On-site Renewable Energy Sources Research Articles

Mapping the Potential of Zero-Energy Building in Greece Using Roof Photovoltaics

The present study investigates the incorporation of renewable rooftop photovoltaic systems in fully electrified residential buildings and estimates the zero-energy demand building potential in relation to the climatic data of Greece. Specifically, the aim of the analysis is to calculate the maximum possible number of stories and therefore the total building height for a complete transformation to zero-net-energy building. The energy analysis, which is conducted using the DesignBuilder software, focuses on single-floor up to seven-story buildings. The importance of the present work lies in the acknowledgment of the diversity of the Greek residential sector, the adherence to national energy policies, and the European goal of fully electrified buildings. The examined case studies are equipped with electrically driven air-to-air heat pumps serving the space heating and cooling demands and with an air-to-water heat pump covering the domestic hot water requirements. The investigated locations are the four main cities of Greece, Athens, Thessaloniki, Chania, and Kastoria, which represent the country’s four climatic categories. The conducted analysis allows for the mapping of the zero-energy building potential for the climatic data of Greece, demonstrating the possibility of striking a positive building energy balance through the integration of on-site renewable energy sources and the production of necessary electrical energy. The novelty of the present work lies in the identification of a key factor, namely, the building height, which determines the feasibility of transforming multifamily buildings into zero-energy buildings. According to the analysis results, the critical number of stories is calculated at six for Chania, five for Athens, four for Thessaloniki, and two for Kastoria. Regarding a three-story residential building, the incorporation of a renewable photovoltaic system can result in an annual surplus electricity production of 13,741 kWh (Chania), 10,424 kWh (Athens), and 6931 kWh (Thessaloniki), and a corresponding coverage of 100% (Chania), 69.0% (Athens), 38.9% (Thessaloniki) and 0% (Kastoria).

Optimizing integrated lot sizing and production scheduling in flexible flow line systems with energy scheme: A two level approach based on reinforcement learning

Many production environments are faced with the need to simultaneously determine the planning of lot sizing and the scheduling of production sequences while ensuring cost minimization. This issue becomes even more complex when integrating multiple energy sources with the goal of a low-carbon economy. To address this challenge, this paper proposes an integrated lot sizing and flexible flow line production scheduling model under a time-of-use pricing scheme. In addition, the model takes into account conventional grid power, on-site renewable energy sources, and an energy storage system. The associated objective function is solved adopting a two-level approach to optimize energy costs while maintaining production throughput and meeting customer demand. The implementation relies on reinforcement learning capabilities to tackle complexity issues. The proposed approach is evaluated on a benchmark case and its results are compared with those obtained with First-In-First-Out heuristic, genetic algorithm and CPLEX. These results highlight the promising aspect of the proposed approach in terms of performance.

Quantifying the environmental implication of cotton-Fiber-based Nanocrystalline cellulose: A life-cycle assessment

Considering the increasing demand for nanocrystalline-cellulose in the industry, due to its exceptional physical and biological properties, cheaper and more efficient production processes are sought. Addressing environmental concerns, especially within the framework of EU policies, this study employs Life Cycle Assessment (LCA) to evaluate the environmental performance of a novel nanocrystalline-cellulose production procedure, encompassing biomass depolymerization, rinsing, and bleaching. The LCA aims to identify environmental hotspots, explore mitigation measures, and enables comparisons with other LCA studies on nanocrystalline-cellulose. The results are calculated and reported for 19 environmental impact categories, using the ReCiPe 2016 impact assessment method. The production of 1 kg of dry nanocrystalline-cellulose using the novel process emits 63.7 kg CO2 equivalent, which is lower than the literature average (68 kg CO2 equivalent). The solvent (e.g. diethylene glycol) is the major contributor to the global warming potential and fossil-fuel depletion potential in the product stage of the nanocellulose, while the electricity requirements and glycerin represent environmental hotspots regarding 15 of the 19 impact categories assessed. In terms of the water-consumption potential, the environmental hotspot is production of raw materials (e.g. cotton fibers). Electricity contributes more than 50 % of the burden to the impact categories associated with ionizing radiation, the pollution of aquatic ecosystems and human toxicity related to cancer. It also holds a significant share of the burdens for terrestrial acidification (48 % of the impact), the formation of fine particulate matter (46 % of the impact), and human toxicity related to non-cancer diseases (37 % of the impact). This underscores the importance of optimizing the production process, possibly through upscaling. Additionally, incorporating on-site renewable energy sources and utilizing biomass-derived diethylene glycol can enhance the environmental performance of nanocrystalline-cellulose.

Performance Assessment of Two Different Phase Change Materials for Thermal Energy Storage in Building Envelopes

To meet the 2050 EU decarbonization goals, there is a need for new and innovative ideas to increase energy efficiency, which includes reducing the energy consumption of buildings and increasing the use of on-site renewable energy sources. One possible solution for achieving efficient thermal energy transition in the building sector is to assign new functionalities to the building envelope. The building envelope can function as a thermal energy storage system, which can help compensate for irregularities in solar energy availability. This can be accomplished by utilizing phase change materials as the energy storage medium in the building envelope. In this paper, two phase change materials with different melting temperatures of 21 °C and 28 °C are compared for their application in a dynamic solar building envelope. Both experimental and numerical studies were conducted within the scope of this study. The laboratory testing involved simulating the conditions of the four seasons through steady-state and dynamic experiments. The performance of the phase change materials was evaluated using a small-scale PASLINK test stand that imitates indoor and outdoor conditions. A numerical model of a small-scale building envelope was created using data from laboratory tests. The purpose of this model was to investigate how the tested phase change materials perform under different climate conditions. The experimental findings show that RT21HC is better at storing thermal energy in the PCM and releasing it into the indoor area than RT28HC. On the other hand, the numerical simulation results demonstrate that RT28HC has an advantage in terms of thermal storage capacity in climates found in Southern Europe, as it prevents overheating of the room.

A Review on Mode Transition Strategies between Grid-Connected and Standalone Operation of Voltage Source Inverters-Based Microgrids

Microgrids technologies are seen as a cost effective and reliable solution to handle numerous challenges, mainly related to climate change and power demand increase. This is mainly due to their potential for integrating available on-site renewable energy sources and their flexibility and scalability. The particularity of microgrids is related to their capacity to operate in synchronization with the main grid or in islanded mode to secure the power supply of nearby end-users after a grid failure thanks to storage solutions and an intelligent control system. The most critical operating case occurs when a sudden transition from grid-connected (GC) to stand-alone operation (SA) happens. During the transition, the system experiences abrupt changes that can result in a malfunction of the control system and a possible failure of the power system. The transition issue attracted considerable attention from researchers. Indeed, many research works are proposed to address this issue by proposing detection and transition techniques that ensure a smooth transition at the islanding time. Although there are several approaches to dealing with this issue, a categorization of the proposed methods in the literature and their differences is useful to assist engineers and researchers working on this topic. Thus, this study proposes a comprehensive review to summarize these approaches and point out their advantages and limitations.

Power-to-X in energy hubs: A Danish case study of renewable fuel production

The European Commission recently proposed requirements for the production of renewable fuels as these are required to decarbonize the hard-to-electrify parts of the industrial and heavy transport sectors. Power-to-X (P2X) energy hubs enable efficient synergies between energy infrastructures, production facilities, and storage options. In this study, we explore the optimal operation of an energy hub by leveraging the flexibility of P2X, including hydrogen, methanol, and ammonia synthesizers by analyzing potential revenue streams such as the day-ahead and ancillary services markets. We propose EnerHub2X, a mixed-integer linear program that maximizes the hub’s profit based on current market prices, considering the technical constraints of P2X, such as unit commitment and non-linear efficiencies. We investigate a representative Danish energy hub and find that without price incentives, it mainly sells renewable electricity and produces compressed hydrogen. A sufficient amount of renewable ammonia and methanol is only produced by adding a price premium of about 50% (0.16 €/kg) to the conventional fuel prices. To utilize production efficiently, on-site renewable energy sources and P2X must be carefully aligned. We show that renewable power purchase agreements can provide flexibility while complying with the rules set by the European Commission.

Guest editorial: Application of cloud energy storage systems in power systems

Guest editorial: Application of cloud energy storage systems in power systems

Modelling and simulation of a thermal storage system based on phase change materials integrated in a tertiary building

Decarbonization of the building sector is one of the key challenges to achieve the ambitious goal of carbon neutrality by 2050, established in the European Green Deal. In this sense, current trends focus on the promotion of onsite renewable energy sources, as well as on the electrification of heating and cooling demands and sector coupling approaches through Power-to-heat strategies. This minimizes energy transportation losses while creating an increased need for storage systems. In this scenario, Thermal Energy Storage (TES) systems gain importance and provide the required flexibility, although the experience with high storage periods and volumes, fast response capacity, easy integration into building facilities and cost-effective and environmentally friendly solutions is still scarce. This paper focuses on a TRNSYS (Transient System Simulation Program) modelling and simulation analysis of different integration strategies of a TES system based on Phase Change Materials (PCM) into a real-scale tertiary building. The target building (CARTIF III) is located in Valladolid, Spain, within a Mediterranean climatic area, and incorporates different energy systems including a local photovoltaic (PV) field and a geothermal heat pump (HP). The combination of the PCM storage with the PV and the geothermal HP is studied for the cooling season (in summer) aiming at maximizing the overall system energy efficiency and minimizing the energy import from the grid, thus pursuing a Smart Island concept. Results from this study will feed the solution design for the actual integration project that will be addressed within the framework of a upcoming EU research project.

Hydrogen-Based Networked Microgrids Planning Through Two-Stage Stochastic Programming With Mixed-Integer Conic Recourse

Networked microgrids that integrate the hydrogen fueling stations (HFSs) with the on-site renewable energy sources (RES), power-to-hydrogen (P2H) facilities, and hydrogen storage could help decarbonize the energy and transportation sectors. In this paper, to support the hydrogen-based networked microgrids planning subject to multiple uncertainties (e.g., RES generation, electric loads, and the refueling demands of hydrogen vehicles), we propose a two-stage stochastic formulation with mixed integer conic program (MICP) recourse decisions. Our formulation involves the holistic investment and operation modeling to optimally site and configure the microgrids with HFSs. The MICP problems appearing in the second-stage capture the nonlinear power flow of networked microgrids system with binary decisions on storage charging/discharging status and energy transactions (including the trading of electricity, hydrogen, and carbon credits to recover the capital expenditures). To handle the computational challenges associated with the stochastic program with MICP recourse, an augmented Benders decomposition algorithm (ABD) is developed. Numerical studies on 33- and 47-bus exemplary networks demonstrate the economics viability of electricity-hydrogen coordination on microgrids level, as well as the benefits of stochastic modeling. Also, our augmented algorithm significantly outperforms existing methods, e.g., the progressive hedging algorithm (PHA) and the direct use of a professional MIP solver, which has largely improved the solution quality and reduced the computation time by orders of magnitude. Note to Practitioners—This paper proposes an optimal planning model for electricity-hydrogen microgrids with the renewable hydrogen production, storage, and refueling infrastructures. Our planning model is extended under a two-stage stochastic framework to address the multi-energy-sector uncertainties, e.g., RES generation, electric loads, and the refueling demands of hydrogen vehicles. The first-stage problem is to optimize the siting and sizing plan of microgrids. Then, in the second-stage problem, the coordinated scheduling of electricity and hydrogen supply systems is modeled as second-order conic programs (SOCPs) to accurately capture the power flow representation under stochastic scenarios. Also, the logical constraints with binary variables are introduced to describe the energy transactions and storage operations, which results in an MICP recourse structure. Note that the stochastic MICP formulation could be very challenging to compute even with a moderate number of scenarios. One challenge certainly comes from integer variables that cause the problem nonconvex. Another challenge follows from the fact that the strong duality of SOCPs might not hold in general. To mitigate those two challenges, we prove that the continuous relaxation of our recourse problem has strong duality, and make use of that continuous relaxation and other enhancements to design an augmented decomposition algorithm. As revealed by our numerical tests, the proposed decomposition method outperforms PHA in both the solution quality and computational efficiency. Comparing to the PHA, our ABD method often achieves tighter bounds with trivial optimality gaps. Also, it could reduce the computation time by orders of magnitude. With the help of advanced analytical tool, the proposed planning framework can be readily implemented in real-world applications.

Energy management of Internet data centers in multiple local energy markets

Active distribution network Internet Data Centers (IDCs) are large energy consumers in modern distribution networks. The integration of renewable energy and energy storage systems transforms IDCs into proactive energy prosumers, and enables them to participate in the energy trading in regional local energy markets. This paper proposes an energy management framework for a Cloud Service Provider (CSP) that manages multiple geographically distributed IDCs. The framework provides decision-making support for the CSP to optimally schedule the IDCs’ cyber-energy resources (computing requests, on-site battery energy storage systems, and on-site renewable energy sources). In this way, the proposed framework facilitates the CSP to proactively participate in the local energy markets situated in the regions that host the IDCs, with the objective to minimize the CSP's total cost over a finite operation horizon. We use an effective evolutionary computation algorithm to solve the proposed energy management model and design extensive numerical simulations to validate the effectiveness of the proposed method.

Multi-Objective and Cooperative Power Planning for Datacenter With On-Site Renewable Energy Sources

Multi-Objective and Cooperative Power Planning for Datacenter With On-Site Renewable Energy Sources

Reliability-based energy scheduling of active buildings subject to renewable energy and demand uncertainty

The increasing penetration of renewable energy sources (RESs) and the inherent volatility in demand profiles have added another layer of complexity to the management of energy resources in modern active buildings (ABs). Yet, three challenges have been neglected in previous studies: (1) There is no universal systematic method for identifying an AB’s general stochastic model; (2) No research has been conducted on the reliability-based design optimization for ABs’ energy supply; (3) Uncertain sources are not categorized based on their importance in regard to the optimization problem. This article aims to solve these challenges by proposing a probabilistic-based optimization approach for solving the reliability issue of energy supply in buildings with on-site renewable energy sources (RESs), taking into account the uncertainty associated with photovoltaic (PV) production and demand fluctuations. The suggested framework seeks to reduce the overall costs of the system while ensuring high energy supply reliability. The proposed methodology, when applied to a real-world case study, demonstrates a 60% increase in reliability of energy supply as compared to typical deterministic methodologies.

An Assessment of Renewable Energies in a Seawater Desalination Plant with Reverse Osmosis Membranes.

The purpose of our study was to reduce the carbon footprint of seawater desalination plants that use reverse osmosis membranes by introducing on-site renewable energy sources. By using new-generation membranes with a low energy consumption and considering wind and photovoltaic energy sources, it is possible to greatly reduce the carbon footprint of reverse osmosis plants. The objective of this study was to add a renewable energy supply to a desalination plant that uses reverse osmosis technology. During the development of this research study, photovoltaic energy was discarded as a possible source of renewable energy due to the wind conditions in the area in which the reverse osmosis plant was located; hence, the installation of a wind turbine was considered to be the best option. As it was a large-capacity reverse osmosis plant, we decided to divide the entire desalination process into several stages for explanation purposes. The desalination process of the facility consists of several phases: First, the seawater capture process was performed by the intake tower. This water was then transported and stored, before going through a physical and chemical pre-treatment process, whereby the highest possible percentage of impurities and organic material was eliminated in order to prevent the plugging of the reverse osmosis modules. After carrying out the appraisals and calculating the amount of energy that the plant consumed, we determined that 15% of the plant’s energy supply should be renewable, corresponding to 1194 MWh/year. As there was already a wind power installation in the area, we decided to use one of the wind turbines that had already been installed—specifically, an Ecotecnia turbine (20–150) that produced an energy of 1920 MWh /year. This meant that only a single wind turbine was required for this project.

On-site renewable energy for industrial buildings in Sri Lanka: a life-cycle cost analysis

ABSTRACT Industrial sector consumes a substantial portion of electrical energy. Building owners persistently believe that combining on-site renewable energy systems to buildings is not cost-effective in Sri Lanka. Therefore, this research aimed to evaluate the use of on-site renewable energy sources for industrial buildings in Sri Lanka. This research carried out 10 expert interviews and 6 case studies. Experts determined that solar and biomass as viable on-site energy generating sources in Sri Lanka. Life-cycle cost was calculated for six case studies representing three case studies for each viable option followed by a sensitivity analysis. Based on the research findings, biomass can effectively manage waste while eliminating the risk of the emission of harmful biomethane. Based on the calculations, the payback period for a solar system varies between 4 and 6 years and biomass system varies between 6 and 7 years. This research explored the potential of generating on-site renewable energy for industrial building. Although the ‘on-site’ energy generation is not widely discussed in industrial buildings, this research study strengthened the possibility of adopting solar and biomass as on-site renewable energy generation sources.

The Use of Ground Source Heat Pump to Achieve a Net Zero Energy Building

Currently, ground source heat pump (GSHP) technology is being studied, as the use of the ground as a source of renewable energy allows significant energy savings to be obtained. Therefore, it is useful to quantify how these savings help to achieve the energy balance of a Net Zero Energy Building (NZEB) compared to an air source heat pump or a condensing boiler coupled to a chiller. This paper assesses how these savings affect the number of photovoltaic panels installed on the roof of a building to obtain the NZEB target. The study is conducted by dynamic simulation for a building used as a bed and breakfast, virtually placed in two Italian towns. The energy savings and reduction of CO2 emissions, the percentage of renewable energy used, and the photovoltaic surface needed are assessed. Finally, the discounted payback period is calculated. The results show that the GSHP, unlike the systems to which it is compared, allows an NZEB to be obtained by balancing yearly energy consumption with energy production systems which only use on-site renewable energy sources (by exploiting the surface available on the roof) for both of the climatic conditions considered. GSHP also allows primary energy requests equal to or less than 57 kWh/m2 to be obtained.

Modeling of Heating and Cooling Energy Needs in Different Types of Smart Buildings

Over the last decades, the growing energy consumption of commercial and residential buildings has considerably increased the energy-related carbon dioxide (CO2) emissions. At EU level, the Energy Performance of Buildings Directive (EPBD) has introduced the transformation of buildings into nearly zero energy buildings (nZEBs) that cover the majority of their low energy demand by on-site renewable energy sources. In this direction, the project PV-ESTIA “Enhancing storage integration in buildings with Photovoltaics” aims at developing and validating various optimal energy management strategies in buildings equipped with Photovoltaics (PV) and storage systems. One of the main requirements for the application of the developed strategies is the accurate computation of energy consumption, and particularly, of heating and cooling energy needs. In this paper, a simple and accurate model based on the “grey-box” concept is proposed for the computation of hourly thermal energy needs in different types of premises by using the standard ISO 52016-1:2017. The method's performance is evaluated by comparing the results with those of other simulation programs for ten European cities with climatic variations. It is concluded that the proposed model presents high accuracy on the computation of the operative temperature, since it considers the air temperature, as well as the temperatures and the areas of the internal surfaces. Finally, any deviations with the other simulation tools are due to differences in the internal air temperature, weather data, as well as the approaches of ventilation and shading effects.

Estimation of Energy Activity and Flexibility Range in Smart Active Residential Building

The smart active residential buildings play a vital role to realize intelligent energy systems by harnessing energy flexibility from loads and storage units. This is imperative to integrate higher proportions of variable renewable energy generation and implement economically attractive demand-side participation schemes. The purpose of this paper is to develop an energy management scheme for smart sustainable buildings and analyze its efficacy when subjected to variable generation, energy storage management, and flexible demand control. This work estimate the flexibility range that can be reached utilizing deferrable/controllable energy system units such as heat pump (HP) in combination with on-site renewable energy sources (RESs), namely photovoltaic (PV) panels and wind turbine (WT), and in-house thermal and electric energy storages, namely hot water storage tank (HWST) and electric battery as back up units. A detailed HP model in combination with the storage tank is developed that accounts for thermal comforts and requirements, and defrost mode. Data analytics is applied to generate demand and generation profiles, and a hybrid energy management and a HP control algorithm is developed in this work. This is to integrate all active components of a building within a single complex-set of energy management solution to be able to apply demand response (DR) signals, as well as to execute all necessary computation and evaluation. Different capacity scenarios of the HWST and battery are used to prioritize the maximum use of renewable energy and consumer comfort preferences. A flexibility range of 22.3% is achieved for the scenario with the largest HWST considered without a battery, while 10.1% in the worst-case scenario with the smallest HWST considered and the largest battery. The results show that the active management and scheduling scheme developed to combine and prioritize thermal, electrical and storage units in buildings is essential to be studied to demonstrate the adequacy of sustainable energy buildings.

The future of modernist housing estates: the “Replace vs Refurbish” dilemma in the context of future urban densification

The aim of this paper is to present a part of the research developed inside the author’s dissertation topic which deals with the future of large modernist housing estates. The central question of the dissertation investigates which of the currently dominating tendencies - their replacement or refurbishment - result in lower energy consumption and provides more sustainable use of natural resources within the context of future urban densification. The presented workflow combines actions contained in the first step of the research methodology built around the abovementioned dilemma. It explores the solar energy harvesting potential of various urban forms and densification scenarios, proposed inside the main “refurbishment” and “replacement” approaches, including both retain and demolition options of the existing building stock located in the Nordweststadt housing estate in Frankfurt, Germany. All scenarios are tested against maximal density rate which secures enough operational energy from on-site renewable energy sources for the achievement of the zero energy building (ZEB) standard. The expected outcome of this paper gives an insight which of the proposed densification scenarios from both approaches generate the highest density rate in respect to the given boundary conditions, and compares the energy balance between the best performing scenarios in both approaches at the same density level.

Integration of Onsite Renewable Energy Sources and To Validate Zero Energy Buildings

At present, the buildings are account for about 40% of total global energy and also 1/3rd of GHG emissions. All buildings are having the provision of onsite renewable energy power generation, but unable to tap these resources in most of the cases. If, these resources can be tapped properly and integrated to the buildings will solve the problem of global energy shortage and also less impact on GHG emissions. In this paper, an analysis has been done by using HOMER software to estimate the capacity of onsite renewable energy sources and its integration to Zero Energy Buildings. Finally, an economical solution has been given towards integration of onsite renewable energy sources with any type of building and to make them as Zero Energy buildings.

Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities

In the last few years, the application of Model Predictive Control (MPC) for energy management in buildings has received significant attention from the research community. MPC is becoming more and more viable because of the increase in computational power of building automation systems and the availability of a significant amount of monitored building data. MPC has found successful implementation in building thermal regulation, fully exploiting the potential of building thermal mass. Moreover, MPC has been positively applied to active energy storage systems, as well as to the optimal management of on-site renewable energy sources. MPC also opens up several opportunities for enhancing energy efficiency in the operation of Heating Ventilation and Air Conditioning (HVAC) systems because of its ability to consider constraints, prediction of disturbances and multiple conflicting objectives, such as indoor thermal comfort and building energy demand. Despite the application of MPC algorithms in building control has been thoroughly investigated in various works, a unified framework that fully describes and formulates the implementation is still lacking. Firstly, this work introduces a common dictionary and taxonomy that gives a common ground to all the engineering disciplines involved in building design and control. Secondly the main scope of this paper is to define the MPC formulation framework and critically discuss the outcomes of different existing MPC algorithms for building and HVAC system management. The potential benefits of the application of MPC in improving energy efficiency in buildings were highlighted.