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Introduction of demand response (DR) programs could help improve the overall power system stability, even out energy valleys and also push the prices lower due to the increased competitiveness. Liberalization of electricity markets provides possibilities for load aggregators to schedule consumption and obtain revenue by direct participation in demand response programs. This paper proposes a robust algorithm for aggregation of flexible loads within the same distribution network. Participation in DR programs is investigated considering electric vehicle (EV) located at the same carpark. Battery aging is considered and a utilization compensation scheme is proposed for EV drivers. A robust algorithm based on a receding horizon linear problem is designed for the load aggregator considering EV constraints, price uncertainties, and battery aging.

Abstract Blue carbon produced by marine ranching has tremendous economic and ecological value. A sound blue carbon trading mechanism, a fair market environment, and an effective supervision framework will help to transform and upgrade the marine economy through blue carbon trading. The present study develops a three-party evolutionary game model, that consists of the government supervisory agency, the blue carbon trading platform, and the news media, to analyse the evolutionary equilibrium conditions and each party’s evolutionarily stable strategy. It also performs numerical simulations on the evolution strategies. The study results demonstrate: (1) More strict supervision from the government will prevent the platform from engaging in opportunistic behaviours, and ensure fairness in blue carbon trading. (2) The news media’s participation as a watchdog can play a role in restraining the platform’s non-compliance behaviours, but a free-rider issue may also arise, which leads to an absence of supervision. (3) Consumers’ recognition of marine ranching products and the proportion of blue carbon produced by marine ranching that is available for trading will indirectly affect the platform’s course of action. Lastly, the paper makes policy recommendations for the development of a well-functioning blue carbon trading mechanism, a fair market environment, and an effective supervision framework.

Currently, Hybrid Power Systems (HPS) have been shown as an excellent opportunity for generation of electricity. This paper presents the study of a hybrid system considering two energy sources (solar - biogas) available in the city Ilhabela island in the state of Sao Paulo - Brazil. This system will supply electricity to electric vehicles. The study is based on the calculation of the energy demand of the electric vehicles on the island. Then the capacity of biogas production in Ilhabela is determined. Subsequently, in order to know the energy produced and the amount of biogas needed by the microturbine, an energy analysis of this plant is carried out. Last, the energy needed to be generated with the photovoltaic plant is calculated. The results show that, considering a market insertion index of 4% of electric vehicles, the average energy demand is 46.327 kWh/month. On the other hand, the amount of biogas produced on the island is twice that needed to generate 16.200 kWh/month. Finally, the solar plant will produce 30.127 kWh/month.

Electric hybridization technologies appear to be one of the most promising approaches to improving the energy efficiency of buses; however, this improvement has not been systematically quantified. A fuel consumption model is essential for capturing fuel consumption behavior accurately and quantifying the fuel benefits of hybrid buses. Consequently, the objective of this study was to develop a fuel consumption model for hybrid buses on the basis of the framework of the Virginia Tech Transportation Institute’s comprehensive power-based fuel consumption model and then to quantify the benefits associated with hybridization technologies relative to conventional diesel bus operations. The model estimates were demonstrated to be consistent with in-field measurements, and the optimum fuel economy cruise speed was demonstrated to be approximately 50 km/h. The results demonstrate that hybrid buses consumed less fuel overall, while heavier buses and higher passenger loads may have reduced the fuel savings. The results also reveal that more fuel savings could be achieved for cruise and stop-and-go activity compared with idling behavior and that stop-and-go operation generated the highest level of fuel efficiency benefits. The conclusions of this paper can support bus planning applications to achieve fleet fuel savings.

Motor vehicle ownership and utilization are growing rapidly in Asia, because of rapid urbanization and growing urban incomes. This sudden growth is resulting in increasing traffic congestion, fuel use, and CO2 emissions and in deteriorating air quality. This paper presents a common framework to explore scenarios of vehicle and energy use and emissions in three South Asian cities: Bangalore, India; Colombo, Sri Lanka; and Dhaka, Bangladesh. Scenarios are built by separately analyzing transportation activity (in tonne kilometers or passenger kilometers), modal structure (i.e., share of tonne kilometers or passenger kilometers occurring on each mode), modal energy intensity (in energy burned per tonne kilometer or passenger kilometer), and emission factors. Although the types of data available across cities vary widely and there are deficiencies and inconsistencies in the available data, the analysis suggests that motor vehicle use would roughly double in each city by 2020 in the business-as-usual scenario, largely because of expected income increases; fuel use and CO2 emissions would triple; and pollution loading would rise exponentially. An alternative scenario of slower vehicle and energy growth is explored, premised on substitution of personal vehicles with buses and reduction in traffic congestion. Consequently, fuel use and CO2 emissions would only double in Bangalore and Dhaka, whereas in Colombo the increase would not be significantly lower than in the business-as-usual scenario. The cumulative carbon mitigation potential over a 15-year period would be 13% in Bangalore, 9% in Dhaka, and 2% in Colombo. The drop in pollution loading would be different in each city.

Abstract As the population of cities continues to proliferate, society places a greater strain on the productivity of geographical features and their resources. In recent years, this trend has increased for the planet's seas. In order to further maximize the utility of marine space, the concept of co-location between economic sectors operating in the sea, and coexistence of such sectors with the ecosystem, has provided traction for the concept of multi-use (MU). In response, the European Union Horizon 2020 programme funded the Multi-Use in European Seas (MUSES) project which aims to provide innovative technical and policy solutions to facilitate MU in the five European sea basins. Within the broader analytical framework of MUSES, 10 case studies were developed to determine the potentials and effects of MU for various sectors. This paper examines MU between tidal energy development and environmental protection, as well as tidal energy development and environmental monitoring. A desk analysis provided for known drivers, added values, barriers, and impacts of MU. Results from the desk analysis were validated by key stakeholders, resulting in policy and technical recommendations informing the MUSES Action Plan. The analysis demonstrates that technological advancements to monitoring equipment are required to further studies of environmental interactions with tidal energy arrays, and determine the viability of co-locating developments in environmentally sensitive areas. However, greater capacity deployments of tidal energy are required so that robust monitoring data sets can accumulate over time, geographical scope, and ecological make-up. Such capacity development is currently hindered by ineffective government fiscal measures.

The economics and social development of cities depend heavily on urban freight. But, despite its obvious benefits, freight transportation has substantial negative externalities. The electrification of urban freight could help mitigate these. However, there exists a paucity of literature on barriers to the adoption of electric freight in the context of developing countries such as India. The present study intends to bridge this gap. It aims to identify the barriers to the adoption of electric freight vehicles (light commercial vehicles) in urban areas by using a fuzzy analytical hierarchy process (FAHP), a multi-criteria decision-making (MCDM) technique. Based on the opinion of 32 experts, it was found that high capital costs, low driving range, and long charging times are the major obstacles to the adoption of electric freight vehicles in India. The results from the present study will assist government officials in identifying bottlenecks and prioritizing strategies for the promotion of electric freight vehicles in India.

Abstract The ability to calculate the battery available capacity (BAC) for electric vehicles (EVs) is very important. Knowing the BAC and, thus, the driving range cannot only prevent EVs from being stranding on the road but also optimize the utilization of the battery energy storage in EVs. In order to determine the BAC, this paper presents a new neural network (NN) model of the lead–acid battery, based on the battery discharge current and temperature. Comparisons between the calculated BAC from the NN model and the measured BAC from experiments show good agreement. Furthermore, this new approach can readily be extended to the calculation of the BAC for other types of batteries.