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This paper aims to forecast the availability of used but operational electric vehicle (EV) batteries to integrate them into a circular economy concept of EVs' end-of-life (EOL) phase. Since EVs currently on the roads will become obsolete after 2030, this study focuses on the 2030–2040 period and links future renewable electricity production with the potential for storing it into used EVs' batteries. Even though battery capacity decreases by 80% or less, these batteries will remain operational and can still be seen as a valuable solution for storing peaks of renewable energy production beyond EV EOL.

Storing renewable electricity is gaining as much attention as increasing its production and share. However, storing it in new batteries can be expensive as well as material and energy-intensive; therefore, existing capacities should be considered. The use of battery electric vehicles (BEVs) is among the most exciting concepts on how to achieve it. Since reduced battery capacity decreases car manufacturers' interest in battery reuse and recycling is environmentally hazardous, these batteries should be integrated into the future electricity storage system. Extending the life cycle of batteries from EVs beyond the EV's life cycle is identified as a potential solution for both BEVEOL and electricity storage.

Results revealed a rise of photovoltaic (PV) solar power plants and an increasing number of EVs EOL that will have to be considered. It was forecasted that 6.27–7.22% of electricity from PV systems in scenario A (if EV lifetime is predicted to be 20 years) and 18.82–21.68% of electricity from PV systems in scenario B (if EV lifetime is predicted to be 20 years) could be stored in batteries. Storing electricity in EV batteries beyond EV EOL would significantly decrease the need for raw materials, increase energy system and EV sustainability performance simultaneously and enable leaner and more efficient electricity production and distribution network.

Storing electricity in used batteries would significantly decrease the need for primary materials as well as optimizing lean and efficient electricity production network.

Energy storage is one of the priorities of energy companies but can be expensive as well as material and energy-intensive. The use of BEV is among the most interesting concepts on how to achieve it, but they are considered only when in the use phase as vehicle to grid (V2G) concept. Because reduced battery capacity decreases the interest of car manufacturers to reuse batteries and recycling is environmentally risky, these batteries should be used for storing, especially renewable electricity peaks. Extending the life cycle of batteries beyond the EV's life cycle is identified as a potential solution for both BEV EOL and energy system sustainability, enabling more efficient energy management performance. The idea itself along with forecasting its potential is the main novelty of this paper.

Rapidly increasing the proportion of installed wind power capacity with zero carbon emission characteristics will help adjust the energy structure and support the realization of carbon neutrality targets. The intermittency of wind resources and fluctuations in electricity demand has exacerbated the contradiction between power supply and demand. The time-of-use pricing and supply-side allocation of energy storage power stations will help “peak shaving and valley filling” and reduce the gap between power supply and demand. To this end, this paper constructs a decision-making model for the capacity investment of energy storage power stations under time-of-use pricing, which is intended to provide a reference for scientific decision-making on electricity prices and energy storage power station capacity.

Based on the research framework of time-of-use pricing, this paper constructs a profit-maximizing electricity price and capacity investment decision model of energy storage power station for flat pricing and time-of-use pricing respectively. In the process, this study considers the dual uncertain scenarios of intermittency of wind resources and random fluctuations in power demand.

(1) Investment in energy storage power stations is the optimal decision. Time-of-use pricing will reduce the optimal capacity of the energy storage power station. (2) The optimal capacity of the energy storage power station and optimal electricity price are related to factors such as the intermittency of wind resources, the unit investment cost, the price sensitivities of the demand, the proportion of time-of-use pricing and the thermal power price. (3) The carbon emission level is affected by the intermittency of wind resources, price sensitivities of the demand and the proportion of time-of-use pricing. Incentive policies can always reduce carbon emission levels.

This paper creatively introduced the research framework of time-of-use pricing into the capacity decision-making of energy storage power stations, and considering the influence of wind power intermittentness and power demand fluctuations, constructed the capacity investment decision model of energy storage power stations under different pricing methods, and compared the impact of pricing methods on optimal energy storage power station capacity and carbon emissions.

1. Electricity pricing and capacity of energy storage power stations in an uncertain electricity market.

2. Investment strategy of energy storage power stations on the supply side of wind power generators.

3. Impact of pricing method on the investment decisions of energy storage power stations.

4. Impact of pricing method, energy storage investment and incentive policies on carbon emissions.

5. A two-stage wind power supply chain including energy storage power stations.

Electricity pricing and capacity of energy storage power stations in an uncertain electricity market.

Investment strategy of energy storage power stations on the supply side of wind power generators.

Impact of pricing method on the investment decisions of energy storage power stations.

Impact of pricing method, energy storage investment and incentive policies on carbon emissions.

A two-stage wind power supply chain including energy storage power stations.

The ongoing urbanization and decarbonization require deployment of energy storage in the urban energy system to integrate large-scale variable renewable energy (VRE) into the power grids. The cost reductions of batteries enable private entities to invest energy storage for energy management whose operating strategy may differ from traditional storage facilities. This study aims to investigate the impacts of energy storage on the power system with different operation strategies. Two strategies are modeled through a simulation-based regional economic power dispatch model. The profit-oriented strategy denotes the storage system operated by private entities for price arbitrage, and the nonprofit-oriented strategy denotes the storage system dispatched by an independent system operator (ISO) for the whole power system optimization. A case study of Jiangsu, China is conducted. The results show that the profit-oriented strategy only has a very limited impact on the cost reductions of power system and may even increase the cost for consumers. While nonprofit-oriented energy storage performs a positive effect on the system cost reduction. CO₂ emission reduction can only be achieved under a high VRE scenario for energy storage. Integrating energy storage into the power system may increase CO₂ emissions in the near term. In addition, the peak-valley spread is crucial to trigger operations of profit-oriented energy storage, and the profitability of energy storage operator is observed to be decreasing with the total storage capacity. This study provides new insights for the energy management in the smart city, and the modeling framework can be applied to regions with different resource endowments.

The authors characterize two battery storage operating strategies of profit- and nonprofit-oriented by adopting a simulation-based economic dispatch model. A simulation from 36 years of hourly weather data of wind and solar output from case study of Jiangsu, China is conducted.

The results show that the profit-oriented strategy only has a very limited impact on the cost reductions of power system and may even increase the cost for consumers. While nonprofit-oriented energy storage performs a positive effect on the system cost reduction. CO₂ emission reduction can only be achieved under high VRE scenario for energy storage. Integrating energy storage into the power system may increase CO₂ emissions in the near term. In addition, the peak-valley spread is crucial to trigger operations of profit-oriented energy storage, and the profitability of energy storage operator is observed to be decreasing with the total storage capacity.

This study provides new insights for the energy management in the smart city, and the modeling framework can be applied to regions with different resource endowments.

In order to compliment the growing use of renewable energies in the US, additional technologies must be employed on the bulk power system. This paper aims to forecast the most probable energy storage technologies.

The methodology was deployed in two steps: evaluate the potential energy storage technologies that could complement a wind turbine or photovoltaic system; and forecast which of these technologies is best poised to become a viable solution to the energy storage problem facing these renewable technologies.

Based on the publication and patent data, compressed air energy is set to be the fastest growing complimentary technology to wind energy. Two of these types of plants are currently in existence today as mentioned previously indicating the technology is commercially available. This technology has great potential; however, implementing this technology involves finding or creating underground airtight caverns in usable locations.

The number of variables have been limited due to the methodologies chosen for this analysis. The research can be expanded using other criteria such as cost, cost of capital, economies of scale, environmental concerns, social and political constraints.

This paper provides an assessment that was indicated as necessary by those who identified the need for the development of energy storage technologies for future electricity generation.

Pumped-storage hydroelectricity (PSH) is considered as an effective method to moderate the difference in demand and supply of electricity. This study aims to understanding of the high capacity of energy production, storage and permanent exploitation has been the prominent feature of pumped-storage hydroelectricity.

In this paper, the optimization of energy production and maintenance costs in one of the large Iranian PSH has been discussed. Hence, a mathematical model mixed integer nonlinear programming developed in this area. Minimizing the difference in supply and demand in the energy production network to multiple energies has been exploited to optimal attainment scheme. To evaluate the model, exact solution CPLEX and to solve the proposed programming model, the efficient metaheuristics are utilized by the tuned parameters achieved from the Taguchi approach. Further analysis of the parameters of the problem is conducted to verify the model behavior in various test problems.

The results of this paper have shown that the meta-heuristic algorithm has been done in a suitable time, despite the approximation of the optimal answer, and the consequences of research indicate that the model proposed in the studied power plant is applicable.

In pumped-storage hydroelectricity plants, one of the main challenges in energy production issues is the development of production, maintenance and repair scheduling concepts that improves plant efficiency. To evaluate the mathematical model presented, exact solution CPLEX and to solve the proposed bi-objective mixed-integer linear programming model, set of efficient metaheuristics are used. Therefore, according to the level of optimization performed in the case study, it has caused the improvement of planning by 7%–12% and effective optimization processes.

This paper aims to present a forecast for renewable energy production in the USA. Growth curves are used to conduct the forecasts.

The analysis is based upon a literature review, supplemented by collection of secondary data. The study then focuses on applying the Pearl growth curve.

The authors' results show that biomass energy production is growing the fastest followed by geothermal and wind. Additionally, the forecast for solar energy production shows little to no growth over the next two decades.

If the US government hopes to achieve its goals in renewable energy, considerable funding and incentives will have to be put forth to accelerate the growth of renewable energy. Since the biomass technology is already growing nicely it makes sense to put the additional resources behind the other three technologies to close the 10.3 percent gap being forecasted. The government also needs to put more funding into dual renewable plants such as wind or solar combines with pumped hydro, this will ensure environmental and reliability are both maintained. Finally, for renewable energies to be competitive in the long term, considerable research needs to go into driving down the cost so there is not a need for subsidies.

This study provides value in providing a forecast for expected future growth for renewable energy sources.

The purpose of this paper is to investigate the impact of market orientation (MO) on the major determinants of commercialization behavior among Sub-Saharan smallholders. The study addresses the shortfalls in prior research on smallholder commercialization, which makes little difference between MO and market participation (MP).

The study reports on an empirical data set of 272 vegetable growers from Kiambu West District in Kenya and employs a partial least squares structural equation approach to test the hypotheses.

The results evidence that MO: fosters farmers’ ability to create value within commodity markets by capitalizing on market opportunities; changes the way in which farmers perceive the role of institution and infrastructure support and; and develops a drive for adopting business approach in farming operations.

Fostering commercialization behavior among smallholders in Kenya requires implementing a two-pronged approach: improving MO to adopt business approach in farming operations; and facilitating MP at output level. The major limitation of this study is data collected only from high value vegetable producers in Kenya, signifying a need to include other agriculture produce across different Sub-Saharan countries.

Research on smallholder agriculture is replete with investigating institutional and technical constraints to make smallholders more productive, however, research on MO to adopt business approach in farming operations is scant. This study emphasizes that understanding MO, as a distinct and separate concept from MP, is vital for scaling up business approach among smallholder farmers.

Continual cost reduction of overhead costs of building projects can realign the concept of post-contract cost control towards value-driven construction projects and stakeholders’ satisfaction. This study synthesised and analysed the viable continuous improvement measures critical for waste reduction during the execution phase of a building project.

A review of existing literature facilitated a list of continuous improvement measures. This literature review findings enabled a Likert-scale questionnaire which was administered to two-hundred and fifty (250) small- and medium-scale construction companies (SMSCC) in Nigeria. Multiple linear regression statistical tests deduced the significant cost reduction measure from which a causal loop diagram was designed to indicate continuous improvement measures during the execution phase of a building project.

Cogent construction activities associated with overhead costs were deduced from the statistical tests as being payment of suppliers and sub-contractors and purchase orders. An all-inclusive casual loop model for cost reduction through waste minimisation in construction projects as a viable oriented mechanism for meeting clients' requirements was developed.

The causal loop continuous improvement model recognised external and internal factors which are crucial for SMSCC to focus on for their organisational growth and performance enhancement.

A focus on non-physical waste in construction organisations potentially addresses behavioural challenges for continuous improvement.

The purpose of this study was to design a renovation plan for a university campus building (Department of Electrical and Computer Engineering) with the aim to achieve nearly zero energy performance, ensuring a low specific demand (lower than 44 kWh/m²) and a high level of on-site renewable generation (equivalent to more than 20 per cent of the energy demand).

The baseline demand was characterized based on energy audits, on smart metering data and on the existing building management system data, showing a recent reduction of the electricity demand owing to some implemented measures. The renovation plan was then designed with two main measures, the total replacement of the actual lighting by LEDs and the installation of a photovoltaic system (PV) with 78.8 kWp coupled with an energy storage system with 100 kWh of lithium-ion batteries.

The designed renovation achieved energy savings of 20 per cent, with 27.5 per cent of the consumed energy supplied by the PV system. This will ensure a reduction of the specific energy of the building to only 30 kWh/m², with 42.4 per cent savings on the net-energy demand.

The designed renovation proves that it is possible to achieve nearly zero energy goals with cost-effective solutions, presenting the lighting renovation and the solar PV generation system a payback of 2.3 and 6.9 years, respectively.

This study innovated by defining ambitious goals to achieve nearly zero energy levels and presenting a design based on a comprehensive lighting retrofit and PV generation, whereas other studies are mostly based on envelope refurbishment and behaviour changes.