Study phase offers the outcomes of this analysis. Different EV penetration levels had been taken into consideration, starting from one thousand to 15000 vehicles, and taking the two EV types described in section. System operation examples with hourly detail are proven inside the following
The following indicators had been computed:
The market percentage study of the masses of the considered system (districts, EVs and metro sections), with (66), as the suggest of the hourly marketplace shares .
The common change on strength expenses due to the aggregator moves and the impact on the electric strength prices on the taken into consideration district and metro section, the usage of equations (67) – (73), shown in below Table.
The average electricity weighted device rate trade, as in previous phase proven in below Table.
The total financial savings in comparison with a base case (operating the systems independently and with none DER implementation) the usage of equation (74), and proven in below Table 56.
The DER making plans and total charges (such as metro, EV and district electricity and DER fees) effects of the analysed case research are presented in Table fifty two and below Table.
Looking at the DER mounted capability; PV and HP grow almost linearly with the number of EVs (due to the more EV power demand).
It is interesting to note that the PV mounted ability is bigger in case have a look at B than in case look at A. This is produced by the slightly higher charges in this case look at in evaluation with case look at A, making it more worthwhile to sell strength again to the
grid. Case have a look at C, on the other hand, offered smaller mounted capability (around 23% and 31% for case studies A and B, respectively, see Table fifty two), that means that the better variability of study expenses proven inside the stochastic eventualities makes load shifting more worthwhile, relying less on the PV production to reduce expenses. This impact has been analysed in element in early phase .
For the battery storage, only case study C has carried out any potential, in view that the costs variations after load management in the other case studies have now not been enough to compensate battery investments. As study discussed in section five.2, the better illustration of the energy rate variability and variety study proven inside the stochastic scenarios have an important effect within the planning and operation of DER, especially for storage systems.
The system total fees at the stop of the assignment lifespan of 20 years, which include strength and DER fees , presented a similar linear pattern, with lower slope, than the PV and HP mounted potential.
The total charges are slightly better in case observe B in assessment with case study A (due to higher overall costs), and the expenses are
considerably smaller in case C, showing over again that the aggregator takes benefit of the larger fee variability, the usage of demand response and battery systems.
Comparing these effects against the ones of previous evaluation, it may be referred to that:
The PV capacity per house on this analysis is slightly larger (around 10%) than in the analysis evolved in chapter 5 (for the same variety of houses). For instance, for the fee situation in case study observe A, around 3kW of common PV in evaluation with 2.7kW from chapter five (see Table 32). This increment can be attributed to the greater hundreds found in this device (EVs and metro) that had now not been considered in previous chapter.
Comparing the PV capacity per residence with the one obtained in previous chapter, the established strength is also barely larger (round 6%, with average values of 3kW vs 2.83kW, see phase 6.3.1). However, it is tough to compare both analysis as they differ no longer most effective inside the load sizes but inside the strength charge technique as well.
Regarding HP capability per house, the distinction among this evaluation and the one in chapter five (for the same range of houses) is negligible: 0.42kW vs 0.417kW . This suggest that the HP thermal energy production is barely suffering from other electric hundreds.
Battery capacity is hard to compare against the opposite analyses evolved in this thesis, as they range in many elements that affect battery implementation. For instance, the presence of EV (which isn’t always taken into consideration in bankruptcy five) and the strength costs (which is considerably special from previous chapter , where traditional commercial and residential tariffs had been used, as opposed to directly the use of marketplace costs as in this chapter). Nevertheless, outcomes remain coherent:
Batteries are simplest hooked up in case look at C (see Table 52), as in bankruptcy 5, and the capacity is inside the equal order of magnitude: round 100 – 250MWh in this bankruptcy and around 350MWh in previous chapter . The lower battery capability fee of this observe might be due to the additional unfastened storage provided by means of the EVs, now not taken into consideration in chapter five.
Similarly, the total costs for the one of a kind research ought to be as compared with caution as they differ importantly in their considerations.
Comparing the total prices per residence on this examine with the ones of previous chapter, the delivered load of EVs and the metro device in this evaluation make the total value larger (around 15%). For instance, in case examine A, this evaluation offers 20.9 – 22.2k€ total value per house, at the same time as in bankruptcy five the price are approximately 18.2k€.
Comparing with the price of bankruptcy 6 , it may be seen that the prices per residence on this bankruptcy are significantly lower: 27.9 – 30k€ in chapter 6 and 20.9 – 22.2k€ for case examine A in this chapter, for an average reduction of 32%. This discount is attributed to the lively participation inside the energy markets taken into consideration in this study, taking advantage of the charge-maker approach and the better variability of prices not present within the tariffs used in bankruptcy 6. However, the variety of houses, EVs and metro strains are very extraordinary among both research, making difficult to do a truthful contrast.
Table fifty five shows the common exchange on power prices due to the aggregator movements and the repercussion at the common electric energy expenses of the machine (calculated with (67) – (73)).
From Table fifty five and the Fig. forty seven to above Fig. it can be visible that distributed technology together with PV panels logically has a tendency to lessen the overall energy consumption from the grid, lowering the energy fee in all case studies. This impact is extra evident inside the evaluation advanced in section 5.three.
Note that the marketplace share on this analysis is fairly small in evaluation with the district sizes taken into consideration for the take a look at developed in previous chapter (achieving a marketplace proportion as much as 8%, whilst right here is 0.77%). Therefore, the strength rate changes presented on this have a look at are extensively smaller.
Comparing the trade on electricity fees, case examine A shows a barely bigger decrement in comparison with case observe B. The barely larger overall prices in case take a look at B, promotes extra PV installed capability to promote extra strength lower back to the grid, however
much less load shifting than case examine A. This may be seen within the system operation figures.
For case take a look at C, it can be visible that the better variability at the original expenses can make the common rate change seem small in comparison with preceding case research. However, the absolute
trade is greater than for the opposite instances: round 1.15%, in contrast with 1% and 0.7% for case research A and B, respectively. In other words, in case study C the price decrements have been more compensated
with the expenses increments, not like the other instances that produced more decrements than increments at the electricity price, moving the average charge down.
Lastly, the impact at the weighted average machine price has also been calculated, resulting in decrement of around 0.54%. This value is very similar to the equivalent exchange inside the evaluation of bankruptcy 5 , displaying that the overall market behaviour of both structures is comparable, affecting the strength charges in a comparable way.
Additionally, the overall costs of all the taken into consideration systems (together with metro, EVs, district and DER charges) have been as compared with a base case following a business-as-usual approach (no longer implementing any DER structures and managing all of the structures independently). Hence, this contrast permits to evaluate the blessings of the choicest integrated management of metro, EVs, district hundreds and DER systems beneath distinct EV penetration levels. To create a fair assessment, each case study has been compared with its personal base case (equal input parameters) without enforcing any distributed electricity resources, as defined in (74).
The results of such comparisons can be observed in below Table.
Looking at the effects, case have a look at B, with barely better variety of off-peak to peak expenses in evaluation with case have a look at A, presents a small greater enjoy the interconnected scheme and DER systems.However, the large price variability of the situations in case observe C, presents even better effects, accomplishing 30% of economic blessings. A similar behaviour occurs in the evaluation of chapter 5, wherein case observe C is the only with more financial savings. Showing once more, the significance of a better representation of the real variety and variability of strength costs, which is partly lost inside the averaging method of case studies A and B .
It is thrilling to commentary that the quantity of EVs has little effect on the whole savings for all case research (around 0.5% of difference). Also. The EVs add greater load that translate into better expenses. This advise that for this specific application, the EVs have reached its saturation point.
By analysing these consequences, a few recommendations may be drawn for coverage makers and stakeholders:
Even though the outcomes presented here are precise to the case take a look at analysed, these results advise that there are capacity economic benefits for such integrated technique. In addition, if environmental and health benefits due to renewable structures and EVs also are taken into account, smart city programmes, as the only presented right here, may be of top notch hobby for investors and policy makers.
During the making plans of structures, it may be seen that the stochastic scenarios represent higher the real-existence variability and range of electricity charges, which translates to greater robust capability planning of DER structures and better overall fee financial savings. Therefore, the sort of stochastic approach in the making plans method is recommended.
Certainly, the introduction of greater EVs will bring more load to the electric device, translating to extra price. However, these charges may be compensated with the savings from the more garage supplied by means of the EVs, especially if the garage is no longer only used for energy arbitrage, however for ancillary offerings as well (which have no longer been taken into consideration in this thesis). Therefore, vehice-to-grid (V2G) schemes need to be supported to facilitate the creation of EVs in clever cities.