Effect of flexibility penetration level on the DSO cost

Specific calculations of the flexibility for every consumer and the methods of aggregation carried out by the aggregators are out of the scope of this thesis and they require already established communication infrastructure and data repositories to gather the required information. However, the objective of the analysis carried out here is to show how the flexibility penetration level, or the amount of flexibility available, can be beneficial to the DSO [287]. Consider the same network explained in section 5.2, with the same flexible buses, and only the firm flexibility transaction for the high probable congestions in the DA Flex-DLM. Keeping the flexibility prices constant, four levels of flexibility penetration are tested from 10% to 50% with a 10% step, to evaluate the total savings that can be achieved by the DSO if more flexibility becomes available by the customers. Table 5.25 shows the total flexibility cleared at every bus with respect to the four penetration levels and the already penetration level 10% carried out. It can be noticed that at a low level of 10%, the DSO has no choice but to use the flexibility from all the buses. With low availability of flexibility, the DSO optimizes its operation with limited options considering the technical and locational constraints of the network. However, as the level of flexibility penetration increases, which means that more flexibility becomes available at the flexible buses, the DSO is able to better optimize its operation and decrease the cost of flexibility. For example, starting from penetration level of 40%, the DSO opts to use only the flexibility offered from the buses 2, 3 and 4 and neglect the flexibility from the rest of the buses. This means that buses 2, 3 and 4 have optimal locations in the network to solve the congestion and minimize the system losses. As a result, for the same total activated flexibility at every level, the savings achieved by the DSO at every penetration level compared to the original 10% penetration is given in Figure 5.17, which shows an expected savings of 4.5% for a 50% penetration of flexibility compared to only 10%. For larger distribution networks with possibly hundreds of customers, such savings can increase if more flexibility becomes available and more customers are involved in demand flexibility programs. This last issue can be challenging and cannot be considered as an easy task. Aggregators must be technologically advanced to provide full automation for flexibility sources at the consumers’ households [281].

Table 5.25 Activated flexibility at buses with respect to penetration levels of flexibility.

Flexibility penetration

level

Flex_Bus 1 Flex_Bus 2 Flex_Bus 3 Flex_Bus 4 Flex_Bus 5 Flex_Bus 6

MW MW MW MW MW MW

10% 0.123 0.362 0.365 0.295 0.165 0.279

20% 0 0.519 0.270 0.590 0 0.209

30% 0 0.450 0.274 0.759 0 0.105

40% 0 0.391 0.365 0.832 0 0

50% 0 0.482 0.457 0.650 0 0

Figure 5.17 DSO’s savings at every penetration level compared to 10% penetration.

5.3 Summary

Many conclusions could be drawn out of the case studies carried out in this chapter. First and foremost, demand flexibility products, UREG and DREG, can be of great value to the DSO and can offer efficient solutions to manage the common distribution-level congestions.

Take for example UREG flexibility, where the DSO can benefit from the load reduction volumes offered by the consumers to mitigate congestions occurring from overloaded network lines. Also, the load increase volumes offered by DREG flexibility can help the DSO in managing voltage fluctuations caused by the variability and intermittent behavior of RES in distribution networks. The second conclusion is the importance of considering the demand uncertainty in the flexibility programs. Ignoring such aspect and using deterministic approaches to optimize the purchase of demand flexibility can easily lead to inaccurate procurement of demand flexibility amounts, either more or less than what is actually needed.

In addition to this, a progressive flexibility market framework should allow trading demand flexibility during real-time. While flexibility trading during the DA period can help in mitigating some of the expected congestions, the sudden variability and the unforeseen outages in the real-time cannot be accounted for during the DA period. Beside the uncertainty of demand consumption, the DSO should as well take into account the consumers’ behavior uncertainty. One of the key drawbacks of demand flexibility is its dependency on the level of compliance of the consumers to the activation request and the amount of flexibility activated. It is very important for the DSO to consider such uncertainty to avoid engaging in flexibility trading with aggregators or consumers that do not match the level of reliability maintained in the networks.

1.00%

1.50%

2.00%

2.50%

3.00%

3.50%

4.00%

4.50%

5.00%

20% 30% 40% 50%

DSO cost savings (%)

Penetration Level %

6 C ^OST & B ^ENEFIT A ^NALYSIS

One of the roles for DSOs is related to the planning of its local distribution networks.

With the wide expansion of DERs and the introduction of new loads such as EVs, DSOs must take into their consideration such new network elements when planning its future expansions. Also, the deployment of demand flexibility programs can impact the future planning of the network and it must be considered. The two main issues that may be facing the DSO to equip its network and deploy demand flexibility programs are the consumers’

readiness and the economic feasibility of demand flexibility. From an economic perspective, a distribution network must have the financial incentives to install the needed equipment to facilitate the deployment of demand flexibility, in order to defer capital expenditures in reinforcing the network. However, the passive behavior or unwillingness of the consumers to participate can halt such initiative. From a technical perspective, distribution networks can have customers willing to participate in the flexibility programs. From the DSO’s point of view, the cost of equipping the network and cost of flexibility activations can be inefficient when compared to the cost of reinforcing the network. The issue of finding the optimal network solution can be rather complicated due to many reasons. There is not a definitive method to valorize the prices of flexibility. In addition, the long-term network planning tools are not designed to handle the levels of versatility and complexity introduced by the provision of demand flexibility programs. With the high penetration of low carbon technologies and the increase of electricity demand, the DSO is faced with challenges to maintain high reliability network levels. As a result, capital expenditures must be provided to upgrade the conventional passive distribution networks. A common method that is found in literature to assess the economic benefits of demand flexibility opposed to common conventional approaches of network upgrades is carrying out cost and benefit analysis (CBA). The CBA is able to showcase whether it is more beneficial to the DSO to participate in demand flexibility programs or to invest in upgrading its network.

Demand flexibility have been labelled by several studies as a potential substitute to conventional grid reinforcement solutions [309], [310]. The impact of demand flexibility on system operators, especially on DSOs, has been the focus of many previous studies. In [311], a wide range of distribution network topologies simulations were presented to identify the benefits of smart grid solutions and demand response programs. Moreover, a comparison study between the need and cost of network reinforcements and smart grid solutions required to accommodate demand growth was introduced. The work emphasizes on the importance of deploying demand response programs and the efficient managing of smart grid technologies such as smart electric vehicles (EVs) charging, which can significantly decrease the total cost of needed investments. In a similar study based in France [312], a smart grid experiment was carried out that aims to investigate the benefits of load control when planning for distribution network expansion. A Swedish case study in [313] investigates the economic benefits of demand flexibility in postponing the needs for network investments. The study carried out a CBA to evaluate the feasibility of demand flexibility on a long-term basis. This issue of using demand flexibility as an alternative to avoid unnecessary grid investments or to defer high costs for balancing power in system with high RES penetration, is addressed in [314]. The paper proposes a centralized scheduling model for residential demand flexibility in a micro-grid with high RES penetration. Furthermore, it assesses the potential of current customers’ devices as well as the possible future ones as sources of demand flexibility. The work suggests that loads such as storage batteries and storage heaters possess the highest potential as flexibility sources at the residential level. The work in [315] addressed the trade-off method between choosing to upgrade the network capacity and actively engaging consumers in demand response programs.

One of the recent projects that carries out detailed cost benefit analysis (CBA) for the provision of demand flexibility as an opponent to grid expansion, is the Capacity to Customers project (C2C) [316]. The UK project’s philosophy is based on maximizing the usage of demand response (DR) programs, through optimal distribution network planning.

In addition, the project has carried out various studies to assess the feasibility of DR programs through implementing cost control strategies to defer the needs for grid expansions [56], [317]–[320]. Based on the UK regulation, the work in [316] carried out a cost and benefit analysis (CBA) based on the Ofgem’s CBA framework. The CBA analysis compared between the option of deploying demand flexibility programs and reinforcing the network with needed assets. The study computed the net present cost (NPC) of both options and accordingly choose the optimal solution.