With the gradual depletion of fossil energy sources and the improvement in environmental protection attention, efficient use of energy and reduction in carbon emissions have become urgent issues. The integrated electricity and heating energy system (IEHS) is a significant solution to reduce the proportion of fossil fuel and carbon emissions. In this paper, a stochastic optimization model of the IEHS considering the uncertainty of wind power (WP) output and carbon capture power plants (CCPs) is proposed. The WP output in the IEHS is represented by stochastic scenarios, and the scenarios are reduced by fast scenario reduction to obtain typical scenarios. Then, the conventional thermal power plants are modified with CCPs, and the CCPs are equipped with flue gas bypass systems and solution storage to form the integrated and flexible operation mode of CCPs. Furthermore, based on the different load demand responses (DRs) in the IEHS, the optimization model of the IEHS with a CCP is construct... [more]

In this study, optimal allocation and planning of power generation resources as distributed generation with scheduling capability (DGSC) is presented in a smart environment with the objective of reducing losses and considering enhancing the voltage profile is performed using the manta ray foraging optimization (MRFO) algorithm. The DGSC refers to resources that can be scheduled and their generation can be determined based on network requirements. The main purpose of this study is to schedule and intelligent distribution of the DGSCs in the smart and conventional distribution network to enhance its operation. First, allocation of the DGSCs is done based on weighted coefficient method and then the scheduling of the DGSCs is implemented in the 69-bus distribution network. In this study, the effect of smart network by providing real load in minimizing daily energy losses is compared with the network includes conventional load (estimated load as three-level load). The simulation results cle... [more]

Several technical, computational, and economic barriers have caused curtailing a share of renewable-based power generation, especially in systems with higher penetration levels. The Mobile Battery Energy Storage (MBES) can cope with this problem considering the spatial and temporal distribution of the curtailed energy. Accordingly, a new operation model is proposed for optimal scheduling of the MBES in a distribution network with wind and photovoltaic (PV) resources. The network experiences curtailment situations because of bus overvoltage, feeder overload, and power over-generation. The MBES is a truck-mounted battery system compacted in a container. The proposed model seeks to determine the optimal spatio-temporal and power−energy status of the MBES to achieve a minimum curtailment ratio. The model considers transportation time and cost of the MBES efficiently while both active and reactive power exchanges are modeled. The model is linear, without convergence and optimality problems,... [more]

Various algorithms predominantly use data-driven methods for forecasting building electricity consumption. Among them, algorithms that use deep learning methods and, long and short-term memory (LSTM) have shown strong prediction accuracy in numerous fields. However, the LSTM algorithm still has certain limitations, e.g., the accuracy of forecasting the building air conditioning power consumption was not very high. To explore ways of improving the prediction accuracy, this study selects a high-rise office building in Shanghai to predict the air conditioning power consumption and lighting power consumption, respectively and discusses the influence of weather parameters and schedule parameters on the prediction accuracy. The results demonstrate that using the LSTM algorithm to accurately predict the electricity consumption of air conditioners is more challenging than predicting lighting electricity consumption. To improve the prediction accuracy of air conditioning power consumption, two... [more]

This article deals with the new challenges facing modernising railways in Poland. We look at the problem of the efficiency of the power supply system (3 kV DC) used in the context of the increasing use of electric vehicles, which have a higher demand for electricity than the old type. We present and characterise the power supply system in use, pointing out its weaknesses. We consider a case study. The load of the power supply network generated by the rolling stock used in Poland was examined using a microsimulation. A real train timetable was taken into account on a fragment of one of the most important railway line sections in one of the urban agglomerations. Then the results were compared with the results of a microsimulation in which old units were replaced by new trains. These tests were carried out in several variants. We found critical points in the scheduling of railway system use. Our results indicate that it is becoming increasingly necessary to take into account the permissib... [more]

Integrated energy systems have become an important research topic in the pursuit of sustainable energy development. This paper examines regional integrated energy systems, presents the typical architecture of regional integrated energy systems, and builds an integrated energy system model. Two evaluation indexes are proposed: the integrated energy self-sufficiency rate and the expected energy deficiency index. Based on these evaluation indexes and taking into account the uncertainty of wind power generation, a bi-level optimization model based on meta-heuristic algorithms and multi-objective programming is established to solve the problem of regional integrated energy system planning under different load structures and for multi-period and multi-scenario operation modes. A quantum evolutionary algorithm is combined with genetic algorithms to solve the problem.

Climate change and expected weather patterns in the long-term threaten the livelihood inside oases settlements in arid lands, particularly under the recurring heat waves during the harsh months. This paper investigates the impact of climate change on the outdoor thermal comfort within a multifamily housing neighborhood that is considered the most common residential archetype in Algerian Sahara, under extreme weather conditions in the summer season, in the long-term. It focuses on assessing the outdoor thermal comfort in the long-term, based on the Perceived Temperature index (PT), using simulation software ENVI-met and calculation model RayMan. Three different stations in situ were conducted and combined with TMY weather datasets for 2020 and the IPCC future projections: A1B, A2, B1 for 2050, and 2080. The results are performed from two different perspectives: to investigate how heat stress evolution undergoes climate change from 2020 till 2080; and for the development of a mathematica... [more]

This study aims to plan a cost-minimizing charging schedule for electric buses with fast charging stations. The paper conceptualizes the problem as a three-stage procedure, which is oriented around the participation of an electric bus aggregator in a day-ahead energy auction. First, the aggregation stage determines the bid parameters of buses. With bid parameters, aggregated cost-minimizing charging plans are obtained in the second stage conceived as the hourly day-ahead auction. The disaggregation of hourly plans into feasible minutely charging schedules is the third stage. The main contribution is the formulation of mixed-integer linear programming aggregation models to determine charging availability expressed as minimum and maximum hourly energy requirements taking into account detailed, minutely characteristics and constraints of the charging equipment and the buses. No price forecasts are required, and the plans adjust to the wholesale prices of energy. Defining only a few aggreg... [more]

The implementation of monitoring tools and energy management systems (EnMSs) supports companies in their long-term energy efficiency strategies, and they are essential to analyse the effectiveness of energy performance improvement actions (EPIAs). The first fundamental step towards increasing energy efficiency is the development of energy audits (EAs). EAs provide comprehensive information about the energy usage in a specific facility, identifying and quantifying cost-effective EPIAs. The crucial role of these tools in clean energy transition is remarked by the European Energy Efficiency Directive (EED), which promotes the implementation of EAs and EnMS programmes. The purpose of this work is to better understand the link between EnMSs (specifically ISO 50001) and EAs in the EED Article 8 implementation in two industrial and two tertiary sectors in Italy. Moreover, the impact of company size, energy monitoring systems, and EnMSs on planned and/or implemented EPIAs is analysed. Our find... [more]

The power system is changing towards a decarbonized one. The Kyoto protocol and the Paris climate agreement have prompted many nations to approve energy policies based on volatile renewable energy sources (RESs). However, the integration into the grid of the power generated by RESs as well as the electrification of the heating, gas and transportation sectors is becoming a huge challenge. Planning industrial and tertiary sites as net-zero energy systems (NZESs) might contribute to advance the solutions of fully integrating volatile RESs into the power system. This study aims to point out the importance of planning large energy consumer sites such as NZESs, and to depict a holistic modeling approach for this. The methodology is based on a multi-layer approach, which focuses on on-site power generation by RESs, on the improvement of energy efficiency, and on the increase of system flexibility. A qualitative case study has been conducted. It considers the planning of a Net-Zero Energy Data... [more]

Construction time and time overruns for infrastructure projects have been frequently studied; however, the construction time of power plants has not been studied. This lack of study is problematic, as more renewable energy power plants, such as wind and solar, are planned for many jurisdictions. Accurately estimating the construction time of a power plant will assist construction planning, budget estimates, and policy development encouraging the use of more renewable sources. The construction times of utility scale power plants in Canada were studied using publicly available data. Multiple linear regression analysis techniques were applied to the data to generate construction time estimation functions for all power plants together, and for individual technologies. The analyses reveal that construction time is sensitive to jurisdiction and the decade of construction, indicating that decisions made by individual Canadian provincial governments at different times had statistically signifi... [more]

Optimal scheduling strategy of integrated energy systems (IES) with combined cooling, heating and power (CCHP) has become increasingly important. In order to make the scheduling strategy fit to the practical implementation, this paper proposes a variable performance parameters temperature−flowrate scheduling model for IES with CCHP. The novel scheduling model is established by taking flowrate and temperature as decision variables directly. In addition, performance parameters are treated as variables rather than constants in the proposed model. Specifically, the efficiencies of the gas turbine and the waste heating boiler are estimated with the partial load factor, and the coefficient of performance (COP) of the electrical chillers and heat pumps are estimated with the partial load factor and outlet water temperature. Then, to deal with the model nonlinearities caused by considering the variability of COPs, the COP-expansion method is developed by adopting a specific representation of t... [more]

Energy firms are the beneficiaries and initiators of innovation, and energy investments are a crucial area of business activity that is specially protected in any country. This is no wonder, as energy security is the basis for the functioning of states and economies. The Internet of Things and Big Data create both new challenges and new threats. This study aimed to identify the potential threats and determine preventive measures, as well as to establish the agile principles related to energy firms’ logistics. The method of the narrative summary in combination with the literature searching method was used. Two conclusions emerged: first, research serves to develop the discipline of management science; second, the identification of risks associated with innovation serves practitioners. In addition, the study defined further research directions.

Power system operators are in search of proven solutions to improve the penetration levels of distributed generators (DGs) in the grid while minimizing cost. This transition is driven, among others, by global climate concerns, the growing power demand, the need for greater flexibility, the ageing grid infrastructure and the need to diversify sources of energy production. Distributed renewables would not easily substitute the conventional electric grid system, perhaps because the latter is a well-established technology and it would not be prudent to abandon it, while the new distributed renewable energy technologies are generally not adequately developed to support the total load. Thus, it is becoming increasingly necessary to consider sustainable options such as integrating renewable energy sources into the existing power grid. This study is a review that is mainly hinged on distributed generation (DG) classification, the challenges of DG to grid integration, practical options used in... [more]

Electric vehicles’ (EVs) technology is currently emerging as an alternative of traditional Internal Combustion Engine (ICE) vehicles. EVs have been treated as an efficient way for decreasing the production of harmful greenhouse gasses and saving the depleting natural oil reserve. The modern power system tends to be more sustainable with the support of electric vehicles (EVs). However, there have been serious concerns about the network’s safe and reliable operation due to the increasing penetration of EVs into the electric grid. Random or uncoordinated charging activities cause performance degradations and overloading of the network asset. This paper proposes an Optimal Charging Starting Time (OCST)-based coordinated charging algorithm for unplanned EVs’ arrival in a low voltage residential distribution network to minimize the network power losses. A time-of-use (ToU) tariff scheme is used to make the charging course more cost effective. The concept of OCST takes the departure time of E... [more]

The maximization of output from variable renewable energy (VRE) sources considering system operational constraints (SOCs) is a traditional method for maximizing VRE generators’ profits. However, in wholesale electricity markets, VRE participation tends to reduce marginal prices (MP) because of its low marginal costs. This circumstance, called the “merit-order effect” (MOE), reduces the generators’ profits. Thus, the traditional method is possibly no longer the best and only method to maximize the generators’ profits. Moreover, the VRE support schemes also affect MP, making MOE more severe. VRE curtailment can relieve MOE, but VRE output must be decreased, thereby reducing the generators’ profits. This paper proposes a method to find the optimal VRE generation schedules that maximize VRE generators’ profits while considering the trade-off among the VRE output, MP, and SOCs. The method combines the merit-order model and the unit-commitment model solved by the optimization tools in MATLAB... [more]

After the awareness-raising of recent years for coping with the global societal, economic and environmental challenges, the need for sustainable planning in the transport sector has become even more evident. Initiatives aiming at promoting sustainable and innovative mobility solutions, especially in urban areas where mobility needs are higher and transport problems are more intense, have been launched by different organizations around the world. In this context, autonomous electric vehicles are emerging as a promising solution; however, they are accompanied by new infrastructure requirements, along with safety concerns. Policymakers will be confronted with an array of choices, such as plug-in or wireless, dynamic or stationary charging and mixed flow with conventional vehicles or dedicated lanes, taking into account the uncertain impacts of innovation on safety and sustainability. Within this scope, these infrastructure alternatives are evaluated and prioritized, for the first time, in... [more]

The increasing integration of renewable energies into the grid is calling for the expansion of the power transport capacities in the distribution system. Yet, the expansion of the grid could require long authorization procedures and cannot be always asserted. Therefore, a higher utilization of the existing grid is becoming increasingly necessary today. This paper proposes a new time series-based planning method for distribution systems using classical grid expansion instruments as well as innovative planning instruments such as battery storage systems (BSS) and dynamic power curtailment (DPC). These planning instruments could be applied individually or combined. The aim of the BSS and DPC application is to enable a higher utilization of the grid at minimal costs. The proposed method, which has been implemented as an automated planning algorithm, determines the cost-optimal grid reinforcement measures that ensure the prevention of prognosticated congestions in the considered grid. Furth... [more]

Several problems can be encountered in the design of autonomous vehicles. Their software is organized into three main layers: perception, planning, and actuation. The planning layer deals with the sort and long-term situation prediction, which are crucial for intelligent vehicles. Whatever method is used to make forecasts, vehicles’ dynamic environment must be processed for accurate long-term forecasting. In the present article, a method is proposed to preprocess the dynamic environment in a freeway traffic situation. The method uses the structured data of surrounding vehicles and transforms it to an occupancy grid which a Convolutional Variational Autoencoder (CVAE) processes. The grids (2048 pixels) are compressed to a 64-dimensional latent vector by the encoder and reconstructed by the decoder. The output pixel intensities are interpreted as probabilities of the corresponding field is occupied by a vehicle. This method’s benefit is to preprocess the structured data of the dynamic en... [more]

Modelling tools and transport models are required to assess the impact of measures for the effective planning of cycling routes in cities. This paper presents the methodology for developing a four-stage macroscopic model of bicycle traffic for the city of Gdynia, and its use in planning new bicycle routes, considering a modal shift. The model presented in this paper allows for the evaluation of the influence of the characteristics of the cycling infrastructure, along with the development of the cycling network based on the choice of cycling as an alternative to other modes of transport, by taking into account the modal shift. The model takes into account the influence of the longitudinal gradient, link, and surface type of cycling routes on the distribution and demand for bicycle traffic. The results of our research allow us to assess the impact of planned cycling routes on the reduction in the volume of car traffic, which is crucial for reducing energy consumption and negative environ... [more]

High-performance districts and communities offer opportunities for reducing energy use, emissions, and costs, and can be instrumental in helping cities achieve their climate goals. The design of such communities requires identification of opportunities early on and their re-evaluation throughout the planning process. There is a need for energy modeling tools that connect 3D Computer-Aided Design (CAD) platforms to simulation engines, enabling detailed energy analysis of districts within the workflows and tools used by practitioners. This paper introduces the Dragonfly and URBANoptTM combined toolset that supports the creation of urban models from a range of geometry formats typically used by designers and planners, and provides an integrated pathway to simulate district-scale energy systems. The toolset is piloted by a global architecture and master planning firm to evaluate several key urban-scale technical questions for the design of a district in Chicago. The findings indicate that,... [more]

Territorial energetic and environmental planning provides operational solidity to the concept of sustainable development, in particular in energy-related issues, where recent attention to and social awareness of climate change are driving actions and policies at local and international levels. The goals of the United Nations Agenda 2030 can be reached through the strategy of glocalization, giving more responsibility to local administrations like municipalities. In this work, a scientific methodology is developed and validated to revise Sustainable Energy Action Plans (SEAP) and the monitoring phase of municipalities. The methodology starts from measured data in the territory considered and makes use of specific statistical models in order to estimate the needed data. The methodology considers the energy consumption of the main sectors: residential, transportation, tertiary, and commercial, with a particular focus on municipal competences (public lighting, urban transport, municipal fle... [more]

Optimal planning of a remote area electricity supply (RAES) system is a vital challenge to achieve a reliable, clean, and cost-effective system. Various components like diesel generators, renewable energy sources, and energy storage systems are used for RAES systems. Due to the different characteristics and economic features of each component, optimal planning of RAES systems is a challengeable task. This paper presents an overview of the optimal planning procedure for RAES systems by considering the important components, parameters, methods, and data. A timely review on the state of the art is presented and the applied objective functions, design constraints, system components, and optimization algorithms are specified for the existing studies. The existing challenges for RAES systems’ planning are recognized and discussed. Recent trends and developments on the planning problem are explained in detail. Eventually, this review paper gives recommendations for future research to explore... [more]

The technology of cold ironing (or shore-to-ship power) can meaningfully reduce greenhouse gases and air pollutant emissions from ships at the berth by powering the vessels from the electrical shore grid. While cold ironing constitutes an effective and affordable solution in northern Europe and America, economic, legal, and environmental factors still render this technology less attractive in southern Europe. This paper aims to unpack and analyze the economic, regulatory, and environmental factors that can foster cold ironing as a standard installation in the Mediterranean Sea. Based on a model design for the port of Trieste (Italy) as applied to a cluster of target ports in the Adriatic Sea (in Italy, Croatia, and Greece), this article evaluates the cold ironing payback period by comparing costs of shore side-plants with environmental externalities and O&M costs. Moreover, the paper addresses key regulatory bottlenecks arising in different European jurisdictions with regard to the set... [more]

Process planning in manufacturing today focuses on optimizing the conflicting targets of cost, quality, and time. Due to increasing social awareness and subsequent governmental regulation, environmental impact becomes a fourth major aspect. Eventually, sustainability in manufacturing ensures future competitiveness. In this paper, a framework for the planning of sustainable manufacturing is proposed. It is based on the abstraction and generalization of manufacturing resources and part descriptions, which are matched and ranked using a multi-criteria decision analysis method. Manufacturing resources provide values for cost, quality, time and environmental impacts, which multiply with their usage within a manufacturing task for a specific part. The framework is validated with a detailed modeling of a laser machine as a resource revealing benefits and optimization potential of the underlying data model. Finally, the framework is applied to a use case of a flange part with two different man... [more]