Battery swapping stations (BSSs) present an alternative way of charging electric vehicles (EVs) that can lead toward a sustainable EV ecosystem. Although research focusing on the BSS strategies has been ongoing, the results are fragmented. Currently, an integrated way of considering stochastic EV station visits through planning and operations has not been fully investigated. To create comprehensive and resilient battery swapping stations, a two-stage optimization with recourse is proposed. In the planning stage, the investment for battery purchases is recommended even before the EV station visit uncertainties are made known. In the operation stage, the battery allocation decisions, such as charging, discharging, and swapping are then coordinated. To apply the recourse strategy in creating representative scenarios, the EV station visit distribution techniques are also proposed using a modified K-means clustering method. Aside from the sensitivity analysis made with swapping prices and charging intervals, the strategy comparisons with conventional strategies have also demonstrated the practicality of the BSS coordination to future electricity and transportation networks.

Emission trading is widely considered to be the most effective policy to minimize the overall costs for CO₂ abatement. However, the political feasibility of an emission trading scheme may crucially depend on the free initial allocation of emission permits to carbon-intensive industries in order to offset the reduction in profits. This paper aims to analyze these potential profit impacts and the possible compensation to affected generation companies through modeling the Australian National Electricity Market under a potential emission trading scheme. Historical emission-based and historical generation-based allocation approaches are used in this paper to calculate and compare the percentages of carbon permits that should be freely allocated. Two carbon permit price scenarios are used to analyze the sensitivity of the optimal percentage of free allocation to carbon permit price.

Transactive energy is a novel approach for energy management and trading, which can be used in microgrids to facilitate the integration of distributed energy resources (DERs) in existing networks. The key feature in transactive energy is using market-based solutions for energy management. Hence, an appropriate transactive energy market (TEM) framework should be designed to enable and incentivize DER owners to participate in different markets. The efficient implementation of TEM for microgrid energy management encompasses the application of a variety of design principles. In this rapidly developing area, this paper presents a complete proposal of the TEM as a framework for the design, implementation, and deployment of transactive energy solutions for energy management in microgrids. In particular, we outline the requirements to design an effective market mechanism for the TEM. The applicability of this perspective is demonstrated through the introduction of the Monash Microgrid as a real-world implementation of a TEM solution, where a complete hardware and software foundation is presented as a platform to deploy a market-based solution for microgrid energy management. This is further illustrated through an example scenario, where the application of TEM is discussed to demonstrate the impact of considered design choices on achieving desired objectives.

As the global transition toward sustainable energy gains momentum, integrating electric vehicles (EVs), energy storage, and renewable energy sources has become a pivotal strategy. This paper analyses the interplay between EVs, energy storage, and renewable energy integration with Indonesia’s grid as a test case. A comprehensive energy system modeling approach using PLEXOS is presented, using historical data on electricity generation, hourly demand, and renewable energy, and multiple scenarios of charging patterns and EV adoption. Through a series of scenarios, we evaluate the impact of different charging strategies and EV penetration levels on generation capacity, battery storage requirements, total system cost, renewable energy penetration, and emissions reduction. The findings reveal that optimized charging patterns and higher EV adoption rates, compared to no EVs adoption, led to substantial improvements in renewable energy utilization (+4%), emissions reduction (−12.8%), and overall system cost (−9%). While EVs contribute to reduced emissions compared to conventional vehicles, non-optimized charging behavior may lead to higher total emissions when compared to scenarios without EVs. The research also found the potential of vehicle to grid (V2G) to reduce the need for battery storage compared to zero EV (−84%), to reduce emissions significantly (−23.7%), and boost penetration of renewable energy (+10%). This research offers valuable insights for policymakers, energy planners, and stakeholders seeking to leverage the synergies between EVs and renewable energy integration to pursue a sustainable energy future for Indonesia.