Solutions In Terms Of Energy Research Articles

Multi-objective optimization and improvement of multi-energy combined cooling, heating and power system based on system simplification

The multi-objective optimization of combined cooling, heating, and power (CCHP) systems typically focuses on optimizing objective functions that consider energy, environmental, and economic factors. However, the implementation of optimization solutions, which is related to decision variables, is often overlooked. This paper proposes a novel improved optimization method based on system simplification by reorganizing, re-optimizing and re-selecting the initial optimized population to improve decision variables. And created algorithm pseudocode. The improved algorithm is adopted to perform multi-objective optimization on the established multi-energy CCHP system. The hypervolume of the improved/original algorithm is 0.9770/0.9887, with only a 1.18% difference. The optimization results of the improved algorithm and the original algorithm are equal in the minimum values of the net present value (NPV) and fossil energy consumption (FEC), which are 2.26 × 107$ and 1.21 × 105GJ, respectively. There is only 1.4% difference in the carbon dioxide emissions (CDE). The number of equipment types corresponding to the decision variables of the improved algorithm is reduced from 8 to 4, significantly simplifying the systems. The proposed improved optimization method can harness the local energy-saving potential and comprehensively analyze optimization solutions in terms of energy, economy, and environment. It also obtains simplified systems to promote the implementation of the project.

HYPER: Computer-Assisted Optimal Pump-as-Turbine (PAT) Selection for Microhydropower Generation and Pressure Regulation in a Water Distribution Network (WDN)

Although pressure reducing valves (PRVs) have traditionally been employed to regulate pressure and reducer water leakage, researchers have been increasingly investigating the strategy of micro-hydropower generation using pumps as turbines (PATs) to enable both pressure reduction and energy production as an alternative strategy in water distribution networks (WDNs). However, due to the continuous variability of flow discharge during the day, selecting the optimal PAT remains a challenging issue. To address this, the authors have developed HYPER, a freely available software app that implements an innovative approach for selecting the most suitable PAT in systems that involve both hydraulic and/or electrical regulation. In enabling the identification of the PAT parameters that maximize energy production, HYPER thus provides a fast and effective PAT selection tool. The effectiveness of the proposed approach was further demonstrated with application to a real WDN. Four operational patterns varying in terms of available flow and head drop were considered, showing that the most efficient pumps consistently tended to be located in close proximity to the maximum produced energy. Furthermore, the results confirmed that hydraulic regulation and coupled hydraulic/electric regulation-based installation layouts represent the best solutions in terms of energy produced. The solely electrical regulation option, given its poor flexibility, returns in all cases lower energy production with the lower adaptability of commercial pumps.

Residential Building Envelope Energy Retrofit Methods, Simulation Tools, and Example Projects: A Review of the Literature

As one of the biggest energy consumers, buildings are the focus of the energy conservation market, and the building envelope, which has the highest impact on heating and cooling loads, is one of the main targets in retrofit projects. Several materials, systems, methods, and simulation tools are used in these projects, and it is critical to understand the impact of these methods in different locations, their frequency of use, and the effectiveness of market-ready new solutions. In that context, it is necessary to review the energy conservation measures (ECMs) that are suitable for residential building envelope retrofitting, and that are commercially available or under research and development. This paper provides an overview of these ECMs. A literature review was conducted on different building envelope ECMs, including traditional and innovative energy retrofit methods, such as aerogel and phase change materials on opaque and transparent components of existing buildings. Results show that the most effective retrofit projects include bundles of ECMs, and the traditional ECMs can be as effective as more innovative solutions in terms of energy saving. Moreover, computer energy models were created for a typical residential building in the US for cold and warm climate zones to determine the impact of different retrofit approaches based on a sensitivity analysis. Results show that envelope ECMs have higher energy saving potentials in cold climate zones, of up to around 30%, and reducing the air infiltration has the highest impact in both cold and warm climate zones in a typical small residential building.

Optimal Balance between Heating, Cooling and Environmental Impacts: A Method for Appropriate Assessment of Building Envelope’s U-Value

In Europe, the recent application of regulations oriented to zero-energy buildings and climate neutrality in 2050 has led to a reduction in energy consumption for heating and cooling in the construction sector. The thermal insulation of the building envelope plays a key role in this process and the requirements about the maximum allowable thermal transmittance are defined by country-specific guidelines. Typically, high insulation values provide low energy consumption for heating; however, they may also entail a risk of overheating in summer period and thus negatively affect the overall performance of the building. In addition, the embodied energy and related emissions caused by the manufacturing and transportation processes of thermal insulation cannot be further neglected in the evaluation of the best optimal solution. Therefore, this paper aims to evaluate the influence in terms of embodied and operational energy of various walls’ thermal insulation thicknesses on residential buildings in Europe. To this end, the EnergyPlus engine was used for the energy simulation within the Ladybug and Honeybee tools, by parametrically conducting multiple iterations; 53 variations of external wall U-value, considering high- and low-thermal-mass scenarios, were simulated for 100 representative cities of the European context, using a typical multifamily building as a reference. The results demonstrate that massive walls generally perform better than lightweight structures and the best solution in terms of energy varies according to each climate. Accordingly, the wall’s thermal transmittance for the samples of Oslo, Bordeaux, Rome and Almeria representative of the Continental, oceanic temperate, Mediterranean, and hot, semi-arid climates were, respectively: 0.12, 0.26, 0.42, and 0.64 W/m2K. The optimal solutions are graphically reported on the map of Europe according to specific climatic features, providing a guidance for new constructions and building retrofit.

AVL Based Settlement Algorithm and Reservation System for Smart Parking Systems in IoT-based Smart Cities

In Internet of Things (IOT)-based smart cities, negative reasons such as cost, energy and air pollution when searching for a parking space increase the importance of smart parking systems. In this study, a two-stage hybrid approach is proposed so that drivers can find a parking space that will consume the least time and energy. The first stage focuses on car parks having at least one free parking space located near the target address in an n diameter circumference, which are also open for business. An AVL tree-based hierarchical structure is created with driving time from the starting point to each car park and walking time from each car park to the destination, and it focuses on the most appropriate car park. In the second stage, the most suitable parking space is searched and made available, if found, in hierarchical parking monitoring system. In order to demonstrate the effectiveness of the approach, the results compared with hierarchical, hierarchical Binary Search Tree (BST) and non-hierarchical solutions in terms of energy and time performance are shown on a simulation. Proposed approach gave the best result with 99% energy efficiency. In addition, a dynamic cloud-based reservation system was proposed for the parking lot determined in the study.

Heuristic-based Approach for Dynamic Consolidation of Software Licenses in Cloud Data Centers

Since its emergence, cloud computing has continued to evolve thanks to its ability to present computing as consumable services paid by use, and the possibilities of resource scaling that it offers according to client’s needs. Models and appropriate schemes for resource scaling through consolidation service have been considerably investigated, mainly, at the infrastructure level to optimize costs and energy consumption. Consolidation efforts at the SaaS level remain very restrained mostly when proprietary software are in hand. In order to fill this gap and provide software licenses elastically regarding the economic and energy-aware considerations in the context of distributed cloud computing systems, this work deals with dynamic software consolidation in commercial cloud data centers 〖DS〗^3 C. Our solution is based on heuristic algorithms and allows reallocating software licenses at runtime by determining the optimal amount of resources required for their execution and freed unused machines. Simulation results showed the efficiency of our solution in terms of energy by 68.85% savings and costs by 80.01% savings. It allowed to free up to 75% physical machines and 76.5% virtual machines and proved its scalability in terms of average execution time while varying the number of software and the number of licenses alternately.

Massive MIMO Systems for 5G Communications

Massive MIMO will improve the performance of future 5G systems in terms of data rate and spectral efficiency, while accommodating a large number of users. Furthermore, it allows for 3D beamforming in order to provide more degrees of freedom and increase the number of high-throughput users. Massive MIMO is expected to provide more advantages compared to other solutions in terms of energy and spectral efficiency. This will be achieved by focusing the radiation towards the direction of the intended users, thus implementing simultaneous transmission to many users while keeping interference low. It can boost the capacity compared to a conventional antenna solution, resulting in a spectral efficiency up to 50 times greater than that provided by actual 4G technology. However, to take full advantage of this technology and to overcome the challenges of implementation in a real environment, a complicated radio system is required. The purpose of this work is to present the MIMO technology evolution and challenges in a simple introductory way and investigate potential system enhancements.

Commercial building retrofitting: Assessment of improvements in energy performance and indoor air quality

Climate change is regarded as one of the greatest challenges facing the mankind. There is a global drive to reduce greenhouse gas emissions across all sectors. The building sector being responsible for around 40% of the energy consumption and one third of the greenhouse gas emissions in the world, needs to play a leading role in the fight against global warming and climate change. Heating, ventilation and air conditioning (HVAC) systems account for a major proportion of the total energy consumption in buildings, especially in hot and humid climates. This study aims to investigate the prospects of retrofitting in commercial buildings in terms of improvement in energy performance and indoor air quality. An administration building of a commercial organization has been selected as a case study. The building, with a net covered area of 2115 m2 and an occupancy of 250 people has been retrofitted with energy efficiency and indoor environmental quality improvement measures. The study discusses retrofit solutions in terms of energy saving as well as the associated cost. The results reveal that the implemented retrofit measures reduced the building's energy load by 39%. Improvements in the indoor environmental quality on various fronts such as thermal comfort, illumination, noise control and reduction in pollutants such as particulate matter (PM10), total suspended particulate (TSP), Carbon Monoxide (CO), Sulphur Dioxide (SO2), Nitrogen Dioxide (NO2), and Volatile Organic Compound (VOCs) have also been highlighted.

Design and Assessment of District Heating Systems with Solar Thermal Prosumers and Thermal Storage

In this study, a holistic energy, economic and environmental assessment was performed on a prosumer-based district heating system, including scenarios with varying district size, retrofitting stages and system configurations. A modeling framework was built which comprises a thermal network design and simulation model; a building energy demand model for districts; and supply and storage technology models that allow assessing system solar fraction, equivalent annual cost and greenhouse gas emissions of district heating systems (DHS). Furthermore, the approach allows comparing the performance of a DHS with individual heating systems (IHS) for the district with the same set of technology options (rooftop-mounted solar thermal collectors, gas boilers and thermal storage tanks). The framework was applied to a Swiss case study. The results of the case study show that DHS often outperform IHS; however, parameters such as the district size, the retrofitting stage of buildings and the system configuration have impacts on the performance of the DHS. The most important parameter lies in the adequate selection of the storage volume over solar collector area ratio, which indicates that DHS solutions are only advantageous if they are properly sized. Smaller districts and districts with retrofitted buildings especially benefit from DHS solutions in terms of energy, economic and environmental performance. Maximum solar fractions of 50% (non-retrofitted case) and 63% (retrofitted case) were reached with the DHS solutions.

Traffic and Energy Aware Optimization for Congestion Control in Next Generation Wireless Sensor Networks

Congestion in wireless sensor networks (WSNs) is an unavoidable issue in today’s scenario, where data traffic increased to its aggregated capacity of the channel. The consequence of this turns in to overflowing of the buffer at each receiving sensor nodes which ultimately drops the packets, reduces the packet delivery ratio, and degrades throughput of the network, since retransmission of every unacknowledged packet is not an optimized solution in terms of energy for resource‐restricted sensor nodes. Routing is one of the most preferred approaches for minimizing the energy consumption of nodes and enhancing the throughput in WSNs, since the routing problem has been proved to be an NP‐hard and it has been realized that a heuristic‐based approach provides better performance than their traditional counterparts. To tackle all the mentioned issues, this paper proposes an efficient congestion avoidance approach using Huffman coding algorithm and ant colony optimization (ECA‐HA) to improve the network performance. This approach is a combination of traffic‐oriented and resource‐oriented optimization. Specially, ant colony optimization has been employed to find multiple congestion‐free alternate paths. The forward ant constructs multiple congestion‐free paths from source to sink node, and backward ant ensures about the successful creation of paths moving from sink to source node, considering energy of the link, packet loss rate, and congestion level. Huffman coding considers the packet loss rate on different alternate paths discovered by ant colony optimization for selection of an optimal path. Finally, the simulation result presents that the proposed approach outperforms the state of the art approaches in terms of average energy consumption, delay, and throughput and packet delivery ratio.

Influence of two motion types on solar transmittance and daylight performance of dynamic façades

Recently, architectural designs with dynamic facades have been introduced as a strategy for improving building environmental performance. Currently, such as those capable of rotation and folding motion, are widely used. An investigation of the effect of these two motions on the energy and daylight performance can contribute to enhanced energy efficiency and occupant comfort. Therefore, a parametric simulation approach was implemented for the design optimisation of dynamic façades capable of two motions in a high-rise tropical office building near the Equator. 72 cases representing the two motions and different transmittance values, axes, and dimensions were compared for determining the best compromise between minimum energy consumption and maximum daylight comfort.The results indicate that energy consumption can be decreased by 14–21% through the implementation of dynamic façade compared with base case. The folding motion exhibits better performance in all four orientations than the rotation motion. For daylighting, the area of adequate illuminance increases by 15–32% with the optimal configuration. The value obtained for the rotational motion exceeds that for the folding motion. Based on the overall optimal solutions in terms of energy and illuminance performance, the optimal design for all orientations corresponds to the rotation motion. Furthermore, the results indicated that optimal angles are concentrated within a certain range that typically corresponds to 15° from the fully open position. This study provides a performance-based approach to aid designers in making decisions in the early design stage, from the energy and visual comfort perspectives, and not simply from the aesthetic viewpoint.

A Study on Multi-Objective Parametric Design Tool for Surround-Type Movable Shading Device

This study presents a multi-objective parametric design tool for four-axis surround-type movable shading device using solar position tracking in Seoul, South Korea. In order to explore large numbers of possible forms of shades, generic algorithms are utilized with real-time simulation of the performative criteria such as solar radiation, daylight glare probability (DGP), and solar shielding rate on window surface. This study outlines a workflow using a multi-objective engine called Octopus that runs within Grasshopper 3D, a parametric design tool, in addition to environmental performance simulation plug-in Ladybug. The workflow utilizes a performance-based design tool, which allows the designer to explore, sort, and filter solutions, and visually compare alternative solutions in terms of energy saving and indoor daylight quality in order to determine the optimal form of shade changing its shape every one hour. The result of deriving and analyzing the optimal shade shape through the genetic algorithm proposed in this study is as follows: On the one hand, on the summer solstice, shade shapes with shielding areas of almost 100% should be derived to achieve the most effective reduction of the direct solar radiation. The proposed movable shading device reduced direct solar radiation by 52.40% and 57.20% in the south- and east-facing windows, respectively. On the other hand, in winter when solar heat gain is important, the absence of sunshade is optimal in terms of heating load. However, in order to improve the indoor light environment, it is confirmed that it is possible to derive a certain shape of sunshade according to the sun’s trajectory. On the winter solstice, the problem of glare arises from 10:00 to 15:00 in the south and 10:00 in the east. Therefore, the proposed four-axis movable shading device can be configured to have a minimum protrusion length satisfying DGP less than 0.35 in winter.

Development, implementation and performance of a model predictive controller for packaged air conditioners in small and medium-sized commercial building applications

Small and medium sized commercial buildings, such as retail stores, restaurants and factories, often utilize multiple packaged air conditioners, i.e. roof top units (RTUs), to provide cooling and heating for open spaces. A conventional control approach for these buildings relies on local feedback control, where each unit is cycled on and off using its own thermostat. The lack of coordination between RTUs represents a missed opportunity for operating more efficient units when there is strong coupling between the spaces they serve and can lead to unnecessarily high electrical demand due to the inherent randomness of unit cycling. This paper presents an overall model-based predictive control (MPC) approach for RTU coordination that includes a description of the control architecture, modeling approach, implementation, and assessment. We provide results of laboratory and field tests that demonstrate the short-term and long-term performance of the MPC solution in terms of energy and demand savings.

E3DOAS: Balancing QoE and Energy-Saving for Multi-Device Adaptation in Future Mobile Wireless Video Delivery

Smart devices (e.g., smartphones, tablets, smart-home devices, etc.) have become important companions to most people in their daily activities, and are very much used for multimedia content exchange (i.e., video sharing, real-time/non-real-time multimedia streaming), contributing to the exponential increase in mobile traffic over the current wireless networks. While the next generation mobile networks will provide higher capacity than the current 4G systems, the network operators will face important challenges associated with the outstanding increase of both video traffic and user expectations in terms of their levels of perceived quality or quality of experience (QoE). Furthermore, the heterogeneity of mobile devices (e.g., screen resolution, battery life, and hardware performance) also impacts severely the end-user QoE. In this context, this paper proposes an evolved QoE-aware energy-saving device-oriented adaptive scheme (E3DOAS) for mobile multimedia delivery over future wireless networks. E3DOAS makes use of a coalition game-based rate allocation strategy within the multi-device heterogeneous environment, and optimizes the trade-off between the end-user perceived quality of the multimedia delivery and the mobile device energy-saving. Testing has involved a prototype of E3DOAS, a crowd-sourcing-based QoE assessment method to model non-reference perceptual video quality, and an energy measurement testbed introduced to collect power consumption parameters of the mobile devices. Simulation-based performance evaluation showed how E3DOAS outperformed other state of the art multimedia adaptive solutions in terms of energy saving, end-to-end quality of service metrics and end-user perceived quality.

The cost-optimal methodology for the energy retrofit of an ex-industrial building located in Northern Italy

The recast of the Energy Performance of Buildings Directive (EPBD) introduced a comparative methodological framework for calculating cost-optimal levels of minimum energy performance requirements. The cost-optimal methodology, conceived for national authorities, was here exploited as a decision-making tool for supporting a private investor in choosing the most viable energy scenario. The methodology was thus used to evaluate different energy efficiency measures applied to an abandoned industrial building in Turin (Northern Italy) and to identify the best retrofit solution in terms of energy and costs. Providing guidance and tools for re-designing ex-industrial areas can be useful for several similar case studies widespread not only nearby Turin, but also in other Italian regions and EU countries. The research activity here presented aims at testing the cost-optimal methodology to support energy retrofit projects starting from an early design stage. The arisen issues may be considered for future applications, with reference to specific contexts. In this perspective, this work constitutes a first step towards the definition of an “environmental and economic sustainability equilibrium”, assuming that the application of models and approaches for evaluating both the energy-environmental performances and the economic ones, in many cases, may give very different results.

Choice model for a modular configuration of a point-focus CPV/T system

In this paper a model for choosing the proper modular configuration of a point-focus concentrating thermo-photovoltaic (CPV/T) system according to the domestic user energy demands, is presented. The main aim is to evaluate several modular configuration solutions in terms of energy and economic performances and space occupied. First of all, the main CPV/T system components are chosen: optics, solar cells and tracking system. A point-focus system with parabolic mirrors, triple-junction cells and dual-axis tracking system is considered. The choice of the proper CPV/T system configuration is realized considering an equations system that defines the electric and thermal performances in terms of solar radiation, cells number and concentration factor. The choice model presented in this paper allows to configure, referring to different Italian zones, the CPV/T system under several working conditions minimizing spaces and costs. It is observed that CPV/T modules with a lower cells number allow high flexibility to satisfy the loads. The high concentration level determines interesting solutions related to a domestic application from the energy and economic point of view, above all in southern Italy, during the CPV/T system life cycle. Finally, CPV/T systems allow a significant reduction of CO2 emissions due to the primary energy savings.