Building Power System Research Articles

A hierarchical framework for integration of smart buildings in fully-renewable multi-microgrids and distribution systems: Towards more sustainable societies

Using smart buildings would be a crucial step towards sustainability. Although in the literature, some research effort has focused on integration of smart buildings into power systems; the integration of fully-renewable smart buildings into fully-renewable microgrids and distribution systems has not been addressed before. In this paper, a tri-level hierarchical stochastic framework is developed for the integration of fully renewable smart buildings in fully renewable multi-microgrids (MGs) and distribution systems. The studied smart buildings have electric water heater, air conditioner, PV and battery. In the first level, the model of each smart building is separately solved to find optimal schedule of its resources and the desired electricity exchange with its corresponding MG. In the second level, each MG solves its operational planning model, considering its transactions with the connected smart buildings and finally, in the third level, distribution system operator solves its operational planning model, accepting the electricity exchange requests taken from all MGs. The proposed methodology is applied to a 69-bus 100 % renewable distribution system with 4 100 % renewable microgrids, integrated with 100 % renewable smart buildings. The results confirm the efficacy of the proposed methodology for the integration of 100 % renewable smart buildings in 100 % renewable multi-MGs. The results testify that that building-to-grid (B2G) capability decreases the operation cost of all smart buildings; the average decrease in operation cost of buildings, caused by B2G, is 38 %. The results on the studied case indicate that that the impact of batteries on operation cost of smart buildings is marginal. The results also show that the higher threshold of comfort index in smart buildings, results in their higher operation cost. The results of this research may be helpful for both smart building operators and power system operators. This research is in line with the global energy transition and decarbonisation targets as the considered smart buildings, microgrids and distribution system are fully renewable.

High-frequency harmonics suppression in high-speed railway through magnetic integrated LLCL filter.

The traction converter modulation generates switching-frequencies current harmonics. The trapped filters can eliminate these switching harmonics, reducing total inductance and filter size. Nonetheless, in comparison with the typical inductor-capacitor-inductor (LCL) filter, the trap inductor needs a larger magnetic core. Moreover, the trapped filter has not been analyzed in the traction systems. This paper proposes a magnetic integrated inductor-trap-inductor (LLCL) filter to decrease the filter's size and investigate its application in traction converters. In fact, the application range of this filter is quite broad, and it can be used in various electrical power systems, including industrial power systems, renewable energy systems, transportation systems, and building power systems. The LC-trap may be formed by connecting the equivalent trap inductor, introduced through the magnetic coupling between inverter-side and grid-side inductors, in series with the filter capacitor. Furthermore, for H-bridge unipolar pulse width modulation (PWM) traction converters, the prominent switching harmonics are concentrated at the double switching frequencies. Therefore, the stability zone is expanded by moving the resonance above the Nyquist frequency. The presented filter's features and design are thoroughly analyzed. The proposed method is finally validated by the MATLAB/Simulink simulation and hardware-in-the-loop (HIL) experimental results. Compared to the discrete windings, the integrated ones can save two magnetic cores. Furthermore, the proposed filter can meet IEEE criteria with 0.3% for all the harmonics and total harmonic distortion (THD) of 2.15% of the grid-side current.

Enhancing Short-Term Electrical Load Forecasting for Sustainable Energy Management in Low-Carbon Buildings

Accurate short-term forecasting of electrical energy loads is essential for optimizing energy management in low-carbon buildings. This research presents an innovative two-stage model designed to address the unique challenges of Electricity Load Forecasting (ELF). In the first phase, robust data preprocessing techniques are employed to handle issues such as outliers, missing values, and data normalization, which are common in electricity consumption datasets in the context of low-carbon buildings. This data preprocessing enhances data quality and reliability, laying the foundation for accurate modeling. Subsequently, an advanced data-driven modeling approach is introduced. The model combines a novel residual Convolutional Neural Network (CNN) with a layered Echo State Network (ESN) to capture both spatial and temporal dependencies in the data. This innovative modeling approach improves forecasting accuracy and is tailored to the specific complexities of electrical power systems within low-carbon buildings. The model performance is rigorously evaluated using datasets from low-carbon buildings, including the Individual-Household-Electric-Power-Consumption (IHEPC) dataset from residential houses in Sceaux, Paris, and the Pennsylvania–New Jersey–Maryland (PJM) dataset. Beyond traditional benchmarks, our model undergoes comprehensive testing on data originating from ten diverse regions within the PJM dataset. The results demonstrate a significant reduction in forecasting error compared to existing state-of-the-art models. This research’s primary achievement lies in its ability to offer an efficient and adaptable solution tailored to real-world electrical power systems in low-carbon buildings, thus significantly contributing to the broader framework of modeling, simulation, and analysis within the field.

Testing the effectiveness of deploying distributed photovoltaic power systems in residential buildings: Evidence from rural China

It is critical to promote photovoltaic (PV) power since it helps build up an efficient energy system and facilitates the achievements of China's carbon peak and carbon neutrality targets. However, there are several challenges to deploy distributed PV power in rural areas. In order to uncover the key influencing factors and measure the associated environmental and economic benefits of deploying distributed PV systems in rural China, we conducted a questionnaire survey and interviews in 296 villages with 913 rural households from 2019 to 2023. An econometric model was established to uncover the factors influencing the installation of distributed PV systems in rural China. The results show that those households living in the PV pilot policy areas are more inclined to accept distributed PV systems. Better understanding of relevant policies, more active involvement of village committees and higher educational level of villagers led to their higher enthusiasm for installing PV systems. We also find that distributed PV power can result in significant energy savings and emission reduction. Based on these findings, we propose several policy recommendations from the perspectives of system construction, governmental regulations, and capacity building efforts. We expect that these findings can help promote rural energy transition through the application of distributed PV power in rural households.

The Economic and Environmental Evaluations of Combined Heat and Power Systems in Buildings with Different Contexts: A Systematic Review

Cogeneration systems—also known as combined heat and power systems—form a promising technology for the simultaneous generation of power and thermal energy while consuming a single source of fuel at a site. A number of prior studies have examined the cogeneration systems used in residential, commercial, and industrial buildings. However, a systematic review of the economic and environmental evaluations of the system is not found in the literature. The present study aims to address this research gap by reviewing the most relevant studies on the cogeneration systems applied to buildings in different contexts (e.g., residential, commercial, and industrial) and provides systematic evaluation approaches from economic and environmental perspectives. Results show that the cogeneration system can significantly reduce energy consumption, operating costs, carbon dioxide equivalent emissions, and positive performance on other relevant parameters. The present study provides extensive evidence to show that the cogeneration system is simultaneously economically profitable and environmentally friendly in various application contexts. To achieve the maximum benefits from cogeneration systems, several practical suggestions are provided for their successful installation and implementation in real-life situations.

Energy Management and Capacity Optimization of Photovoltaic, Energy Storage System, Flexible Building Power System Considering Combined Benefit

Building structures themselves are one of the key areas of urban energy consumption, therefore, are a major source of greenhouse gas emissions. With this understood, the carbon trading market is gradually expanding to the building sector to control greenhouse gas emissions. Hence, to balance the interests of the environment and the building users, this paper proposes an optimal operation scheme for the photovoltaic, energy storage system, and flexible building power system (PEFB), considering the combined benefit of building. Based on the model of conventional photovoltaic (PV) and energy storage system (ESS), the mathematical optimization model of the system is proposed by taking the combined benefit of the building to the economy, society, and environment as the optimization objective, taking the near-zero energy consumption and carbon emission limitation of the building as the main constraints. The optimized operation strategy in this paper can give optimal results by making a trade-off between the users’ costs and the combined benefits of the building. The efficiency and effectiveness of the proposed methods are verified by simulated experiments.

Simulation and power quality analysis of a Loose-Coupled bipolar DC microgrid in an office building

With distributed generation and battery storage technologies thriving in microgrids, the use of direct current (DC) microgrids in the building sector offers multiple advantages in energy efficiency and power quality compared with alternating current (AC) systems. This study developed a new concept of a loose-coupled bipolar DC building power system. The concept was used to design a real-world office building in Shenzhen, China. A power system model was developed to study the stability and control of the DC power system and to verify DC power quality. The design and modeling of the DC power control system is discussed in detail. The study developed a few common fault scenarios in DC building microgrids that were simulated in the MATLAB-Simulink environment to validate the design of a loose-coupled bipolar DC system. The results indicate that the proposed loose-coupled bipolar DC system schema, when implemented with proper control algorithms, can achieve good fault-tolerant performance with reliable power quality, even during disruptive system events.

Optimal control and implementation of energy management strategy for a DC microgrid

This paper proposes an optimal energy management strategy (EMS) for DC microgrid. The studied system presents a commercial building power system that combines a photovoltaic array (PV), fuel cell (FC), a battery storage system and a bidirectional DC/AC grid converter. The integration of multiple power sources like renewables leads to techno-economical challenges including power quality, stability, fuel consumption, and efficiency. The proposed EMS is based on the salp swarm algorithm (SSA). This algorithm has been implemented because of considerable advantages such as its convergence properties and its reduced computing complexity. The step-by-step design of the proposed method is detailed. Then HIL tests are performed to validate the proposed EMS performances. The performance of the proposed EMS is compared with the state machine control strategy (SMC) in terms of system efficiency and fuel consumption where the obtained results prove the superiority of the proposed EMS (5.2 % fuel saving). Regarding the power quality, the proposed EMS is compared with EMS based PSO to investigate the optimizer influence, the obtained results confirm the ability of the proposed EMS to provide a superior power quality. Hence, the proposed EMS responds to the power systems challenges including power quality, fuel-saving and efficiency.

PV Energy Communities—Challenges and Barriers from a Consumer Perspective: A Literature Review

Renewable energy sources, in particular those based on solar radiation, are growing rapidly and are planned to play an instrumental role in building power systems to reach the 2030 and 2050 energy and climate mitigation objectives. However, new actors have been introduced into the energy field, highlighting the importance of the role of citizens and communities in building such energy systems. To outline the significance of citizens in the development of solar energy communities and to describe the benefits of and barriers to their implementation so far, a comprehensive literature review has been carried out based on 64 thoroughly selected, reliable scientific publications (published within 2015–2021), revealing the latest trends, technologies and research in this field. The research focuses on four consumer interest areas: policy, economic, technical and social, covering the following subsections: policy, trading model, economic assessment, business model, energy management, demand response, modelling tools and consumer adoption. Within each subsection the conducted review seeks to answer the questions related to the further development and implementation of PV energy communities, considering consumer needs and revealing the possible solutions.

Summary of Research on Supporting Facilities and Structure Vibration and Noise Reduction of High-Rise Buildings

At this stage, mid-to-high-rise buildings are flooding every corner of my country’s urban construction, and large-scale buildings have also become an inevitable result of urban planning and development. The comfort and safety issues associated with mid-to-high-rise buildings as well as the comfort and safety caused by structural vibration have also come into our sight. This article will explain the research on the vibration control of building power systems, air conditioning systems, network systems, pipeline systems and other building supporting facilities, as well as the research on the vibration control of building structures. These details reflect the improvement of vibration and noise reduction research in the comfort and safety of middle and high-rise buildings.

EnergyPlus-Towards the Selection of Right Simulation Tool for Building Energy and Power Systems Research

This article offers the summary of detailed literature review on the state of the art of simulation tools for building energy and power system research. The fundamental capabilities required for building energy and power system analysis tools are outlined. A comparative review of different energy simulation tools is presented, along with the summary of their strengths and weaknesses. A review of energy simulation tool rankings using evidence-based research is presented. A novel aspect of this article is the investigation of the limitations of energy simulation tools for district level energy analysis. A state of the art review of the co-simulation platforms to overcome technical difficulties of multi-domain energy and power systems used for district level energy analysis is presented. This article offering a review of latest developments in the building energy and power system simulation tools to help researchers and industry professional to choose the right platform for building energy and power system design and analysis.

Retrofitted IoT Based Communication Network with Hot Standby Router Protocol and Advanced Features for Smart Buildings

The advent of renewable energy sources brings the concept of building power systems, which are located at the load-centres/buildings. Further, the concept of smart building in the modern energy era increases operational efficiency, safety, and consumer comfort, where, all its operations are monitored and controlled by central monitoring and control unit (CMCU). However, for reliable communication between the components of smart building and the CMCU, a well-established network is essential. This network shall provide advanced features such as user alerts, usage details, remote control options, link failure handling, security, etc. However, the traditional IoT network can’t provide all these features and poses a challenge to use it for smart buildings due to inadequate technology to meet the unremitting user requirements. In this context, this paper proposes a retrofitted IoT based communication network with Hot Standby Router Protocol (HSRP) for remote monitoring and control of smart building devices. Besides, this proposed network possess Adaptive Security Appliance (ASA) firewall, Message Queuing Telemetry Transport (MQTT) protocol, and email alert to facilitate all the advanced features. The HSRP handles the link failures by providing a redundant path, thereby ensures reliable communication in the network. The ASA firewall provides intrusion prevention (blocking unauthorized packets). The MQTT enables the broker for broadcasting messages to all the subscribers of a particular topic. Similarly, the email alert provides communication between different users in the building. Altogether, this proposed communication network establishes a reliable monitoring and control facility in smart buildings, which is simulated and verified using Cisco Packet Tracer 7.3.1.

Fuel cells as combined heat and power systems in commercial buildings: A case study in the food-retail sector

Abstract This work investigates the viability of fuel cells (FC) as combined heat and power (CHP) prime movers in commercial buildings with a specific focus on supermarkets. Up-to-date technical data from a FC manufacturing company was obtained and applied to evaluate their viability in an existing food-retail building. A detailed optimisation model for enhancing distributed energy system management described in previous work is expanded upon to optimise the techno-economic performance of FC-CHP systems. The optimisations employ comprehensive techno-economic datasets that reflect current market trends. Outputs highlight the key factors influencing the economics of FC-CHP projects. Furthermore, a comparative analysis against a competing internal combustion engine (ICE) CHP system is performed to understand the relative techno-economic characterisitcs of each system. Results indicate that FCs are becoming financially competitive although ICEs are still a more attractive option. For supermarkets, the payback period for installing a FC system is 4.7–5.9 years vs. 4.0–5.6 years for ICEs when policies are considered. If incentives are removed, FC-CHP systems have paybacks in the range 6–10 years vs. 5–8.5 years for ICE-based systems. A sensitivity analysis under different market and policy scenarios is performed, offering insights into the performance gap fuel cells face before becoming more competitive.

Optimization of the micro combined heat and power systems considering objective functions, components and operation strategies by an integrated approach

Although the micro combined heat and power generation is one of the most successful methods for decentralized generation, it still has not developed enough for the residential sector. Determining the optimal capacity and the dispatch profile of the micro-cogeneration systems can significantly influence the development of these technologies. In this paper, a novel integrated approach for determining the optimal capacity and the dispatch profile of the micro combined heat and power systems in residential buildings considering different operation strategies, objective functions, and components inclusion which adopts mixed-integer linear programming optimization by implementing logical constraint formulations, has been presented. Moreover, several essential specifications, such as inverter efficiency for direct-current based micro combined heat and power units, charging, discharging, and storage losses, as well as dumping of excess heat, have been considered as technical details. The developed model has been applied to four types of residential buildings with different heat and electricity consumption patterns. The results of the Pareto Front solutions demonstrate that the model can reduce the total annual cost and greenhouse gas emissions simultaneously by up to 62.5% and 14.9%, respectively, compared with the separate generation.

Integrated cost-optimal residential envelope retrofit decision-making and power systems optimisation using Ensemble models

The dynamic integration of building energy models and power system models is essential to analyse the potential supply-side benefits of adopting Energy Conservation Measures (ECM) at the national, regional scale. The integration of these models requires the development of linear building energy models which are numerically compatible with linear power systems models. Ensemble Calibration is an automated model calibration methodology which identifies a cluster of lumped parameter building energy models (denoted Ensemble models) using an archetype building energy model. Each lumped parameter building energy model represents an ECM configuration (i.e., a combination of ECMs). The current paper introduces a novel mechanism by which Ensemble models are integrated with power systems models in a manner such that cost-optimal retrofit decision-making problems and power systems optimisation problems can be simultaneously solved. To achieve this objective, Ensemble models are reformulated as bi-linear models, which are then co-optimised with power systems models using a multi-stage optimisation algorithm. The methodology is tested using two building energy archetypes: a detached house archetype and a mid-floor apartment archetype. The archetypes are representative of the Irish residential stock built prior to 1970. The results show that the proposed multi-stage optimisation algorithm provides computational advantages to the solution of the equivalent problem using a brute force approach (i.e., solving building-to-grid models for each ECM configuration). The proposed method is 4.73 times faster than the brute force approach when the archetypes are decoupled and 73 times faster when the models are deemed to be coupled via a power systems model.

INTEGRATED ASSESSMENT OF THERMAL PARAMETERS IN CONSTRUCTION AND SERVICING LOW-RISE BUILDINGS

Purpose. Thermal and economic parameters of power systems in low-rise buildings during their construction and operation. Methodology. Analysis and comparison of thermal and economic parameters of energy systems in low-rise buildings. Research findings. The construction of low-rise buildings instead of individual houses confirms saving of capital construction and power system costs as well as energy savings while in operation. Based on the developed methodology, the capital and operating costs for power systems of an individual residence and a section of blocked houses are calculated. The main indicators for both house options are summarized and the most optimal option is selected. Research applications. These recommendations can be applied in modern housing construction and serve as a basis for new investment and construction projects on low-rise buildings that meet the energy efficiency requirements. Conclusion. Calculations show a 7% heat loss reduction during the construction of blocked houses. The capital cost savings for the construction of the sectional blocked lowrise building amount to 180.574 rubles.

One‐day ahead predictive management of building hybrid power system improving energy cost and batteries lifetime

In recent times, the energy consumed by buildings facilities became considerable. Efficient local energy management is vital to deal with building power demand penalties. This operation becomes complex when a hybrid energy system is included in the power system. This study proposes new energy management between photovoltaic (PV) system, Battery Energy Storage System (BESS) and the power network in a building by controlling the PV/BESS inverter. The strategy is based on explicit model predictive control (MPC) to find an optimal power flow in the building for one-day ahead. The control algorithm is based on a simple power flow equation and weather forecast. Then, a cost function is formulated and optimised using genetic algorithms-based solver. The objective is reducing the imported energy from the grid preventing the saturation and emptiness of BESS. Including other targets to the control policy as energy price dynamic and BESS degradation, MPC can optimise dramatically the efficacy of the global building power system. The strategy is implemented and tested successfully using MATLAB/SimPowerSystems software, compared to classical hysteresis management, MPC has given 10% in energy cost economy and 25% improvement in BESS lifetime.

The In-Op Design of Electrical Distribution Systems Based on Microsystem Criteria

This paper deals with an innovative design strategy of building power systems by introducing criteria based on both the “installation approach” and the “operating approach” applying plan-do-check-act (PDCA) cycle. The In-Op design of the electrical power systems takes care of the worst cases of configurations, adequate gaps on load in selecting the rating of components, the actual mean losses to evaluate their energetic operation, and to avoid excessive gaps on the lifetime of components. With this aim, the authors suggest consideration of the thermal aging model of Arrhenius to review the actual gap on load in selecting the rating of components. In reference to IEC standards, this paper underlines in the circuits design the cable steady and transient current densities, the load current torque density as “natural” parameters that allow applying a thumb rule in the classic sizing of the cross-sectional area of circuit conductors. Microsystem criteria in power systems design allow structuring their configuration with components of smaller size to reduce radically the volume of circuit conductors with more sensitive results in the branch distribution. The authors suggest why not reconsider the series of commercial cross section areas of power cables.

Preparing for High-Mix of Renewables in India’s Power Generation

Coal and Renewables (especially solar and wind) are likely to dominate India’s energy mix for quite some time. India is blessed with solar radiation in most parts of the country, and costs are falling rapidly. It is conceivable that power-generation using renewables is likely to come close to 50% by 2030. While this could be great for India, the intermittent power-generation through wind and solar would imply that power-available may fluctuate. Battery Storage could be an answer. Even though cost of Battery Storage is falling rapidly, grid-level storage to arrest power-generation fluctuation would push the prices of electric power beyond “affordability” in India. The other answer is demand side load-management to significantly off-set the supply variation without impacting living and working style significantly. The paper briefs on design of power-system in multi-storied commercial complexes, which would make its electrical load respond to power-surplus and power-deficit scenarios on the grid. When the grid has surplus power, the building would consume power to its full extent, but when there is power-deficit, it will consume minimally. Such buildings are being built today, and if tariffs are designed to benefit commercial complexes which adhere to the above principal, their adoption would be speeded up. The key is that it would benefit the grid, while benefitting the commercial complexes. Besides presenting the concept and designs of power-systems in such buildings, the paper presents some simulation results and some initial measurements on power-consumed in different situations in one such building. The paper also presents some initial idea on how this approach can be extended to powering entire residential and commercial sector.

Configuration Optimization with Operation Strategy of Solar-assisted Building Cooling Heating and Power System to Minimize Energy Consumption

This work designs a novel hybrid building cooling heating and power (BCHP) system incorporating with solar energy and natural gas. A basic natural gas BCHP system containing power generation unit, heat recovery system, hybrid cooling system and storage tank is integrated with solar photovoltaic (PV) and/or thermal collector. Optimization methodology with genetic algorithm (GA) is applied to optimize the configuration of the solar-assisted BCHP system for minimizing primary energy consumption. BCHP schemes are optimized in following electrical load (FEL) and following thermal load (FTL) operation strategies respectively. The result indicates that BCHP system in the FEL mode consumes less energy consumption than in the FTL mode to meet building demands. But the FTL mode would be superior to FEL mode at taking the surplus products from the hybrid BCHP system into consideration.