is calculated in detail implementing accurate models for all the system components. Special control strategies are implemented in order to maximize the system profitability, evaluated by considering both capital and operating costs. The developed system is extremely profitable: the achieved payback period is about 1.3 years, mainly due to high capital cost of freshwater in the reference scenario. A remarkable water saving equal to 80% is obtained, also reducing the dependency of the Island from the water transported by the tank ships. For the selected case study, the sensitivity analyses suggest adopting a solar field area equal to 6436 m2, avoiding an increase of the water storage basin and of the maximum and minimum operating pressures of the reverse osmosis unit single train. [ABSTRACT FROM AUTHOR]