Major Conclusions

As a consequence of the fast development of the smart grid in recent years, an

increasing number of DERs, smart meters and other ICT based devices have been

installed in the grid, especially in the distribution network. This vast deployment leads

to significant reduction of carbon emission, but the inherent intermittence of DERs also

brings new challenges such as demand and supply unbalance to the grid. The smart

home and building solutions provide not only the living comforts improvements and

energy optimisation to the end users but also the interaction service to the power grid

operators. The EMS, which bears the energy management work in smart homes &

buildings, contributes great power in solving the new challenges caused by the

increasing DERs and loads.

EMS helps delivering a necessary coordinating platform for the controllable loads,

DERs and the advanced tariffs to schedule their operations. This thesis has proposed a

range of solutions for individual device, individual home all the way to residential

buildings.

1. As a large energy consuming devices in residential house and commercial buildings,

the space heating & cooling system is one of most valuable loads to be controlled

and optimised by EMS. However, the current system in the market only provides

the basic control features such as timer and constant temperature control, which is

not compatible with the smart tariffs such as RTP. A GA based EMS for space

heating system has been proposed in chapter 3, fully considering the house thermal

models, residents’ living comforts and the float tariffs. With the pre-configuration

of the proposed EMS, the space heaters can operate in-advance according to the

price signals; the residents’ house will acts as a temporary thermal storage media,

which store the low-price electricity for a short-period before people come back

home, so that people can enjoy the warm environment once they get home but

spend less. The results within different prices scenarios indicate that the proposed

solution can cut the energy bills up to 36.8% for the customers without sacrificing

living comforts compared to the heaters equipped with basic control features. A

hardware based test bed has been established in the lab and the performance of the

proposed GA based EMS has been validated on the test bed.

2. For a complete EMS solution of a residential house, all the controllable loads such

as clothes dryer and water boiler, and the DERs should be taken into account.

Regarding the quick change of the loads and the DERs’ states, the optimisation

speed and accuracy of the EMS are the critical factors to be considered. In order to

been proposed in chapter 5, which combined both RTCS and RO, so that the load

scheduling will rely on not only the predicted data but also the real-time

information collected by the sensor network. In addition, the DR programs are

promoted by the energy suppliers in the distribution network, giving incentives for

an increasing number of residential houses to join the programs to earn extra

benefits. Therefore, the DR automatic response and control mechanism were

embedded in the proposed EMS control approach in order to fulfill the

requirements of the customers to join DR programs. It should be mentioned that the

BESS and PV systems, considered as the DERs installed in the home, are taken into

the optimisation as well. The numerical results presented in chapter 5 indicated that

the proposed control approach can schedule the loads such as WB and EVs to

operate during the relatively low price period and fulfill the DR events at the same

time. The BESS performs excellently in assisting the optimisation of energy

consumption, through storing spare energy of PV generation and purchasing cheap

energy from the gird in off-peak time based on FLC.

3. Compared with the EMS for a single residential house, the management of the loads

and DERs in building by aggregator tends to be more intricate. The complexity lies

in heavy scheduling work of load and DERs as well as the variety of user

requirements and conditions. Especially for the residential apartment building, the

distribution network. In order to solve the problem, an aggregator service for the

residential building was proposed in chapter 5, which coordinates and optimises the

DERs in the building. According to the predicted information of renewable energy

generation, EVs’ using pattern, electricity price and the load consumption in the

building, the aggregator generated the control plan for the EV and BESS. This

mechanism minimized the cost of electricity imported from the grid and brought

profits to the stakeholders of the DERs and residents in the building. Considering

the cheap energy exporting price of the Feed-in tariff, the inside trading of PV

generation and BESS energy proposed in chapter 5 no doubts provided much

better financial benefits to the stakeholders. The case studies in chapter 5 have

given the performance of the proposed aggregator service for the residential

building with three different kinds of tariffs. The results in all three cases validated

the effectiveness of the proposed aggregator service in shortening the pay-back

periods of the DER investments and provide cheap energy to residents.