Flexibility system design for electric vehicles: performing congestion management for the DSO

The climate change is one of the major topics on the political agenda. This has resulted in the Paris agreement which is ratified by 148 parties worldwide. This agreement states that the worldwide temperature increase needs to stay below 2 ℃. This has resulted in regulation to lower the use of fossil fuels and to increase the energy efficiency. For centuries, the world has been heavily relying on fossil fuels which has led to a high level of prosperity. However, the world is running out of fossil reserves. The transition towards renewables is therefore not only an environmental issue but is a necessity to keep the same level of quality of life. Even though, wind and sun have the prospect to deliver abundant amount of electricity, this requires a major change in the electricity system. Hence, the transition to renewables will cause a disruption of one of the fundamentals of our society.
The increase of renewable generation in the installed capacity leads to a higher reliance on weather conditions and a lower controllability of the power system, resulting in a higher volatility in electricity prices. Additional to this, there is a need for a higher energy efficiency which leads to an electrification of household appliances. An example is the electrification of transport. This leads to a reduction of fossil fuels like gasoline, but to an increase in demand for electricity. It is expected that electric cars will increase the pressure on the peak load of the local electricity network and installed generation capacity. The electric vehicle demands for a high-power consumption in comparison to the current household appliances for a long period of time in the capillaries of the electricity network. These developments of electric vehicles can lead to both a challenge as an opportunity, while the electric vehicle can also be used for flexibility on the demand-side. Flexibility is seen as a power modification sustained at a given moment for a given duration at a particular location within the network.
Flexibility is of interest of three different parties: the transmission system operator (TSO), balance responsible party (BRP) and distribution system operator (DSO). The TSO needs flexibility for balancing services while renewable generation has an intermittent nature and is not controllable. The BRP wants to use flexibility on the demand-side to adjust their portfolio while sustainable production is less predictable. At last, the DSO wants to use flexibility because of the increase in adoption of PV, electric heating and EV which can lead to an overload in the existing cables and transformers. The first two parties have challenges that are interrelated and have a system framework to manage the changes in demand and supply. However, the need for flexibility will increase with the adoption of renewable generation which could result in a need for a flexibility market. However, the challenge for the DSO has a locational component for which this existing framework is not useful. If the DSO detects an overload in its network, the overload needs to be solved by changing the load on that specific cable or transformer. Therefore, there is a need for a new mechanism which can provide demand-side flexibility.
According to literature, there are several market mechanisms to unlock flexibility on the demand-side. Four of these are elaborated in this thesis: price-based mechanism, variable connection capacity, direct control and the flexibility market. All these market mechanisms have pros and cons. To be able to compare the mechanisms different aspects are described. These aspects are based on the Smart Grid Architecture Model (SGAM) which is developed to support the design of smart grid use cases. The SGAM consists of five layers: business-, function-, information-, communication- and component layer. An agent-based simulation is developed to describe some of the aspects. Agent-based simulations make it possible to model a complex social-technical system with many interrelated variables. This gives the opportunity to model the interactions between different levels in society, such as the interrelation between the national electricity market to local charging behavior of people regarding electric vehicles. In this simulation a neighborhood in ‘s-Hertogenbosch is modelled and nine scenarios of market mechanisms are compared.
The results in the simulation show that market mechanisms with static profiles, capacity or price-based, lead to static reactions of the EVs. This can be explained by the high level of flexibility of EVs which gives the opportunity to postpone their charging until the cheapest moment or to the moment the capacity profile ends. This leads to a high level of simultaneous charging and therewith to high loads on the network and high electricity prices. Next to this, the simulation shows that market mechanisms with dynamic prices based on a spot market lead to a damping effect of the load profile on the transformer which will lead to benefits for the TSO, DSO, BRP as the consumer. In combination with the evaluation of the aspects, this leads to the conclusion that market mechanisms with a static approach are not useful for both the DSO as BRP for their challenges. An approach with dynamic prices is useful for all parties but need to be added with a congestion control mechanism of the DSO to maintain a high reliability of the network. This results in a conclusion that a market mechanism with spot market charging in combination with a flexible capacity contract is most suitable. The capacity contract gives the DSO the opportunity to send capacity constraints to flexible appliances when overload is detected. The simulation indicates that this is an occasional matter when price sensitivity of consumers is sufficient.
This has resulted in a functional, physical and technical system design which optimizes the charging profiles of the EV based on the input of the EV driver, BRP and DSO. This results in a system in which the EV driver does not need to change its mobility behavior to offer flexibility. The BRP has the possibility to use flexibility for adjustment of their portfolio and the DSO has a high level of reliance to avoid congestion.