Because of the increase in volatile, distributed energy generation, security of supply will be a continuous challenge for the next decades. It is the number one priority in the energy domain.
In order to meet the regulatory goals of the European Comission, energy efficiency has to be increased. It is also a big interest on the consumer side.
Regulatory goals and environmental concerns drive the need for significant emission reduction.
In order to handle large amounts of data and a variety of centralised and decentralised energy sources, the overall energy management is of high importance.
Due to the high volatility of renewable energy sources and quick changes in switching supporting capacities on and off, the power grid will have to be more flexible.
In order to make energy supply more efficient, shifting energy consumption from peak-times to times with lower overall consumption is an important next step. Variable tariffs are an important enabler to reach the goal of smooth energy consumption with low peaks.
The consolidation of standardised SoS terminology is a necessary step to further develop and apply SoS concepts in the future. SoS Engineering approaches have great potential to deal with highly complex, large-scale, socio-technical systems. They require multi-disciplinary collaboration.
Grid control systems are necessary to monitor the grid condition and automatically implement grid stabilisation measures such as feeding in management load shedding or switching actions.
Upcoming smart meter rollouts are just one next step to real-time measuring of the energy flows on generation and consumer side. Therefore, further reference models and algorithms will have to be developed.
Virtualisation can be used to bundle many small electricity producers to one larger virtual power plant that can be better managed and integrated as an energy generation entity. Virtualisation therefore is a key technology to overcome difficulties in distributed energy generation.
With high resolution energy metering, large amounts of data will be produced that will have to be dealt with in order to present them to both consumers and suppliers.
With a more open and linked power grid, security will become an even bigger issue in the future. New patterns like security by design will have to be included in the engineering process on the way to a secure smart grid.
Local demonstration projects are important for people to become acquainted with the new concepts and technologies and to test them in a real-world environment. These projects will become more and more sophisticated until locally independent micro grids will replace them.
Market liberalisation is an ongoing process which is a driver for new business models and stimulation of the energy economy.
Regulatory energy efficiency and emission goals exert a strong pull effect to ensure low-wmission, high efficiency energy production.
Societal awareness of climate change results in a demand for green energy supply.
An increase in reliability, capacity, failure tolerance and efficiency of networks enables the linkage of systems generally.
This results in a more volatile and distributed energy generation which makes it necessary to deal with these new conditions.
Recycling is a topic beyond glass, plastic or paper. In the future most resources will become scarce so human kind has to develop a way of living in a recycling economy.
Increasing electricity and heating costs have made consumers more sensitive about their consumption already.
Incentives have to be offered on all consumer levels in order to reach everyone in the domain. Since energy suppliers have generally no interest in higher energy efficiency on the consumer side, either the system has to be changed or legal requirements will have to be created.
Due to the increasing obligatory installation of smart meters, the prediction of the actual power consumption of customers will be more and more accurate within shorter periods of time. For the customer this results in a better knowledge and awareness of his or her current consumption which leads intentionally to lower energy consumption and better efficiency on the consumer level. Another benefit is that invoices can be charged on the actual consumption for everyone so that there is less risk by inaccurate forecasting for the consumers. Because of the ability of profiling due to high resolution metering, privacy aspects will have to be fully evaluated before the benefits of smart meters can be exploited.
In order to make a European or worldwide smart grid more efficient, common standards for metering energy consumption are required.
Systemic modelling tools comprise all sorts of standardised models for optimisation, collective adaptive systems, prediction, virtual deployment, simulation and planning.
Due to better and increasing storage solutions like electric cars or pumped storage power stations there will be a more flexible distribution which results in a smoother energy supply and overall reduction of energy losses. Especially problems like grid bottlenecks or peak loads in energy consumption can be addressed with the development of consumer friendly storage solutions like electric cars.
Hardware, software and network technologies are mature enough to develop smart meters with sufficient capabilities for strategic smart grid goals. Standard protocols, common security mechanisms and clear privacy protection are to be defined before the benefits of a uniform metering infrastructure can be exploited.
This capability will be more and more developed and refined over a longer period of time. Starting with 15 minutes between transfers of current consumption loads, this time span is going to decrease ultimately down to "real-time" streaming of metering data which finally enables a very accurate forecast respond.
A variety of systems always leads to a certain heterogeneity of standards and protocolls since different systems require different configuration. Ensuring interoperability despite this variety, the development of integration technologies is necessary so that differently configured systems can communicate and interact.
Due to the great amount and wide spread of energy generation units, grid control becomes a non-trivial problem. Wide-area measurement is thus fundamental for control mechanisms to ensure overall grid stability.
Large amounts of data will be created from smart meters, sensors in the grid, private and industrial power plants, etc. Distributed computing is one of the key technologies, to deal with this Big Data in order to enable humans to make more informed decisions.
Demand side management (DSM)/demand response describes the effect of balancing current power requirements automatically through various mechanisms, predominantly price signals. Placing incentives like variable tariffs that the systems can automatically deal with is another mechanism to support DSM.
A distributed energy management system is the "brain" of a distributed generator pool, links the generator entities and exercises control in this network. It also schedules the deployment according to both economic and ecologiacal rules such that the potential of virtual power plants is fully exploited. The management system also provides functions to forecast loads and renewables generation and uses this data to calculate the optimum timetables for the distributed generation and possibly consumption systems.