Distributed Cooperative Control and Near-Future Energy Networks
The development of new systems, known as Cyber-Physical and Human Systems (CPHS) and Humans-IoT, is gaining global attention. In 2016, Japan, ahead of the rest of the world, set the goal of realizing a "super-smart society" and proposed a vision for a future society known as Society 5.0.
Realizing a super-smart society requires various technological developments, including artificial intelligence, systems science, robotics, and transportation systems. Among these elemental technologies, the core component is the energy management system.
Since the 2011 Great East Japan Earthquake, social demand for the mass introduction of renewable energy has led to a review of the previously monopolistic structure of the electric power business and a reconsideration of electricity liberalization. This is a welcome development for us, the general consumers, as it expands the possibility of purchasing inexpensive electricity. The increase in distributed power sources from renewable energy promotes the local production and consumption of electricity, reducing transmission losses and leading to cost savings. However, will the mass introduction of renewable energy not cause any problems?
Electricity is a very unique commodity, and it is difficult to store large amounts of it. Supplied electricity must be consumed at the same time it is generated; conversely, to consume electricity, an equivalent amount must be supplied in real time. If the balance between supply and demand is not maintained, the frequency cannot be kept constant (at 50/60 Hz). Until now, regional power companies have worked to maintain power quality through supply-demand adjustments. However, the increase in distributed power sources from renewable energy brings the risk of deteriorating power quality, which, if it progresses, could lead to major blackouts.
A solution to this problem is smart distributed cooperative control technology for distributed power sources. Fundamentally, distributed control is a control method that divides a large-scale system, such as a power network, into several subsystems and gives each subsystem decision-making authority. As a result, a controller is required for each subsystem, but each controller can make decisions locally and flexibly according to the characteristics and conditions of its individual subsystem. Since subsystems are smaller in scale compared to the entire system, communication and computational loads can be significantly reduced. However, optimization at the subsystem level does not necessarily guarantee optimization of the entire system. In some cases, there is a risk of compromising stability. Therefore, distributed cooperative control technology is a control method where the controllers of each subsystem share information with the controllers of adjacent subsystems, adding cooperative behavior between them to ensure the stability and sub-optimality of the entire system.
The application of this control method to large-scale power networks is what constitutes a distributed cooperative control-based energy network. In an energy network like the one shown in the figure below, multiple decision-makers, such as BEMS (Building Energy Management Systems) and HEMS (Home Energy Management Systems), basically manage their energy independently and freely. However, by mutually sharing information and energy with their neighbors under a set of rules, they can increase energy efficiency.
By controlling distributed power generation from renewable energy with distributed cooperative control technology, it is expected that the local production and consumption of energy will advance, curbing CO2 emissions to put a brake on global warming, and that a disaster-resilient energy network will arrive in the near future.