Urban areas including cities are recognized as places for exploiting the untapped potential of renewable energy and also major global energy consumers. Due to the increased urbanization since 2007, it is expected that two-thirds of the world’s population will live in urban areas by 2050. Urban areas currently are responsible for 65% of the global primary energy consumption in addition to more than 70% of greenhouse gas emissions in the energy sector.
On the other hand, because of raising awareness at the socio-political level of cities, city governments have recognized variable renewable energy (VRE) technologies including solar PV modules, wind turbines help to create clean, liveable, equitable as well as greener cities by reducing greenhouse gas emissions. The major driver of this awareness is the features of VRE technologies such as being environmentally friendly, distributed and decentralized generation, and lower prices.
Some of the municipal governments are making net-zero pledges on their own, and many are joining networks of like-minded actors. For example, the Carbon Neutral Cities Alliance, as well as 88 members of C40 Cities, have signed on to Deadline 2020, committing them to be neutral greenhouse gas emissions and climate-resilient by 2050. Municipal interest in becoming net-zero at the city level divides the building sector into new and existing buildings. All these actions have been taken in line with the climate change goal of the Paris agreement that is reducing the climate change impact by limiting global warming to well below 2, preferably to 1.5 degrees Celsius, compared to pre-industrial levels.
New buildings have been changed from merely energy consumers to partially or fully prosumers. Prosumers are agents or buildings which simultaneously consume and produce energy. The partially or fully prosumer buildings are so-called near/net-zero energy buildings (n-ZEB) in which the amount of energy consumption is near or equal to the produced energy. These buildings enhance supply and demand flexibility and pose the control of demand flexibility as the major challenge for future grid operations. But existing buildings have to retrofit themselves if they want to be a member of actors in meeting the climate change goal.
However, both new and existing buildings have their opportunities and challenges to meet this goal, there is a promising opportunity for them generally that can achieve it, that is the smart home energy management system (SHEMS). SHEMS is an automated platform that connected new and legacy types of equipment such as home appliances to balance between the supply and demand sides of buildings’ energy and to manage their energy consumption while providing energy flexibility, reducing greenhouse gas emissions, and enhancing the comfort level of occupants.
Hence, the urban energy system needs new control strategies for the building sector to adapt itself to a new range of variations. Some of these variations include environmental variations, urban morphology, occupant behavior, energy policies, technological advances, and prices.
The new control strategies of buildings have come up with the three pillars featuring improved demand-side management (DSM) methods, developed control algorithms, and new technologies. The realization of improved demand-side management requires an information and communication technology (ICT) platform that provides management, grouping and communicating buildings, and prioritizing a large number of appliances with flexible consumption. Internet of things (IoT) in close to end-users can be an ICT-based platform to meet this goal. IoT allows existing buildings and neighborhoods in larger urban systems to communicate with each other seamlessly. Figure 1 demonstrates the main components of an IoT platform. It is important to know IoT platform is designed for what purpose (internet of things application), depending on this purpose or application what type of devices are required (internet of things devices), also need to know how can be connected and communicated with each other internet of things protocols), where is stored the gathered data (internet of things data storage), and finally how can be analyzed these stored data (internet of things data analytics).
For example, to cover all the five components of the internet of things as a new communication technology to build up a new control strategy at the building level, the IoT application is the DSM of home appliances. Then, sensors and terminal controllers are needed IoT devices, wired or wireless network for communication among devices defines the IoT protocols, building performance such as daily/monthly/yearly energy consumption are data that requires to be stored, and at the end how can be analyzed the stored data of buildings.
Most of the available DSM methods based on the IoT need a significant deployment of sensors and control devices (e.g. terminal controller) which require the proper integration of the ICT platform with the energy network. Although the convergence of the Internet and intelligent devices leads to having smart energy systems with networks of sensors and smart meters extended to the end-user, it requires collecting and sharing data with big data centers.
Therefore, there is an urgent need for developing an internet-based platform that does not require any memory or data storage unit and fewer networks of sensors at the building level for problem-solving and decision making. The collective intelligence (CI) control algorithm plus the IoT operating system at the building level is a feasible solution to do this end. The combination of them enhances the smartness and integration of appliances and legacy equipment into a collaborative network, manages the energy demand of existing buildings and neighborhoods within a large urban system in a scalable manner as well as increases the occupants’ satisfaction and comfort level.
This study aims to introduce the utilized CI method by Moazami and et al as a form of universally distributed intelligence for collaborative problem solving and decision making. Here the CI-based DSM (CI-DSM) of buildings in a complex urban energy system is a solution to rectify the DSM problem of buildings in which decision making is made on the basis of certain adaptation measures. The backbone of CI is a simple communication among buildings inside a complex urban energy system without the need for any central brain (data storage and data analytics). Thus, CI is worked as a communication routine among building in the IoT platform and eliminate the required data storage units. After that, the paper also puts forward a heuristic control strategy. Finally, it proposes the 5G network-based IoT and occupant’s smartphones as the distributed ICT-based platform and terminal controller devices for the collaborative distribution network of buildings.
This story is continued in the next part…
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