Household Photovoltaic Research Articles

Impact of photovoltaic and biogas power plant on harmonics in distribution network

Here, the impacts of biogas power plants and photovoltaic (PV) power plants on the power quality in the distribution network are presented and analysed. The biogas power plant's influence on the current harmonics is explored, as a synchronous generator powers the biogas power plant, and the PV plants are connected to the distribution network via the inverter. All the analyses are based on actual measurements that are performed in the last 10 years. Results of the analysis of these numerous measurements were a challenge for investigation how large share of PV systems in distribution network with non-linear loads influence on THD from one side and how biogas power plant with a synchronous generator can improve THD from the other side. In order to investigate interaction of the biomass power plant and PV power plants on the power quality in distribution network, computer model was developed in DIgSILENT Power Factory where PV power plant and household were modelled as a source of current harmonic injections and biomass power plant was modelled as synchronous machine, as a source of voltage harmonics. Analysis of harmonic behaviour in different scenarios is examined through the performed simulations.

Solar PV generation in Colombia - A qualitative and quantitative approach to analyze the potential of solar energy market

Colombia faces several challenges to secure a reliable, affordable, and climate-friendly energy supply. Persistently low reserve-to-production ratios in oil and gas, together with advancing climate change, are putting the country’s energy system at risk. Heavily relying on hydro-power, Colombia’s electricity system will become more vulnerable with extreme weather patterns such as El Niño. This paper offers a multi-method study of the role of photovoltaic (PV), specially prosumage systems, to support a slowly starting energy transition in Colombia. First, qualitative data from an expert elicitation in Colombia’s energy sector is analysed. Second, a model to calculate the internal rate of revenue for households is used to identify optimal sizes for household PV or prosumage systems under the new regulatory framework. Key concerns emerging from the expert elicitation include lacking substantial financial aid, insufficient tax incentives, and high equipment prices, which raise investment and operation costs. Also, model results confirm net-metering implementation as an enabler of widespread deployment of household PV systems. Most profitable system configurations include PV systems without storage technology. Our findings show that financial instruments are still insufficient to scale-up household level PV deployment.

Towards net-zero energy neighbourhoods utilising high rates of residential photovoltaics with battery storage: a techno-economic analysis

ABSTRACTThis paper aims to evaluate the role of residential battery storage in addressing network barriers to the further adoption of household photovoltaics, by presenting a unique perspective combining a housing and network techno-economic evaluation. Stochasticity in demand and weather inputs are modelled using Monte Carlo and a power flow model is constructed of a test area of the low-voltage (LV) network. Findings include: that batteries address voltage drop issues on LV networks at photovoltaic penetration rates of 50% and over and can mitigate voltage rise issues at PV penetration rates up to 75%. Economically, under Queensland conditions, household gains are marginal with optimal results provided by charging batteries from photovoltaic generation only and a minimum array size of 5 kW.

Multi-time Scale Home Energy Management Considering User Comfort

With the rapid development of household photovoltaics and electric vehicles, demand-side energy management has become an important means to release the burden of power grid during the load peaking period. In order to ensure the user comfort and reduce the cost of electricity, a multi-time scale home energy management method is proposed based on mixed integer programming algorithm. Firstly, on the basis of time-of-use electricity price, household photovoltaic, electric vehicles, storage batteries and HVAC are taken into consideration. And then, short time scale model of HVAC is adopted, which increases the rationality of modeling while discretizing. The simulation results verify the superiority of multi-time scale and the optimization effect of the proposed method, which can reduce the cost of electricity for users, smooth the load curve and improve the utilization efficiency of renewable energy.

Q-complementarity in household adoption of photovoltaics and electricity-intensive goods: The case of electric vehicles

Photovoltaic (PV) units and electric vehicles (EVs) are two household goods that are the focus of much research, and many policy initiatives attempting to promote a more sustainable, low-carbon energy system. Despite both academic and practical interest in household adoption of PV units and EVs, potential linkages in these household decisions have only just begun to be explored. This paper presents q-complementarity between the goods as one possible form of a linkage between PV and EV purchases that is based on economic utility theory. We posit the goods could be q-complements due to a PV-owning household's ability to offset and shift their electricity load from EV charging to increase the self-consumption of ‘home-made’ electricity, thereby increasing the positive feelings of environmental efficacy and monetary returns from the PV unit. We use data from 2541 internet surveys of Austrian residential electricity customers collected in 2018 to explore these hypotheses. Probit models of household EV and PV adoption choice are estimated, including a recursive bivariate probit model of households who plan to purchase an EV in the future, with PV ownership endogenously determined. Controlling for household income, characteristics, environmental attitudes, and neighborhood characteristics, we find that EV and PV adoption are positively correlated, and that current PV unit owners are 21% more likely to plan an EV purchase in the next 5 years compared to non-PV owners. We interpret these results as evidence in support of our hypothesis of q-complementarity between PV units and EVs, and note the potential for added benefits from incentive policies promoting adoption of one good or the other that this linkage suggests.

Design criteria for the optimal sizing of a hybrid energy storage system in PV household-prosumers to maximize self-consumption and self-sufficiency

Batteries of photovoltaic (PV) household-prosumers undergo many fast, partial charge/discharge cycles because of the short-term fluctuations of household load and PV profiles. This negatively affects battery lifetime and can increase project cost involving energy storage systems (ESSs). To address this problem, this research developed an innovative analytical technique that assesses the techno-economic impact of battery-aging mechanisms and their influence on the optimal sizing of a hybrid energy storage system (HESS) for prosumers so as to minimize the total energy supply cost. This technique, implemented in a dynamic model of the integrated system, designs battery degradation, supercapacitor (SC) behaviour, converter hardware implementation, and power management strategy (PMS). The results, as reflected in technical short and long-term assessments, showed a potential improvement in self-consumption and self-sufficiency ratios due to PV, battery, SC, and the extension of battery lifetime in various PV-ESS sizing scenarios. The optimal PV-battery configuration was then determined by a techno-economic assessment, as well as the most suitable HESS sizing, while preserving the previous ratios of optimal PV-battery configuration, though with a lower life-cycle cost. The optimal PV-battery configuration was found to depend on the long-term power fluctuations of input profiles, whereas short-term fluctuations determined the optimal HESS sizing.

Assessment of economic benefits of battery energy storage application for the PV‐equipped households in Finland

Significant growth in residential solar photovoltaic (PV) installations and the ongoing decline in battery costs have increased interest in household solar battery energy storage projects in Finland in recent years. Among various potential applications, considerable attention is drawn to the use of the battery energy storage system (BESS) for the purpose of the households’ self-consumption enhancement. This study presents the results of a techno-economic study of the LiFePO4-based battery storage added to residential roof-top PV installations in Finland to maximise self-utilisation of on-site solar energy generation. Using a comprehensive DC model of BESS, the battery charge and discharge levels under the typical household load and PV production conditions are simulated. The estimates of the average retail electricity prices are used to assess the value that the customer-sited solar battery storage can provide to the household end-users in Finland. The economic attractiveness of the battery storage projects is evaluated considering the present and forecasted BESS costs and the electricity tariff levels in Finland and the conditions for profitable operation of the solar energy storage systems are determined.

When the carrot goes bad: The effect of solar rebate uncertainty

Although meant to encourage investment in solar photovoltaic (PV) systems, some incentive policies may themselves become a barrier in instances where policy-related uncertainty is present, as potential solar adopters delay their investment until uncertainty is resolved. This study utilizes a quasi-experimental setting to quantify the effect of solar policy uncertainty. Focusing on the California Solar Initiative's residential rebate program, I exploit the temporary exhaustion of funds within one of the utility territories as an exogenous source of increased uncertainty and estimate that it leads to a 67% drop in rebate applications in an average ZIP code-week. There is considerable heterogeneity in this effect depending on household income and PV system size. Among households that are least likely to invest in PV without a rebate incentive, program participation drops by up to 69%. This suggests potentially significant loss in program effectiveness due to lower PV adoption and underscores the importance of accounting for uncertainty in policy evaluations.

Spatial disaggregation clarifies the inequity in distributional outcomes of household solar PV installation

Global installations of household rooftop solar photovoltaics (PVs) are rapidly increasing, driven in many cases by government incentives. We show a direct correlation between economic resources and both the PV penetration and the average PV system size. Using datasets with a high areal resolution for socioeconomic indicators and household PV installations, we create an Index of Economic Resources for Owner-Occupiers for the Australian Capital Territory, Australia. Our analysis confirms the inaccuracy of using highly aggregated datasets in exploring the socioeconomic outcomes of the renewable energy policy, an inaccuracy long known in other disciplines. Analyses using such datasets are likely to overlook vulnerable areas, which could increase perverse policy outcomes.

Prosumer Community: A Risk Aversion Energy Sharing Model

Household photovoltaic (HPV) prosumers and the community photovoltaic (CPV) system have been growing rapidly with the development of the sustainable technology. The uncertainties of these distributed renewable energy resources bring a significant challenge to the design of power-market mechanism and the energy dispatch of the power system for promoting energy efficiency. It is essential to develop a novel efficient energy management strategy for addressing this challenge from the perspective of community prosumers. Accordingly, a risk aversion energy sharing model based on a devised local energy market is presented. A stochastic game is established to minimize prosumers’ energy costs and the weighted conditional value-at-risk of energy sharing loss of uncertain CPV through optimal energy sharing profiles. The household loads and HPV outputs are considered as stochastic parameters in the game model. Moreover, a sample weighted average approximation (SWAA) method is proposed for a better estimation of the stochastic game while the SWAA equilibrium is obtained by a relaxation method-based algorithm with theoretical proof. In addition, the blockchain technology is introduced as a distributed and secure way to facilitate the energy sharing model. The case studies show the efficiency of the proposed energy sharing model and the algorithm.

Innovative Policies for Energy Efficiency and the Use of Renewables in Households

Renewable energy sources (RES) are gradually becoming one of the key elements in the process of achieving energy efficiency worldwide. This trend can be observed in many developed Western economies—for example, in the United States, as well as in the United Kingdom. Hence, the role of innovative policies for promoting energy efficiency is becoming crucial in transition to the post-carbon economy. The shift to the carbon-free future make all actors to face forgoing commitments Nevertheless, customers and residential households are the first and the most important players in the pursuit of the energy-efficient future. Without them, carbon-free economy based on RES would never take the shape as envisaged. Our paper focuses on the innovative strategies and policies studying the effect and the scope of RES penetration into the households. We employ and empirical analysis of the effects from using RES in households using an example of the residential households in the northwest region of the United Kingdom (UK) with and without solar photovoltaic (PV) panels and electric vehicles (EV). We analyse the four scenarios that are aimed at analysing the system dynamics and providing differentiation between systems in terms of the varying values of the gross demand, tariffs, metered import, and the total revenue. Our results demonstrate that the solar PV leads to the transfer of costs and wealth regardless of the ownership of PV and EVs. Solar energy generation reduces the share of UK solar PV households per kWh costs of the distribution system which causes the augmenting of the per unit charges as well as to the changes in payments for the electricity that impoverishes less wealthy customer groups. It also becomes clear that with the increase of EV penetration, the existing energy efficiency schemes would have to be revised.

Supercapacitors on demand: all-printed energy storage devices with adaptable design

Demands on the storage of energy have increased for many reasons, in part driven by household photovoltaics, electric grid balancing, along with portable and wearable electronics. These are fast-growing and differentiated applications that need large volume and/or highly distributed electrical energy storage, which then requires environmentally friendly, scalable and flexible materials and manufacturing techniques. However, the limitations on current inorganic technologies have driven research efforts to explore organic and carbon-based alternatives. Here, we report a conducting polymer:cellulose composite that serves as the active material in supercapacitors which has been incorporated into all-printed energy storage devices. These devices exhibit a specific capacitance of ≈90 F g−1 and an excellent cyclability (>10 000 cycles). Further, a design concept coined ‘supercapacitors on demand’ is presented, which is based on a printing–cutting–folding procedure, that provides us with a flexible production protocol to manufacture supercapacitors with adaptable configuration and electrical characteristics.

A global monitoring system for electricity consumption and production of household roof-top PV systems in Madeira

This paper describes recent work on the development of a wireless-based remote monitoring system for household energy consumption and generation in Madeira Island, Portugal. It contains three different main sections: (1) a monitoring system for consumed and produced energy of residencies equipped with photovoltaic (PV) systems, (2) developing a tool to predict the electricity production, (3) and proposing a solution to detect the PV system malfunctions. With the later tool, the user (owner) or the energy management system can monitor its own PV system and make an efficient schedule use of electricity at the consumption side. In addition, currently, the owners of PV systems are notified about a failure in the system only when they receive the bill, whereas using the proposed method conveniently would notify owners prior to bill issue. The artificial neural network was employed as a tool together with the hardware-based monitoring system which allows a daily analysis of the performance of the system. The comparison of the predicted value of the produced electricity with the actual production for each day shows the validity of the method.

Assessing the growth of residential PV exports with energy efficiency and the opportunity for local generation network credits

Abstract An unprecedented expansion of household photovoltaic (PV) systems coincided with a marked decline in household electricity demand in several jurisdictions around the world. This was driven by falling PV prices and the installation of more energy efficient residential appliances (EE). However, existing net metering arrangements value self-consumption of PV far more than PV exports to the grid. As a result, energy savings from EE that considerably reduce household PV self-consumption could also reduce the value of PV systems. Since PV exports generally utilise only part of the distribution grid, ‘local generation network credits’ (LGNCs) have been proposed to increase the value of PV exports. LGNCs also have the potential to improve the combined value of PV and EE. Given the large variability of the household PV generation and load and the time-varying structure of LGNCs, an empirical probabilistic method is proposed in this paper in order to assess the combined PV-EE value with the LGNC arrangements. The results show how simplistic feed-in tariffs have an adverse impact on the combined PV-EE value and how LGNCs can assist in removing barriers to the combined uptake of these two key clean energy technologies.

Simulation of a simple PV system for local energy usage considering the time resolution of input data

This article focuses on simulation accuracy of photovoltaic (PV) systems designed for local energy usage in households. The results of simulations can be misleading when the input data is estimated not correctly or the input data has a low time resolution. Load profile is difficult to estimate due to the changes in user behaviour and possible high power fluctuations. In contrast to many other studies, 15s data are used as PV power and household load data input. Using this data for simulations we show the influence of averaging interval on the results and thus we indicate the variance in the simulated system performance (rates of self-consumption, energy independence and grid interaction).

Spatially-explicit Resilience Modeling for PV Electricity Supply-demand Balance

We analyse the potential of PV (Photovoltaic) in terms of electricity resiliency by developing a spatially-explicit model for the PV supply and household demand balance. The model estimation is conducted using hourly solar irradiance data for a whole year for the Tokyo metropolitan area. We have tested the resiliency of the bland against several scenarios of climate uncertainties. Our analysis shows that, although PV supply for the whole Tokyo is smaller than household electricity demand, high level of electricity surplus exists in the western central area where the disaster risk is relatively low, while, few electricity surplus remains in the eastern high disaster risk areas. These results suggest that if we are to create community- based regional resilient electricity sharing grid system ([1]) in the future, we need to create additionally a city scale multi-layer electricity sharing system for adjusting the dynamics demand-supply discrepancies by transferring PV surplus electricity to the high risk areas.

The Effect of Electricity Prices on Residential Solar Photovoltaic Panel Adoption: Fukushima as a Natural Experiment

There are a range of private financial benefits of residential solar photovoltaic (PV) installation, such as a reduced electricity bill, tax incentives and a feed-in tariff for generated electricity. To empirically analyze how rising electricity prices affect household adoption decisions, we use the 2011 Fukushima nuclear disaster as a natural experiment. The shutdown of nuclear power plants across Japan led to a sizable increase in electricity prices that varied by region, allowing us to identify the effect of electricity prices on household PV system adoption. We find that higher electricity prices are significantly more influential on PV adoption on existing homes than on newly-built homes. Our estimated electricity price elasticity of PV systems ranges from 0.9 to 1.2 for existing homes and is much smaller and statistically insignificant for newly-built homes. We discuss behavioral mechanisms explaining this difference and implications for policies stimulating residential adoption of renewables.

Entrepreneurship, sustainability, and solar distributed generation

The issues associated with the generation of own electric power by consumers who install solar photovoltaic (PV) panels (known as solar distributed generation, or DG), attracts rapidly growing attention of both policy-makers, regulators and the members of the general public. Distributed generation (DG) comes with a lot of benefits: being the most sustainable, cleanest source of energy, solar products facilitates local priorities, such as economic growth, internal security, mitigation against climate change, and employment opportunities. However, there is another side of the coin: despite the rapid success of solar DG, it is still faced with a plethora of issues and challenges. An increase in the rooftop solar PV in might results in a transfer of wealth and costs between customer groups. There are elderly, disabled and chronically sick citizens who cannot benefit from generating their own electric power using solar PV panels, but who might still face higher electricity bills due to the higher policy support charges (levies) and taxes aimed at supporting decarbonisation through distributed generation. Overall, it appears that current network charging regime is likely to be unfit in the presence of solar PV households who do not contribute to the grid as they should be.

Probabilistic evaluation of solar photovoltaic systems using Bayesian networks: a discounted cash flow assessment

AbstractSolar photovoltaic (PV) technology is now a key contributor worldwide in the transition towards low‐carbon electricity systems. To date, PV commonly receives subsidies in order to accelerate adoption rates by increasing investor returns. However, many aleatory and epistemic uncertainties exist with regard to these potential returns. In order to manage these uncertainties, an innovative probabilistic approach using Bayesian networks has been applied to the techno‐economic analysis of domestic solar PV. Empirical datasets from over 600 domestic PV systems, together with national domestic electricity usage datasets, have been used to generate and calibrate prior probability distributions for PV yield and domestic electricity consumption, respectively, for typical urban housing stock. Subsequently, conditional dependencies of PV self‐consumption with regard to PV generation and household electricity consumption have been simulated via stochastic modelling using high temporal resolution demand and PV generation data. A Bayesian network model is subsequently applied to deliver posterior probability distributions of key parameters as part of a discounted cash flow analysis. The results illustrate the sensitivity of PV investment returns to parameters such as PV self‐consumption, PV degradation rates and geographical location and quantify inherent uncertainties when evaluating the impact of sector‐specific PV adoption upon economic indicators. The outcomes are discussed in terms of the value and impact of this new Bayesian approach in terms of supporting robust and rigorous policy and investment decision‐making, especially in post‐subsidy contexts globally. © 2016 The Authors. Progress in Photovoltaics: Research and Applications published by John Wiley & Sons Ltd.

Photovoltaic systems in low‐voltage networks and overvoltage correction with reactive power control

This study deals with the overvoltage problems caused by the increased photovoltaic (PV) penetration in typical rural radial distribution systems, where small PV systems and household consumers are connected. For this study, the authors used an iterative algorithm to solve the power flow problem in radial grids and considered three methods for the correction of unacceptable overvoltages, which are based on different principles. The system under consideration is an almost symmetrical three phase, low-voltage radial network, consisting of nine PV and consumer connection points. The system was simulated for a whole year with a sample time of 15 min, taking into account the variations of the solar radiation and loads. The results verified that the control of reactive power on the line can successfully manage overvoltage issues. The additional demand of reactive power and consequent line losses are used to evaluate various correction methods.