Engineering has a significant cultural component in addition to its widespread perception as an engine of innovation and economic growth. This cultural component corresponds to how users and communities react or adapt to technological innovations and their influence on the advancement of such innovations. Hence, it is critical to prioritize the social aspect as much as the technical aspect of the energy transition.

With the fast-growing world and its energy demand, it becomes necessary to shift renewable energy-producing technologies to keep this planet habitable. But during the transition, it is essential to maintain the flexibility, reliability, availability, and robustness of the current energy system. With multiple actors involved in the energy system, it becomes inevitable to have a united front to make an effective transition and offer holistic solutions to the challenges. For this, communication among them is important.

This thesis has contributed to developing a toolkit catering to the cultural component of engineering and bringing different actors in the energy system to the same platform. It takes the route of co-simulation and modelling of energy system components. The modular and user-centred design of the toolkit helps to educate the communities to increase their acceptance of renewables, educate students about recent changes in the energy system, and foster communication among domain experts by simulating the challenges of energy transition and system integration. Illuminator's table top approach makes it easy for users to operate and understand the energy system demonstrations.

The outcomes show example demonstrations simulated for a specific group of users by leveraging Illuminator's modularity, table top approach, and scalability.

The penetration of renewable energy sources is increasing every year and that poses a lot of challenges in the distribution system. Since they are intermittent in nature, they cannot serve the energy demand as stand alone sources without the help of storage technologies or stable energy sources. As the RES, especially the Photo Voltaic generation units are often connected in the distribution system, their intermittent nature may result in a sudden rise or fall in overall generation. Hence the voltage has to be kept within limits to prevent the failure of the system. Storage technologies plays an important role in keeping the voltage levels under control. From the consumer perspective, the usage of electric vehicles is steadily increasing and most of the vehicles are connected to public charging stations to charge the vehicle battery. Hence there is an interaction between the EVs and distribution grids, which is utilized as a storage option here. In this research, the voltage changes due to the penetration of renewable energy sources in the distribution system is regulated by using the electric vehicles as a storage option. This thesis tries to give an understanding on the strategy applied towards regulation of voltage in the distribution system using electric vehicles. The strategy will serve as a platform for regulating voltage using electric vehicles and it can be adapted to any such distribution network. This strategy takes into account the size and capacity of the battery, battery state of charge and the availability of electric vehicles for a given day. Consensus algorithm serves as the communication platform for information interchange between the electric vehicles connected in the network. Average consensus algorithm estimates the average state of charge of the electric vehicles connected in the distributed network and that has been used to ensure equitable contribution of power among the electric vehicles. Markov model is used to simulate the travel pattern of the electric vehicles. This provides a more realistic and accurate pattern of travel. Markov model is implemented with and without considering time of occurrence and the results shows that the pattern is more accurate when time is considered as a parameter. Considering the generated travel pattern, voltage level of the buses in the network and the output from the consensus algorithm, the voltage has been regulated. The Electric vehicles are used for regulating the voltage when the voltage level is beyond the tolerance limits, and during other times, the electric vehicles charge their batteries. This is executed by controlling the charging and discharging cycles of the electric vehicles. The results are discussed based on different cases and the advantages and limitations of each case is explained in detail. The simulation is not robust since the availability of electric vehicles is uncertain. To make it more robust, monte carlo simulations are used. The probability of occurrence of several events has been estimated using monte carlo simulations and through the results, the availability is predicted to a certain extent. Different cases are implemented and analysed and the results shows that the availability depends on the bus, the location of the bus and the travel behaviour of the electric vehicles. Each case is discussed separately and the degree of uncertainty is reduced at the end.

Developing renewable energy sources entails new challenges which have not been faced previously by the traditional grid. One of the issues is the variability of renewable resources due to their characteristics of weather. The intermittent nature produces uncertainty in generation output, especially in solar and wind power generation. As penetration of both sources increase, variability will be more difficult to handle. And even as this issue is being resolved, another one, that of the application of an energy storage system has arisen. The energy storage is the current and typical means of smoothing wind- or solar-power generation fluctuations. Conducted research mostly developed an energy storage for only one technology, however, different technologies can be combined and complement each other which significantly improve the storage system’s performance. In this research, a hybrid energy storage (HES) is proposed to mitigate power fluctuations of renewable plant output power.

This thesis aims to give understanding of the effective strategy of a hybrid energy storage for PV power output and wind power output fluctuation suppression. The strategy will stand as the foundation for a broader framework which aims to optimize the size of hybrid energy capacity to enable such application in uncertain condition. Wavelet power sharing method is proposed as the strategy to operate the hybrid energy storage using frequency-based method. The strategy can decompose the frequency component of renewable power quickly and allocate the power to the respective device. In this paper, battery and supercapacitor is adopted to meet the electric grid technical requirements for smoothing renewable power. The results show that the supercapacitor peak fluctuations of battery power are moderated by adding the supercapacitor, providing lower peaks and slower derivative of power fed to/drawn from the battery. The result from the power sharing is suitable in terms of improving the battery lifetime. Battery lasts for 1.3 years in a conventional energy storage system, while it can last up to 6 years in the hybrid energy storage.

After getting the optimal power allocation between storage devices, sizing the capacity of hybrid energy storage also considers uncertainty in power output. This research uses investment storage cost, penalty and life cycle cost as the objective function, while hybrid energy storage’s state of charge and the power fluctuation performance as the constraint. The chance constrained programming is used to make the fluctuation of output power under a certain confidence level, which also meet the electrical quality and economy. The optimal solution of hybrid energy storage capacity is carried out by using genetic algorithm based on stochastic simulation. The results show that, with the confidence level of smoothing requirement up to 90%, system contains two energy storage has a lower total cost than a single-sourced energy storage.

In 2018 the Dutch government, businesses and other stakeholders started negotiating an agreement to combat climate change (het Klimaatakkoord). Energy consumption is changing and more Renewable Energy Sources (RES) are implemented. While these changes are ongoing, the Distribution System Operators (DSOs) must ensure no congestion occurs in the grid. However, it seems congestion problems are already arising. As a lot of research has been done on Energy Storage Systems (ESSs) and Electric Vehicles (EVs) for congestion prevention, research on movable ESSs is missing. This thesis proposes a method for congestion prevention by Relocatable Energy Storage Systems (RESS). A Mixed Integer Linear Program (MILP) is proposed to minimise the amount of RESS used and penalise displacement. An algorithm which includes a Minimum Cost Maximum Matching is used to determine the planning of each individual RESS. The results show that, for the test grid designed, it is beneficial to use RESS instead of statically placed ESS in the grid.