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Battery-powered electric vehicles are gradually expanding their market outside of the typical public and private transportation sector. A good example is a growing demand for electrification of special-purpose vehicles such as compact urban vacuum sweeper trucks. These vehicles are characterized by low production numbers and specific limitations such as restricted volume for battery placement, specific working conditions, requirement to supply electro- hydraulic systems, etc. Therefore, the selection of optimal battery cell and identification of its required characteristics is not a straightforward task. This article addresses this by presenting a methodology for selecting optimal battery cell for compact urban vacuum sweepers. A laboratory testing procedure is established to measure electric and heating characteristics of candidate battery types and battery producers. After evaluation of the experimental test results using the Analytic Hierarchy Process (AHP), the most appropriate battery cell is selected. The experimental tests and the presented AHP methodology prove that battery cell selection for a specific purpose based solely on manufacturers' datasheet can result in a sub-optimal decision.

Integration of renewable energy sources accompanied with decommission of fossil fueled power plants inherently results in lack of power system flexibility. In turn, this reduced flexibility calls for additional balancing services. In parallel to this, the process of transport sector electrification is in place and the large fleets of electric vehicles (EVs) could prove to be one of the solutions for increased power system flexibility needs. If managed adequately, EVs could be able to provide the missing balancing services. In this paper, a model of EV day-ahead market and frequency containment reserve bidding is defined in order to asses the potential challenges that could arise during such service provision. Special attention is given to the EV battery state of energy, since the batteries are energy-limited resources and specific issues may arise both at individual EV and fleet level.

In traditional power systems production always followed consumption, while nowadays consumers are incentivized to take active part in electricity markets. In energy intensive industry large portion of the product cost goes to energy expenses. Thus, optimizing operations based on market signals can create substantial benefits for industrial prosumers. Industries with more than one energy input vector, e.g. electricity and gas, both being bought from their respective day ahead markets are investigated in this paper. The paper introduces enthalpy modeling versus conventional mass flow which increases the scheduling efficiency. Proposed optimization model is based on stochastic mixed integer linear programming where prices of electricity are treated as stochastic process as oppose to deterministic approach usually used. Goal of optimization is to reduce overall energy cost. Also, it must provide bidding strategy for both day-ahead markets. Idea is to reduce market variability by proper device scheduling, utilizing flexibility between energy vectors and behind the meter production of electricity.

Wireless sensor networks based on energy-neutral energy-harvesting nodes have been in the focus of researchers for years as they bring significant benefits regarding the efficiency and the cost of the final product. In this paper, we focus on timing and energy aspects of energy-harvesting sensor node operation. A typical wireless sensor network application enables user to adjust refresh rates of certain measurements which are executed on a sensor node. Energy-aware scheduling of measurements, i.e. task scheduling, is crucial for maintaining target refresh rates demanded by the user. In this paper, we devise an off-line and on-line scheduling approach for energy-aware scheduling of tasks on sensor nodes. Moreover, we show why earlier real-time energy-harvesting models are inadequate in these applications. We evaluated our approach on synthetically generated task sets and initial results show that further research in this direction can bring practical benefits in real-world applications.

In the light of power system decarbonization, electric vehicles are becoming an important tool to bridge the gap between traditional and low- carbon power systems. If aggregated, electric vehicle’s fleet can provide flexibility to system operator. Recent literature defines aggregators as electric vehicle charger aggregators which collides with the conventional way of observing electric vehicles, as stationary chargers with connected loads/vehicles. This paper observes them as mobile batteries, not chargers. Therefore, new concept of electric vehicle battery aggregator has been defined which exploits their mobility. Battery aggregator has more information about vehicle’s behavior and can maximize their flexibility provision regardless when and where they charge. New concept brings benefits to all system participants from electric vehicle owners, aggregators, and system operators to society altogether.

A transition from a traditional power system towards a low-carbon power system requires unlocking new sources of flexibility a t t he distribution level a nd engaging distribution system users to become electricity market participants. These users are usually too small to adequately position themselves in electricity markets. Therefore, the latest package of the European Commission highly encourages aggregating them into a single market entity. Aggregation of distribution system users can be realized through different business models. The main intention of this paper is to analyze two potential business models to be used for aggregation of distribution system users. The first one illustrates the case in which the supplier also offers aggregation services in markets or auctions on behalf of its customers. The second model considers the case in which a new market participant, called the “independent aggregator”, enables distribution system users to actively participate in electricity markets or offer services to the grid operator. The paper elaborates on the advantages of both models through simplified examples by positioning them within the current European market setup.

High penetration of variable renewable sources act as a heavy burden on conventional power system management and operation. Uncertainty in power systems expanded from demand side to generation side as well. Since new sources of imbalances have entered power system, it should be reorganized, automated and modernized. New providers of flexibility should be recognized and used in future power system planning and design. One of the possible technologies that can be used for flexibility provision are electric vehicles. Numerous fast charging stations are installed all over the world and such trend will continue in future. Depending on their operation, charging stations can act as flexibility providers but they can also further degrade system's flexibility if installed without any kind of energy buffer. This paper will present mixed integer linear model for flexibility studies of modern power systems with high penetration of variable renewable sources and electric vehicles. Results clearly show that smart planning of fast charging infrastructure can bring huge benefits to power system concerning costs, emissions, and variable renewable power curtailment.

An increasing penetration of electric vehicles in recent years has been driven by government and municipal subsidies, tax exemptions, parking access priority, as well as by the citizens’ increased environmental awareness. Electric vehicles indisputably bring benefits to their drivers and society in general, indirectly through global warming and greenhouse gas emissions mitigation and directly through financial savings and cleaner microclimate. However, integration of electric vehicle charging spots at home or work, especially fast charging stations and battery swapping stations, without prior analysis can have a negative effect on power system. In order to predict and eliminate power grid issues before they occur, a detailed analyses should be made through a common understanding of both transportation and recharging needs of electric vehicles’ users and of the power grid constraints. Power and transportation system interdependency becomes of high value for correct placement and sizing of charging stations and for overall increase of social welfare. This paper analyzes electric vehicles charging needs at the basic level, through both the power system and the transportation system. An urban transmission and power grid in the vicinity of the Croatian capital Zagreb is used as a study case. Driving and electricity consumption curves are compared, locations for charging infrastructure are selected (fast charging spots and battery swapping station) and power grid’s available capacity is defined.