Increase Of Self-consumption Research Articles

To use or not to use, that is the question: Income and substitution effects in the feed-in tariff system for solar-generated electricity

Feed-in tariff (FIT) is an important worldwide initiative to encourage renewable electricity technologies. Under the Japanese FIT system, households with solar panels decide the amount of both self-consumption and sales to the power company. By analyzing the household self-consumption and sales behaviors of solar-generated electricity obtained from the Ministry of the Environment of Japan, we examine (1) whether the rate of increase in electricity sales by households is higher or lower than the rate of increase in solar power generation and (2) whether self-consumption and sales behaviors of solar-generated electricity differ among households with different sales prices. The results show that the rate of increase in electricity sales is lower than that in solar electricity generation. This suggests that households increase their self-consumption as solar power generation increases. However, as the rate of increase in self-consumption is relatively low, solar-generated electricity is considered as a necessary good. Furthermore, we find that higher sales prices induce households to reduce their self-consumption and increase solar electricity sales to power companies.

Challenges of renewable energy communities on small Mediterranean islands: A case study on Ponza island

Italy has reconsidered incentives on Renewable Energy Sources (RES) to implement the EU clean energy transition and Renewable Energy Communities (REC). Legislation on RECs shifted the focus of incentives from production to self-consumptions. In this paper, the REC model is studied in a minor island disconnected from the national grid, with strongly seasonal energy load and water demand. This is a typical Mediterranean scenario where energy demand is covered by Diesel gensets and water supply is provided with tankers. The implementation of RES is investigated, exploiting the current REC model of incentives. Two sub-optimal REC configurations were defined using time-dependent simulations on pyRES, an in-house code for energy systems. Results show the economical unfeasibility of REC when there is a poor mix of users. In contrast, REC can achieve economic profitability including industrial demand of a desalination unit (DES). The increase of self-consumption guaranteed from the DES allows to increase the NPV of the community and results in major cuts in CO2 emissions (60% of those related to water supply and 10% of those from Diesel gensets) and a reduction of fuel costs of 22%. This method can be applied to investigate the performance of a REC in a local environment and help stakeholders in planning the expansions of RECs on the territory.

Determination of the power smoothing effect in a photovoltaic-hydrokinetic system by experimental analysis and pattern search

Sizing optimization and power smoothing methodology in highly fluctuating grid-connected renewable systems represent important challenges nowadays, the total cost and energy quality depend on the effective balance between source and load with certain restrictions to increase reliability and enhance the use of renewable sources at all scales. This article presents a novel power smoothing effect and sizing optimization methodology for a grid-connected photovoltaic-hydrokinetic system by pattern search method comparatively with three optimization algorithms encompassing a multi-objective optimization. In this context, the method considers the reduction of power fluctuations using supercapacitors, where the objective function considers technical and economic indexes. The main contribution of the research is that the objective function decreases the fluctuation suppression ratio to sizing optimization of renewable system through three pattern search size optimization algorithms. Experiments have shown that pattern search method can find the global optimum by reducing the computational effort; the Latin hypercube algorithm reduces the photovoltaic capacity by approximately 5 % and 2.3 % with respect to the Nelder Mead and genetic algorithm respectively. The influence of the supercapacitor successfully reduces power fluctuations and causes an increase in self-consumption of 32.32 %, this result represents an annual cost savings of 42 % on energy purchased from the grid. Furthermore, this paper goes further by calculating the optimal location of a hydrokinetic turbine in a river using the HEC-RAS software to determine with high precision the HKT power fluctuations as input signal to novel proposed method.

An Analysis of Energy Consumption in Small- and Medium-Sized Buildings

Building energy efficiency has grown strong in a context of soaring energy prices, especially in Europe. The use of energy-saving devices strongly influences its improvement, but in many cases, it is far from sufficient., especially if the energy comes from renewable sources with forced production. In the case of buildings, these are usually photovoltaic (PV) sources. For this reason, energy management systems (EMS) are becoming increasingly popular as they allow the increase in self-consumption and reduce the size of energy storage. This article presents analyses of historical energy consumption profiles in selected small- and medium-sized buildings powered by renewable energy sources. The implementation limitations of this type of systems, depending on the profile of the building, were identified and guidelines were presented to assess low-cost solutions dedicated to small buildings and considering the actual conditions of existing systems. Statistical analyzes were conducted for the energy demand profiles of 15 different buildings. The analyzes consisted of the preparation of box plots for each hour of working days and the calculation of the relative standard deviation (RSD) index for annual profiles of 60 min periods. The analyzes showed that the RSD index has low values for commercial buildings (e.g., hospital 7% and bank 15%) and very high values for residential buildings—even over 100%. On this basis, it can be concluded about the usefulness of energy profiles for demand forecasting. The novelty of the proposed method is to examine the possibility of using measurement data as data to forecast energy consumption based on statistical analysis, dedicated to low-cost EMS system solutions.

Investigation on Individual and Collective PV Self-Consumption for a Fifth Generation District Heating Network

Renewable Energy Communities have been recently introduced in European legislation to promote distributed generation from renewable energy sources. In fact, they allow to produce and consume energy from shared local power plants. Low temperature district heating and cooling networks with distributed heat pumps have demonstrated their capability to exploit renewable and waste heat sources in the urban environment. Therefore, they are considered a promising infrastructure to help decarbonize the building sector. As their main operating cost is the electricity purchased by the utility for heat pumps and circulation pumps, this work investigates whether a Renewable Energy Community could help mitigate such cost by sharing electricity produced by local photovoltaic (PV) systems. The research relies on computer simulations performed with both physical and statistical models for the evaluation of electrical load profiles at the district level. Results show that due to the different seasonality between heating demand and PV production, the increase in self-consumption due to the distributed heat pumps is lower than 10%. The use of batteries does not seem convenient for the same reason. The environmental benefit of the proposed system is evident, with CO2 emissions reduced by 72–80% compared to the current situation depending on PV power installed. It also emerged that PV sharing significantly improves the self-consumption at the district level, in particular when the installed PV power is limited (+45%). In conclusion, results suggest that current incentives on PV-sharing make Renewable Energy Communities a viable option to improve the techno-economic performance of fifth-generation district heating and cooling networks.

Comparing CO2 emissions impacts of electricity storage across applications and energy systems

Summary Electricity storage systems can support the decarbonization of energy systems. However, the effect of electricity storage use on greenhouse gas emissions is complex because of roundtrip efficiency losses of the storage and its effects on the dispatch of different electricity-generation technologies. The limited literature examining this issue focus on individual electricity storage applications and the geographies where they are applied. Here, we systematically compare the effects of electricity storage on CO2 emissions across four applications in electricity systems resembling seven European countries. Our findings reveal large emission impact differences between applications and countries. Among other findings, we find that when compared with wholesale arbitrage, storing electricity in other applications exhibits much lower effects on CO2 emissions. We also investigate different policy options to reduce CO2 emissions from storing electricity. We find that although a higher carbon price can have a substantial effect on reducing the CO2 emissions from wholesale arbitrage, other applications require alternative approaches.

Li-ion battery storage in private households with PV systems: Analyzing the economic impacts of battery aging and pooling

Abstract This paper investigates the economic viability of Li-ion battery storage for households, taking into account the economic costs of battery aging and the gains from battery pooling concepts. To this end, a techno-economic model is proposed that enables to quantify the increase in self-consumption of electricity from a solar photovoltaic system by means of a home battery storage system. Regarding battery aging, we find that the longest battery lifetimes can be achieved with the highest state-of-charge limit, which is, however, not economically preferable due to limited self-consumption. Three pooling concepts presently promoted in Germany are studied as well (Sonnen, Caterva, Fenecon). Although one of the three battery pooling concepts was identified as not being economical, namely the case of Sonnen, our evaluation shows that profitability can, in principle, be achieved with home battery pooling concepts. We find that the battery lifetime varies greatly from 11.6–26.5 years, depending on the state-of-charge limits set, with important economic implications on the overall cost effectiveness, and that the level of self-consumption of PV power is about 67.5% in the reference case, compared to 59.4–66.4% for the three battery pooling models analyzed.

Applying reinforcement learning to maximise photovoltaic self-consumption for electric vehicle charging

Recently, and in line with the ongoing trend of electrification, many office and industrial buildings are investing in rooftop photovoltaic (PV) installations and electric vehicle (EV) charging stations. This combination and the ability to shift EV charging in time provides opportunities to apply the flexibility of EV charging for local peak shaving and load balancing. This study applies a reinforcement learning algorithm, fitted Q-iteration (FQI), to coordinate the charging of an EV fleet in an office building with the objective of maximising self-consumption of the local generation by shifting the morning peak of EV charging to the afternoon when there is more PV generation. The performance of the proposed algorithm is evaluated using real-world data collected at the EnergyVille research institute in Belgium. The data analysis shows that each EV arriving in this building can offer on average 4 h of flexibility – the number of hours that the EV's charging can be delayed – a day. Simulation results show that FQI achieves a 32.1% increase in self-consumption compared to the business-as-usual model and an 11% decrease compared to a theoretical optimal control. Simulation results also show the scalability of the proposed method with the number of available charging stations.

Report on a Plus-Energy District with Low-Temperature DHC Network, Novel Agrothermal Heat Source, and Applied Demand Response

District heating and cooling networks can pose the possibility of including a variety of renewable energy sources as well as waste heat into a district’s heat supply concept. Unfortunately, low demand densities as they increasingly occur through higher building energy standards and in rural areas render conventional heating and cooling networks inefficient. At the same time, power-to-heat is becoming more and more important to make use of a larger amount of renewable energy sources on the electrical side by providing more flexibility by means of demand response and demand-side management. Within this work, a rural Plus-Energy settlement is presented addressing those topics by a low-temperature district heating and cooling network connected to a novel agrothermal collector supplying 23 residential buildings with decentralized heat pumps and PV systems. The collector, the network, and six of the buildings are equipped with comprehensive monitoring equipment. Within those buildings, forecast and optimization algorithms are implemented to adapt their heat pump operation to enable an increase of self-consumption, to include flexible electricity tariffs, and also to participate in power markets. Thereby, for the low-temperature district heating and cooling network, it has been shown that the concept can operate in the future at competitive heat costs. On the building level, up to 50% of cost savings could be achieved under ideal conditions with the optimization of the self-consumption of PV electricity. However, to ensure optimal results, the individual system components have to be dimensioned for this task.

Economic Modeling of the Economic Efficiency of Li-ion Battery Storage with a Special Focus on Residential PV Systems

This study provides a new approach for evaluating the economic efficiency of Li-ion battery storage, by combining a self-developed economic model with a technical battery-aging model. The model is used to quantify the increase in self-consumption of electrictiy from a solar PV system by means of a home battery storage system. Regarding battery-aging, we find that the longest battery lifetimes can be achieved with the highest state-of-charge (SOC) limit, which is not economically efficient due to the limited self-consumption. Two of the three distributed battery pooling concepts investigated were identified as economically efficient, namely the cases of Caterva and Fenecon. The evaluation shows that economic efficiency can still be achieved with home battery pooling concepts. In future resarch, the model-based impacts on self-consumption and battery-aging found ought to be validated by using real world data from the systems analyzed.

Smart grid and PV driven ground heat pump as thermal battery in small buildings for optimized electricity consumption

The purpose of this paper is to show the possible increase of self-consumption of photovoltaic (PV) electricity production for a building by intelligent use of thermal masses in the building. TRNSYS simulations were carried out for an electrically driven ground heat pump in combination with PV, thermally activated building systems and water storage (TES) in small single-family buildings. Several different control strategies adapting set-temperatures in combination with different building types and heat capacities were investigated. For a single-family house with 8900 kWh space heating and domestic hot water demand per year and a 20 m2 PV system, the solar fraction (SF) increased from 11% for a standard configuration up to 61% with maximized use of overheating of the TES (2000 L tank) and the building mass. The running cost for the heat pump due to grid electricity consumption (0.18 EUR per kWh) decreased from 420 EUR per year – in the reference case without PV – to 373 EUR (SF = 11%) with PV, but in the standard configuration without PV self-consumption optimization, and to 69 EUR per year (SF = 61%) with PV self-consumption optimization, if the remaining PV electricity was completely sold at 0.05 EUR per kWh.

Cost-Effectiveness of Li-Ion Battery Storage with a Special Focus on Photovoltaic Systems in Private Households

Using a self-developed economic model with a technical battery aging component, this paper provides a new approach to evaluating the economic efficiency of Li-ion battery storage. We use our model to quantify the increase in self-consumption of electricity from a solar photovoltaic system by means of a home battery storage system. Regarding battery aging, we find that the longest battery lifetimes can be achieved with the highest state-of-charge limit, which is, however, not economically efficient due to limited self-consumption. Although one of the three battery pooling concepts was identified as not being economically efficient, namely the case of Sonnen, our evaluation shows that economic efficiency can, in principle, be achieved with home battery pooling concepts. In future research, the model-based impacts on self-consumption and battery-aging found here ought to be validated by using real world data from the systems analyzed.

The Economic Feasibility of Residential Energy Storage Combined with PV Panels: The Role of Subsidies in Italy

A solar photovoltaic system produces electricity by converting energy from the sun. By the end of 2016, the global installed solar photovoltaic capacity reached 305 GW. Its growth is impressive in the last years; in fact, it was only equal to 41 GW in 2010. However, Europe has installed only 6.9 GW in 2016 (−1.7 GW in comparison to previous year) and this annual power installed is equal to 9% of global one in according to data released by Solar Power Europe. The profitability of PV systems in mature markets depends on the harmonization between demanded energy and produced one residential energy storage when combined with photovoltaic panels is able to increase the share of self-consumption. This work proposes a mathematical model, in which a Discounted Cash Flow analysis is conducted to evaluate the financial feasibility of photovoltaic-integrated lead acid battery systems in Italy. The indicator used is Net Present Value. Furthermore, a break-even point analysis, in terms of an increase of self-consumption, is conducted. The residential sector is investigated and energy storage system investment is incentivized by fiscal deduction and regional subsidies. The analysis provides several case studies, determined by combinations of the following variables: photovoltaic plant size, battery capacity, the increase of the share of self-consumption, and the useful lifetime of energy storage system. The same case studies are proposed also in four alternative scenarios, where is the modified the structure of subsidies. Results confirm that the profitability can be reached in presence of subsidies.

Enhancing Battery Lifetime in PV Battery Home Storage System Using Forecast Based Operating Strategies

An increase of self-consumption from domestic photovoltaic (PV) can be gained by the use of PV battery energy storage systems (PV-BESS). PV-BESS are currently just at the edge of profitability. Intelligent operating strategies might further increase the economy of these systems. This paper presents a novel approach for an operating strategy for PV-BESS which is able to increase the lifetime of lithium-ion batteries in such systems without reducing the self-consumption rate significantly. The operating strategy is evaluated by simulations, using a model of a DC-coupled PV-BESS and real data measurements as model inputs. To enhance the lifetime of the system, the average state of charge (SOC) of the battery is reduced by storing only the amount of energy predicted to be needed during the following night. With the applied approach, begin of night is defined as the point when the residual load becomes negative and accordingly, end of night is defined as the point when the residual load becomes positive again. This strategy is only applied in the summer months to use the full potential of the storage system during the winter. Using this strategy, seasonal effects like high average SOCs during summer will be reduced. For the necessary prediction, perfect forecast (best case) and persistence forecast (worst case) are evaluated to investigate the influence of prognosis inaccuracies. To minimize losses in self-consumption, not only a forecast for the next night will be considered but a variation of forecast periods is discussed. In conclusion, the results show that the application of such an operating strategy can increase battery lifetime significantly while affecting the self-consumption rate only slightly. Consequently, this operating strategy shows a high potential to increase the profitability of a PV-BESS.

Photovoltaic energy systems with battery storage for residential areas: an economic analysis

The global energy market is characterized by the strong growth of photovoltaic (PV) energy. This renewable source contributes to sustainable development and is a strategic player in the electricity market. The profitability of PV systems is determined by incentive tariffs in developing markets and by the share of self-consumption in developed markets.This paper aims to evaluate (i) the profitability of PV systems in the residential sector without subsidies and (ii) the profitability of energy storage in a mature market (Italy). In this way, it is possible to define the economic results of integrated PV-battery systems, and the indicator used is the Net Present Value. Furthermore, a sensitivity analysis is conducted on the critical variables.The mathematical model proposed in this paper defines the break-even point of the increase of self-consumption at which residential PV battery systems become economically viable in a mature market. Energy storage systems are useful only when the relationship between supply and demand permits them to induce a significant increase of energy self-consumption.

Smart charging of electric vehicles with photovoltaic power and vehicle-to-grid technology in a microgrid; a case study

Abstract We present a model developed to study the increase of self-consumption of photovoltaic (PV) power by smart charging of electric vehicles (EVs) and vehicle-to-grid (V2G) technology. Whereas previous studies mostly use large EV fleets in their models, our focus is on a smaller scale. We apply the model to a microgrid in Lombok, a residential neighbourhood in the city of Utrecht, the Netherlands. The microgrid consists of a 31 kWp PV installation, an office, internet servers, three households, and two EVs. Three control algorithms are presented which manage the charging profile of multiple EVs either in real-time or using linear optimisation with predictions for PV power and electricity demand. We perform one-year simulations using data for PV power, EV use, and electricity demand. Simulations results are evaluated on PV self-consumption and peak demand reduction. In addition, we make qualitative statements on battery degradation resulting from the charging strategies based on several indicators. We also simulate changes in microgrid composition, for example by including more EVs. In the simulations, self-consumption increases from 49% to 62–87% and demand peaks decrease by 27–67%. These results clearly demonstrate the benefits of smart charging EVs with PV power. Furthermore, our results give insight into the effect of different charging strategies and microgrid compositions.