June 03, 2017 Views : 1585Comments : 1
Still a novelty in today’s utility sector, microgrids are slated to evolve into a fundamental building block of 21st century energy infrastructure.
Conservation, self-sufficiency, and sustainability are the key drivers taking the case for microgrids further. To that effect, the US Green Buildings Council discusses the evolving zero net energy trend, which is central to the energy efficiency argument. Zero energy buildings are what could be envisioned as the zenith of energy efficiency – synergizing multiple disciplines to create self-powered sustainability.
Tapping into renewable energy sources and adapting existing transmission and distribution systems to it seems like the obvious starting point. However, the zero energy home is more than just a ‘green’ building with solar panels. Material design excellence and superior HVAC systems in isolation cannot support the ultimate outcome of net zero energy bills. It needs to be supported by on-site power generation, storage, and distribution capabilities.
This is where the buzz around microgrids starts making sense. Just like distributed computing revolutionized IT, microgrids can transform energy management. A localized grouping of energy sources and loads remains connected to the traditional macrogrid but is capable of decoupling and autonomously functioning, depending on defined conditions.
Montgomery County, Maryland made the perfect test bed for this idea. Owing to the location’s inclement weather pattern, maintaining uninterrupted power supply posed a veritable challenge. In order to plug the gap, leading electrical engineering companies joined forces to deploy two microgrids exclusively serving the county’s public safety facilities. This system can automatically, or at will be disconnected from the main grid, continuing to operate at normal capacity for extended periods of time. By recycling waste heat from on-site power generation operations, it can generate up to 3.3 million kWh of solar energy, and 7.4 million kWh of combined heat and power each year. In all, this will diminish greenhouse gas emissions by 3,629 metric tons each year – equivalent to taking 767 conventional fuel cars off the road. The sheer generation capacity of Maryland microgrids is also said to be enough to fulfil the energy needs of 400 ‘non-smart’ homes a year.
In a siloed residential network, this volume of energy is clearly in excess of what the maximum demand can be. It creates the opportunity to develop an elastic demand side management (DSM) subsystem to underscore the automated and distributed energy delivery network. Microgrids with integrated renewable energy sources (RES) and a control unit can dynamically allocate power based on evolving demand profiles. In the long run, this will reduce dependence on the macrogrid, culminating in an ‘island of sustainability’. Scheduling flexible loads through this model becomes a possibility, directly separating itself from the must-run loads tied to essential building functions like ventilation and refrigeration.
In turn, this has a twofold effect; exponentially increasing distribution efficiency and improving energy storage management by using consumption data to determine when the connected battery array should charge or discharge.
However, microgrids are only the medium through which home owners can enhance sustainability. The key to making energy efficient buildings smarter lies in connecting individual microgrids to create an ecosystem. This will enable homeowners to buy and sell excess energy produced within the network, implementing a producer-consumer (prosumer) model.
Last year, an Australian company launched a residential electricity trading market, which will use blockchain technology to facilitate transactions. Other companies are looking to take this idea of a peer-to-peer energy trading network further by developing a decentralized, user-driven energy generation, distribution, and virtual trading platform.
Other than the fact that microgrids are capable of laying the foundation for a free energy market, they are also the cornerstone of business models benefiting utility providers and users. Microgrid-as-a-service is already making waves, shielding ratepayer groups by allowing them to pay per pre-decided rates, while the onus of setting up and maintaining the infrastructure is on the supplier and distributor. From the customer’s perspective, this ensures reliability and negates the need to purchase and install expensive equipment.
In a recent analysis, IDC identified a wide gap between residential technology applications and scenario-based services. The study indicates that R&D efforts must focus on emerging technologies like artificial intelligence (AI) and machine learning to improve infrastructure functionalities.
The present infrastructure’s full potential can only be realized by integrating AI and machine learning capabilities to intuitively link multiple microgrids on individual building platforms. With AI, microgrids will go from being proactive in isolation to being proactive in conjunction with each other. Networked microgrids can monitor each other’s operation, predict potential downtime, and schedule backup in near real-time—rendering power outages a thing of the past.
Machine learning can be harnessed to recognize consumption patterns, shaping household loads to enhance DSM and transforming microgrids into multi-objective intelligent energy management systems. This will use an artificial neural network to predict load demand and RES output, 24 hours in advance. By using fuzzy logic for battery scheduling, it will render legacy techniques like opportunity charging and heuristic flowchart (HF) battery management obsolete—taking us one step closer to a net zero energy future.
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