Self-consumption Rate Research Articles

Analysis of Building Archetypes for Optimising New Photovoltaic Energy Facilities: A Case Study

Fuel poverty rates are high in southern Europe, particularly in social housing, despite the enormous potential for capturing solar power inherent in the roofs of apartment buildings. The in situ generation, distribution and consumption of photovoltaic energy carry obvious advantages including vastly improved efficiency attendant upon the reduction in distribution-related losses and costs, and the energy empowerment afforded lower income communities. The primary drawback is the imbalance between photovoltaic production patterns and users’ actual needs (peak consumption vs. peak generation). That mismatch is difficult to reconcile without resorting to energy storage or net metering, both of which entail grid involvement and greater management complexity. The present study introduces a methodology for analysing residential archetypes to determine the values of the parameters essential to optimising photovoltaic energy production and use. The aim is to determine where excess generation can be shared with other users in the vicinity and optimally pool residential rooftop facilities to meet community-scale energy demand, ultimately enhancing such disadvantaged neighbourhoods’ self-sufficiency. The case study discussed defines archetypes for just such a neighbourhood in Madrid, Spain. The solar energy production potential of the example is promising for its application in large southern European cities, with self-sufficiency rates obtained ranging from 15% to 25% and self-consumption rates from 61% to 80%.

Sodium sulfur batteries allocation in high renewable penetration microgrids using coronavirus herd immunity optimization

Energy storage batteries have been described as an ideal way to solve renewable energy problems, improve self-consumption rate (ScR), and pave the way for further growth in renewables penetration. In this work, an optimization framework is proposed to enhance a grid-connected microgrid performance in three stages. The first stage epitomizes maximization of the ScR of the highly-penetrated renewables hosted in the microgrid considered via sodium sulfur batteries allocation. The second stage epitomizes the minimization of the active power losses. The third stage epitomizes the calculation of the optimal energy management relying on diminishing the overall microgrid’s cost of operation depending on the optimal findings of the earlier two stages. The coronavirus herd immunity optimization algorithm is applied on MATLAB’s platform to solve the engineering problem formulated. Numerous linear and nonlinear constraints have been taken into account. The results have gotten validate the usefulness of the developed solutions and algorithm application.

In-use energy and carbon performance of a true zero carbon housing development in England

This paper systematically examines the in-use energy and carbon performance of a large case study housing development in England, designed to be net true zero carbon. Remote monitoring during a one-year period was used to gather high-frequency data on dwelling heat use, grid electricity use, solar PV electricity generation and export and community heating system performance. Based on data from 74 dwellings, mean energy use of 76 kWh/m2/year and electricity use of 27.4 kWh/m2/year per dwelling placed the case study among the lowest energy housing developments in the UK. Nonetheless, heat usage and designed fabric efficiency fell short compared to other true zero carbon housing. The mean self-consumption rate of generated energy of 23% calls for the provision of home batteries. Heat usage variance was more prominent compared to findings in other studies. Based on the 2018/19 carbon factors, dwellings emitted 20.2 kgCO2e/m2/year on average, missing the zero carbon target. As found in other studies, this was attributed to the underperforming community heating system. This study comes timely in the context of the widespread calls for net zero carbon dwellings. The findings confirm the argument that the anticipated mainstreaming of zero carbon dwellings demands shifting toward an outcome-focused design approach.

Decarbonizing heat with PV-coupled heat pumps supported by electricity and heat storage: Impacts and trade-offs for prosumers and the grid

Heat pumps play an important role in decarbonizing the heating supply of buildings and they allow to increase the self-consumption of PV electricity, especially when supported by electricity or heat storage. In this study, we develop an open-source model to optimize PV-coupled heat pumps, with and without electricity and heat storage, and we compare their performance for three types of single-family houses with different thermal envelope quality paired with 549 electricity profiles. We analyze trade-offs between prosumer benefits and grid impacts, namely bill minimization, and maximum grid relief, depending on the type of storage and incentives for grid peak reduction (i.e., a capacity-based tariff). We conclude that the use of heat storage reduces the levelized cost of meeting the electricity demand between 13–26% compared to the baseline case without storage, in particular when heat pumps are used for both space heating and domestic hot water (DHW). Regarding total self-consumption rates, both storage technologies, namely batteries and hot water tanks (which supply both space heating and DHW) achieve similar rates ranging between 30–39%. In contrast, batteries are found to be very effective in reducing the peak demand (14–17% compared to the baseline scenario), but only if the retail tariff has a capacity-based component. Interestingly, the quality of the envelope plays a key role and heat pumps can double the power peak demand in poorly insulated houses, with thermal storage increasing the power peak demand further up to 8%, compared to the baseline, regardless of the storage technology. Thus, we conclude that policy makers should promote thermal retrofitting of the building stock to avoid the upgrading of the distribution grid.

Profitability Assessment of Residential Photovoltaic Battery Systems in Japan Using Electric Power Big Data

Residential photovoltaic (PV) battery systems are key technology in the design of low-carbon and resilient energy systems; however, limited research has assessed their profitability. This study aims to evaluate the economic performance of PV battery systems for end-users. The evaluation takes geological, technological, and socio-economic factors into consideration, thereby making the evaluation more comprehensive. We used PV power generation data and power consumption data of more than 40,000 all-electric houses in Japan. We performed scenario analyses with a sensitivity analysis. The results showed that residential PV battery systems were highly profitable when their storage battery operation modes were appropriately utilized at the end of the purchase period for solar power generation in Japan’s feed-in-tariff (FIT) scheme. The profitability, however, varied across regions. The results also indicated that the PV self-consumption rate was more than 50% when charging the battery with surplus power. The results of the sensitivity analysis suggested that the unit prices of grid electricity and the purchasing price of surplus power after the FIT scheme had a significant effect on the profitability of residential PV battery systems.

Adoption behaviour and the optimal feed-in-tariff for residential solar energy production in Darwin (Australia)

Small-scale solar energy production on rooftops can contribute to renewable energy targets and reduce domestic energy costs. However, installation rates are low in some cities despite abundant sunshine and generous financial incentives. In this study a drop-off survey was carried out to investigate the intentions and barriers to adopting rooftop solar panels in the remote tropical city of Darwin, in the Northern Territory (NT), and to quantify the minimum feed-in-tariff (FiT) needed to install residential solar panels. More than half of the 652 respondents intended to install solar panels. Age and renting were negatively, and high energy needs and an estimated short payback period positively, associated with installation intentions. Each additional year that potential adopters expect to take paying off panels reduces their likelihood to install them by 10%. Results of a contingent valuation assessing the minimum FiT needed for people to newly adopt solar panels showed that the median amount needed was 14.40 c/kWh (95% confidence interval: 10.74–25.83 cents). This was almost half that offered at the time of the survey (a premium FiT of around 26 c/kWh, GST inclusive) but more than the new FiT that has been introduced since (9 c/kWh, GST inclusive). There is the option that the new FiT could be augmented by a subsidised part to provide enough incentives for potential adopters. Under the new FiT, the likelihood of installing solar panels is highly dependent on the self-consumption rate of the solar energy and affordability of batteries for storage. An ex-ante evaluation showed that, if everything else remains the same, the adoption rate can be expected to decline by about 40% or 17% for people consuming 30% or 60%, respectively, of the solar energy themselves.

Identifying Challenges in Engaging Users to Increase Self-Consumption of Electricity in Microgrids

A microgrid’s self-consumption rate reflects its ability to retain its own energy and decrease its reliance on the synchronous grid. This paper investigates the empirical case of a microgrid equipped with photovoltaic (PV) panels and identifies challenges in engaging the microgrid’s users to increase their self-consumption. Accordingly, we explored both the physical and social dimensions of the microgrid. The former involved mapping the electricity consumption and production through an exploratory data analysis, and evaluating the associated price signals, while the latter involved the use of design interventions to explore users’ perceptions of the system. We highlight the problem of price signal impedance, the need for cost reflective pricing and the challenge in designing and extending internal price models in settings with various actors. We address the limitations of price signals, alongside alternative unidimensional signals, and emphasize the need for an integrated approach to a user engagement strategy as well as the challenges that this approach entails. Our results shed light on the complexity of energy communities such as microgrids, and why their implementation can introduce multidimensional challenges that demand cross-disciplinary approaches.

Enhanced Sizing Methodology for the Renewable Energy Sources and the Battery Storage System in a Nearly Zero Energy Building

The aim of this article is to present a novel methodology to determine the correct size of the renewable energy sources (RES) and the battery storage system (BSS) that are needed to effectively convert a conventional residential building into a nearly zero-energy building (nZEB). This is attained by properly considering the long-term history of the weather at the location of the building, the energy consumption of the appliances and the performance of the energy management system (EMS). The above are embedded in a cost function that balances the impact factors which highly affect the size and have considerable effect on the reliability and lifespan of the RES and BSS in a nZEB, i.e., the depreciation of the initial investment, the self-consumption rate, the feed-in rate, the simultaneity in generating and consuming power, and the impacts of the depth-of-discharge and the discharge power on the BSS's state-of-health. Therefore, the correct sizing of RES and BSS is provided by considering both the effectiveness and the economic point of views. Specifically, the optimal solution is attained by minimizing the above cost function through the genetic algorithm technique. The effectiveness, functionality and practicality of the proposed methodology have been validated on a pilot nZEB.

Impact of distribution tariffs on prosumer demand response

Distributed energy resources (DERs) may enable prosumers to deliver demand response under dynamic energy pricing schemes. Facing wholesale market prices, the DER scheduling of a profit-maximising prosumer minimises the total system energy cost as well. However, regulated electricity bill components, i.a., distribution tariffs for recovering grid costs, may distort these price signals. To study the impact of distribution tariff structures on DER scheduling, we develop a short-term linear optimisation model that determines the cost-optimal DER schedule based on wholesale electricity prices and a distribution tariff. We compare five distribution tariff structures for four combinations of PV, batteries, and heat pumps, and define two metrics to characterise the results: (i) the novel ‘relative flexibility value’, which quantifies energy cost inefficiencies, and (ii) ‘rate of self-consumption’. In a case study, we show how prosumers make trade-offs between energy and distribution costs, depending on the distribution tariff structure. We describe the mechanisms through which different distribution tariff structures alter DER operations, and quantify the tariffs' impact on the system energy cost. Generally, we find that tariff types which stimulate self-consumption increase the system energy cost and vice versa. • Distribution tariffs distort the scheduling of distributed energy resources. • Prosumers trade off energy cost increases with distribution cost decreases. • Self-consumption can reduce grid interaction and related private costs. • Tariffs with high self-consumption perform low on cost-efficiency and vice versa.

Two-level hierarchical model predictive control with an optimised cost function for energy management in building microgrids

Hybrid energy storage systems have been increasingly envisaged for building microgrids to soften the drawbacks arising from the unpredictability of renewable energy resources and dwelling occupancy. The combination of long- and short-term energy storage systems can enhance the building microgrid capacity of shifting the demand peak toward periods of power generation, increasing the marks of self-consumption rate. However, the design of energy management systems for hybrid energy storage microgrids is more complex than single ones due to a greater number possible solutions. Faced with this issue, this paper proposes a two-level Hierarchical Model Predictive Controller (HMPC) enhanced by two data-driven modules to improve the performance of building microgrids equipped with hybrid energy storage continuously and automatically. With minimum pre-design steps, the two data-driven algorithms improve the accuracy of Li-ion batteries and hydrogen storage models and determine adequate parameters for the HMPC cost function. Relying predominantly on data measurements, the proposed hierarchical controller determines which energy storage device must be run on a daily basis based on the estimation of the annual self-consumption rate and the annual microgrid operation costs. This real-time analysis decreases microgrid expenditure because it avoids grid penalisation regarding the energy autonomy index and reduces the degradation and maintenance of energy storage devices. Compared to a standard rule-based strategy, the proposed controller reduces annual costs up to 5% in residential buildings and 9% in non-residential ones. In contrast, compared to a conventional HMPC the annual expenditure is reduced from 1% to 7% in both types of buildings.

Modeling Energy Communities with Collective Photovoltaic Self-Consumption: Synergies between a Small City and a Winery in Portugal

The recently approved regulation on Energy Communities in Europe is paving the way for new collective forms of energy consumption and production, mainly based on photovoltaics. However, energy modeling approaches that can adequately evaluate the impact of these new regulations on energy community configurations are still lacking, particularly with regards to the grid tariffs imposed on collective systems. Thus, the present work models three different energy community configurations sustained on collective photovoltaics self-consumption for a small city in southern Portugal. This energy community, which integrates the city consumers and a local winery, was modeled using the Python-based Calliope framework. Using real electricity demand data from power transformers and an actual winery, the techno-economic feasibility of each configuration was assessed. Results show that all collective arrangements can promote a higher penetration of photovoltaic capacity (up to 23%) and a modest reduction in the overall cost of electricity (up to 8%). However, there are clear trade-offs between the different pathways: more centralized configurations have 53% lower installation costs but are more sensitive to grid use costs (which can represent up to 74% of the total system costs). Moreover, key actor’s individual self-consumption rate may decrease by 10% in order to benefit the energy community as a whole.

Technical and Economic Analysis of Battery Storage for Residential Solar Photovoltaic Systems in the Brazilian Regulatory Context

This paper presents a comprehensive study of the technical and economic benefits that a typical residential prosumer may experience when investing in a solar photovoltaic (PV) system with a battery energy storage system (BESS). To this end, a home energy management system has been designed to simulate the prosumer’s daily operation, considering a novel method for calculating battery degradation while minimizing its operating costs. In order to contribute to the regulatory review process of the distributed generation underway in Brazil, a set of PV+BESS configurations has been assessed under the current and future regulatory scenarios proposed for discussion by the Brazilian regulatory agency. Although the results demonstrate that the prosumer’s self-consumption rate may increase up to 14% with the BESS coupling in the PV system, the investment proved to be economically unattractive in the current regulatory scenario and practically unfeasible in any of the proposed future scenarios. To make PV+BESS systems economically feasible, some business models are proposed and discussed, and for example, provide subsidies for policymakers, financial agents, and battery manufacturers. A sensitivity analysis for each business model showing its economic feasibility spectrum is provided to assist the different sector players, especially the consumers, in their decision-making process.

Optimal Allocation and Economic Analysis of Battery Energy Storage Systems: Self-Consumption Rate and Hosting Capacity Enhancement for Microgrids with High Renewable Penetration

Recent advances in using renewable energy resources make them more accessible and prevalent in microgrids (MGs) and nano grids (NGs) applications. Accordingly, much attention has been paid during the past few years to design and operate MGs with high renewable energy sources (RESs) penetration. Energy storage (ES) is the crucial enabler for reliable MG operation to help MGs become more resistant to disruptions, particularly with the increased penetration of RESs. In this regard, this paper formulates a two-stage optimization framework to improve a grid-connected MG performance. Firstly, the optimal allocation decisions of the battery ES systems (BESSs) are provided to enhance the self-consumption rate of the RESs and the hosting capacity (HC) of the MG. Secondly, an operation strategy with the results (number, location, and capacity) of the BESSs obtained from the first stage is handled as an objective function to minimize the MG’s total operation cost. The IEEE 33-bus radial system is modified to act as the MG with high RESs penetration. The problem is solved using a recent swarm intelligence optimization algorithm called the Harris hawks optimization (HHO) algorithm. The proposed optimal operation strategy considers numerous constraints, such as the charge-discharge balance, number and capacity limitations of the BESSs, and the different technical performance constraints of the MG. The results obtained verify the proposed optimization framework’s effectiveness for grid-connected MGs and validate the benefits gained from the appropriate allocation of BESSs. The results also indicate that oversized storage or using many unneeded storage units may adversely influence the MG’s total power losses.

Experimental Investigation and Energy Performance Simulation of Mongolian Ger with ETS Heater and Solar PV in Ulaanbaatar City

There are approximately 200,000 households living in detached houses and gers (yurts) with small coal stoves that burn raw coal in Ulaanbaatar city. A proper heating system and improvement of the energy efficiency of residential dwellings are vitally important for Ulaanbaatar city to reduce air pollution as well as for the operation of the current central energy system. This study shows the experimental results for two gers with two different heating systems and different thermal insulation, for investigating the merits of each. The technical feasibility of the system consisting of an electric thermal storage (ETS) heater with a daytime charging schedule and areal photovoltaic (PV) system was also examined by using a simulation with software developed in MATLAB (R2020a, MathWorks, USA). As a result of the experiment, the indoor comfort level and energy efficiency of the ger with added insulation and an ETS heater with nighttime charging were shown to be enhanced compared with those of the reference ger. The ger with added insulation and the ETS heater consumed 3169 kWh for electric appliances and 5989 kWh for the heating season. The simulation showed that the PV self-consumption rate is 76% for the Ger 2 with the ETS heater because of the daytime charging schedule of the ETS heater. The PV system supplied 31% of the total energy consumed, with the remaining 69% from the main grid.

Opportunities and challenges for the use of photovoltaics in building monuments – Case Study TU Dresden

Increasing urbanization leads to a higher energy demand, while space to generate renewable energy locally is scarce. With harvesting solar energy providing the largest potential for renewable energy generation, to move towards a self-sufficient city as per UN SDG 7, even difficult roofs have to be covered with photovoltaics (PV), including existing heritage building stock. Strict monument conservation requirements however prohibit changes to the building that affect its visible appearance. In this paper examples of existing PV on heritage buildings around Dresden are presented, and a PV in-roof system that blends in is visualized for a heritage TU Dresden (TUD) building. Using TUD’s buildings as a case study, opportunities and challenges of regenerative electricity generation on TUD heritage buildings are discussed. Covering the considered TUD area with PV, a large CO2-emission reduction is feasible. For a Self-consumption rate of 70-100%, which seems realistic for the TUD due to the high daytime equipment power and its campus power network that allows buildings to distribute a surplus of generated power to other campus buildings, the payback time is favourable.

Economic Assessment of Solar-Powered Residential Battery Energy Storage Systems: The Case of Madeira Island, Portugal

This paper presents an economic assessment of introducing solar-powered residential battery energy storage in the Madeira Island electric grid, where only micro-production for self-consumption is currently allowed. The evaluation was conducted against six local micro-producers using one year of energy consumption and solar photovoltaic production measurements and two distinct storage control strategies. Several inverter sizes and storage capacities were considered based on the six micro-producers’ consumption and production profiles. The results were then analyzed concerning year-long simulations and a projection for the next ten years. To this end, several indicators were assessed, including self-consumption, profit per Euro invested, number of cycles and storage degradation. The results obtained show that, despite the benefits of storage to increase the self-consumption rates, considerable drops in the storage prices are still necessary to achieve profitability during these devices’ lifetime. Furthermore, our results also highlight a very interesting trade-off between self-consumption, pre-charge and profitability, in a sense that higher levels of pre-charge increase the chances of reaching profitability even though this will imply considerable drops in the levels of self-consumption.

Effect of Sampling Rate on Photovoltaic Self-Consumption in Load Shifting Simulations

Grid-connected photovoltaic (PV) capacity is increasing and is currently estimated to account for 3.0% of worldwide energy generation. One strategy to balance fluctuating PV power is to incentivize self-consumption by shifting certain loads. The potential improvement in the amount of self-consumption is usually estimated using smart meter and PV production data. Smart meter data are usually available only at sampling frequences far below the Nyquist limit. In this paper we investigate how this insufficient sampling rate affects the estimated self-consumption potential of shiftable household appliances (washing machines, tumble dryers and dishwashers). We base our analyses on measured consumption data from 16 households in the UK and corresponding PV data. We found that the simulated results have a marked dependence on the data sampling rate. The amount of self-consumed energy estimated with data sampled every 10 min was overestimated by 30–40% compared to estimations using data with 1 min sampling rate. We therefore recommend to take this factor into account when making predictions on the impact of appliance load shifting on the rate of self-consumption.

Prices in the Egyptian seafood market: insights for fisheries management and food security

Reliable information on seafood prices is essential for managing fisheries resources in a sustainable way and therefore to secure seafood sustainability. Unlike other aquaculture producing countries, Egypt does not export its production, which led to a very high self-consumption rate. These characteristics of the Egyptian seafood market make Egypt an atypical country in the region. This paper is the first attempt to analyse seafood prices and their temporal variation (2013-2018) in the Egyptian seafood market, as well as the evolution (1997-2018) of consumption per capita, the national self-sufficiency ratio (SSR) of seafood, consumer price index (CPI) and inflation rate in seafood prices. A steady increase in the overall seafood average price was observed until 2017 when prices almost doubled due to the devaluation of the Egyptian pound, and tripled in 2018. During the year, prices do not vary between months; except for slight peaks in April, August, October, and November, being maximal in December. Variation in seafood average prices are highest on Thursday and Friday. The average consumption in 2018 was 22.98 kg of seafood products per capita, reaching the highest rate in the last two decades. The self-sufficiency ratio (SSR) reached its maximum in 2009 at 90.64%. Despite an almost doubling of production from 1,093 thousand tonnes in 2009 to 1,935 thousand tonnes in 2018 the SSR has decreased to 86.66%. This analysis suggests that the current trends of annual increase in seafood prices exacerbate vulnerability to food security.

High resolution stochastic generator of European household specific electricity demand load curves for decentralized power self-production applications

This work relates to a new stochastic and probabilistic tool allowing to model dwellings specific electricity load profiles (in the European context) for 39 different electrical appliances with a high temporal resolution (2-min time step). This tool was developed by using probabilistic (Monte Carlo) and statistic (Time Of Use curves) methods as well as transition probabilities (Markov chains), seasonal, daily and hourly effects coefficients to obtain the more realistic as possible electricity load curves. The tool distinguishes the flexible part which can be shifted during power self-production operation (micro combined heat and power µCHP or photovoltaic panels PV) periods and the no flexible part (lighting for example). A sensitivity analysis shows the impact of the time step and the repeatability level of the tool on a µCHP system coupled with a building to prove the need to use high resolution electricity demand load curves at low scale (a building) in comparison with hourly data which can overestimate µCHP electrical generation self-consumption rate up to 20%. Time step of maximum 2 min is required for the electricity demand profiles to obtain reliable results on energetic indicators. Finally, a validation procedure based on literature review profiles, high resolution in situ measurements and expansion national load curves is carried out.

Prefeasibility study of a distributed photovoltaic system with pumped hydro storage for residential buildings

Distributed renewable energy systems are vital for satisfying the increasing demand for electricity in cities due to an influx of people. Nowadays, the residential buildings in metropolitan cities like Shanghai have natural height differences for potential energy, this advantage has not yet been fully exploited currently. To better utilize renewable energy, a grid-connected photovoltaic with pumped hydro storage system is first proposed for residential buildings, the operation principle of this system is then developed. Under Shanghai's time-of-use electricity price policy, the proposed methodology is applied in a case study to investigate the techno-economic feasibility of its application on villa and apartment residential buildings. Moreover, some technical indicators, such as self-consumption rate and self-sufficiency rate, are employed to evaluate the performance of the proposed methodology under different scenarios. The results demonstrate that the pumped hydro storage system on the apartment buildings can absorb more surplus power (4.83 kW h/d) from the photovoltaic system than on the villa buildings, meanwhile, it can also release more power (3.69 kW h/d) to meet the load demand. For residents of villa buildings and apartment buildings, the initial total investment is 35,417 and 36,423 Chinese yuan, respectively, while the payback periods are 9.01 and 7.06 years respectively. Moreover, a sensitivity analysis is conducted for the apartment buildings, revealing that the photovoltaic capacity and load demand are the two key parameters affecting the cost and revenue of trading with the grid. A 25% increase in photovoltaic capacity can produce 123.3% higher net revenue value than the base case, and a 25% increase in load demand leads to a 102.7% decrease in net revenue. The variations in building height and upper reservoir volume have a marginal impact on net revenue compared with photovoltaic capacity and load demand.