Energy management and planning in smart cities

Abstract

A smart city is a sustainable and efficient urban centre that provides a high quality of life to its inhabitants through optimal management of its resources. Energy management is one of the most demanding issues within such urban centres owing to the complexity of the energy systems and their vital role. Therefore, significant attention and effort need to be dedicated to this problem. Modelling and simulation are the major tools commonly used to assess the technological and policy impacts of smart solutions, as well as to plan the best ways of shifting from current cities to smarter ones. This paper reviews energy-related work on planning and operation models within the smart city by classifying their scope into five main intervention areas: generation, storage, infrastructure, facilities, and transport. More-complex urban energy models integrating more than one intervention area are also reviewed, outlining their advantages and limitations, existing trends and challenges, and some relevant applications. Lastly, a methodology for developing an improved energy model in the smart-city context is proposed, along with some additional final recommendations.

Modelling changes in the energy efficiency of buildings using neural networks on the example of Zielona Góra

“…As a consequence of the State policy adopted, cities should improve the current system of power supply and energy consumption and implement new solutions in a coordinated manner, thus optimizing synergies between all the possible energy savings solutions. Growing demand for electricity and heat and an increase in its prices, as well as the use of renewable sources, is an important energy challenge, which would be better dealt with in its complexity and not separately as it is often the case [4] . Fabrri and Tronchin (2015) described another challenge for the construction real estate industries, which is formed as a question: is there a link between the buildings with low and high demand for energy and the quality of their use?…”

“…The popularity of smart ways to design and construct more energy-efficient buildings, as well as increase their comfort has been growing in construction and architecture [2,3]. Numerous case studies are known in the literature, that describe and analyze individual projects to increase energy efficiency, depending on the environmental conditions, the characteristics of the building and supporting technology used to reduce energy consumption, energy costs and CO ² emissions in buildings, also through the active technologies, such as photovoltaic panels [4,5], solar panels [6], wind turbines [3.7] or heat pump systems [8]. Important economic benefits were described due to the application of the simultaneous production of electricity, heating and cooling in cogeneration [9].…”

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

“…The main objective of the SC includes improvement in performance and quality of urban electricity delivery. Moreover, other objectives include optimized utilization of electrical infrastructure for demand management, minimization of overall costs, reducing GHG emissions, maximize power quality, benefit in terms of pricing, availability, and reliability [20]. integration [95].…”

“…The work provides initially an overview of HEMS architectures and fundamental functions, followed by configurations and home appliances, finally covering utilization techniques for various RES in a SH. Similarly, on the large and complex scale, Calvillo et al [20] have reviewed the smart city concept, aiming at energy-related work on planning and operation models. Moreover, the scopes of the reviewed works can be classified into five interventions, namely; generation, storage, infrastructure, facilities, and transport.…”

Simulation environment for algorithms and agents evaluation.

“…SC can be represented as a three-level platform, where hardware represents the base, the communication mechanism represents the middle layer, and the top layer is represented by the intelligent software (Calvillo et al, 2016 The presented platform consists of a series of heterogeneous sensors that use M2M for the communication, and applies different AI and statistics technologies to evaluate the system and increase energy efficiency in cities.…”