With the development of ecological economics, energy-saving green energy chain management has been a wide concern of academia and industries. However, the relatively high cost of green investment makes manufacturers face the problem of financial constraints. On this basis, because the green level information of products is proprietary to manufacturers, manufacturers will lie about the green level of products in order to improve their profits out of the principle of profit maximization. As a result, banks cannot obtain the true green level of products, reducing the benefits of the green energy-efficient supply chain system and making the market of green products volatile. In view of this, blockchain technology is introduced in this paper to improve customer’s product green level sensitivity and obtain lower green credit interest rates from banks. In this paper, a green supply chain financing model based on blockchain technology was constructed under the condition of green information mi... [more]

Globally, renewable energies are indispensable resources on account of RE100 and the Paris Agreement. The most developed renewable energies are photovoltaics (PV) and wind energy, and they are continuously expanding. This study aims to optimize and analyze the nuclear power plant (NPP) load-following operation in various PV conditions in a metropolitan region. With theoretically estimated power demand and PV power, a mixed-integer problem (MIP) with ramping cycle constraint (RCC) was constructed for a safe load-following operation and simulated through duck curves under various NPP load-following regions (the extreme, normal, and safe regions). The simulation showed two major results for NPP load-following. Technically, RCC successfully controlled the NPP ramp cycle and was assured to be an optimization tool for NPP operation. Numerically, NPP load-following alleviated PV intermittency to almost 50%, 30%, and 15% depending on the load-following region. However, these effects were restr... [more]

This paper focuses on the application using a solar-powered unmanned aerial vehicle (UAV) to inspect mountain sites for the purpose of safety and rescue. An inspection path planning problem is formulated, which looks for the path for an UAV to visit a set of sites where people may appear while avoiding collisions with mountains and maintaining positive residual energy. A rapidly exploring random tree (RRT)-based planning method is proposed. This method firstly finds a feasible path that satisfies the residual energy requirement and then shortens the path if there is some abundant residual energy at the end. Computer simulations are conducted to demonstrate the performance of the proposed method.

Residential water heaters use a substantial amount of electrical energy and contribute to 25% of the energy usage in the residential sector. This raises concern for users in countries with flat rate electricity fees and where fossil fuels are used for electricity generation. Demand side management of tanked water heaters is well suited for energy-focused load reduction strategies. We propose a strategy for providing an electric water heater (EWH) with the optimal temperature planning to reduce the overall electrical energy usage while satisfying the comfort of the user. A probabilistic hot water usage model is used to predict the hot water usage behaviour for the A*-based optimisation algorithm, which accounts for water stratification in the tank. A temperature feedback controller with novel temperature and energy-correcting capabilities provides robustness to prediction errors. Three optimal control strategies are presented and compared to a baseline strategy with the thermostat alway... [more]

Compared with static transmission network expansion planning (TNEP), multi-stage TNEP is more in line with the actual situation, but the modeling is also more complicated. This paper proposes a new multi-stage TNEP method based on the deep Q-network (DQN) algorithm, which can solve the multi-stage TNEP problem based on a static TNEP model. The main purpose of this research is to provide grid planners with a simple and effective multi-stage TNEP method, which is able to flexibly adjust the network expansion scheme without replanning. The proposed method takes into account the construction sequence of lines in the planning and completes the adaptive planning of lines by utilizing the interactive learning characteristics of the DQN algorithm. In order to speed up the learning efficiency of the algorithm and enable the agent to have a better judgment on the reward of the line-building action, the prioritized experience replay (PER) strategy is added to the DQN algorithm. In addition, the e... [more]

The article presents an analysis of geographical-settlement and legal-planning conditions for the development of Poland’s distributed generation. The choice of this country is important and interesting due to the highly dispersed settlement, which may be a factor stimulating the development of this type of energy systems. For this reason, the analysis can be a model for other countries and regions, indicating ways to analyze and evaluate settlement and planning conditions for the development of renewable and distributed energy. At the same time, Poland is struggling with a severe crisis of spatial planning. By analysing these opportunities and threats, empirical analyses try to indicate regularities in this respect in Poland’s regions in a detailed approach to communes and detailed legal and planning conditions. The conclusions emphasise the usefulness of distributed generation development for peripheral and sparsely populated areas of Europe and other parts of the world and appropriat... [more]

Within the current context of energy transition, the first step to assure cost-efficient and reliable grid operations is the use of adequate planning tools. These tools must evaluate the real needs for reinforcing, replacing and incorporating new network assets considering not only technical and regulatory aspects but also the operational benefits that distributed energy resources (DER) may provide. With this purpose, this paper presents a novel methodology for the analysis and the advanced planning of the active distribution networks in the context of smart grids. The main contributions of the proposed methodology are the following: to incorporate the real capabilities of DER proactively to the planning and operation of distribution networks; to appropriately use the data available in current smart grids; and to promote the efficient use of network capacity in distribution level (efficiency decisions of its users, grid assets in service, access conditions, etc.) through potential oper... [more]

One of the tools to attain the goal of climate-neutrality by 2050 by the European Union is increasing the share of renewable energy sources (RESs) in the energy mix of member states. A major part of the future bioenergy mix is to be played by biomass. As many hazards have been pointed out when using forest biomass, particular attention is paid to the potential of agro biomass. However, as agro biomass is sourced mostly locally, the supply may not be sufficient to meet the growing demand. Therefore, international trade (including overseas) might become increasingly important to meet the EU renewable energy targets. In this context, it is seaports that may play a major part in developing biomass supply chains. The main purpose of the article is to fill the research gap by identifying the pros and cons for the development of biomass sea-based supply chains through secondary ports and specifying their relevance from the perspective of major stakeholders in the context of decarbonization pr... [more]

With the rapid development of the Internet of Things (IoT) and artificial intelligence, autonomous vehicles have received much attention in recent years. Safe driving is one of the essential concerns of self-driving cars. The main problem in providing better safe driving requires an efficient inference system for real-time task management and autonomous control. Due to limited battery life and computing power, reducing execution time and resource consumption can be a daunting process. This paper addressed these challenges and developed an intelligent task management system for IoT-based autonomous vehicles. For each task processing, a supervised resource predictor is invoked for optimal hardware cluster selection. Tasks are executed based on the earliest hyper period first (EHF) scheduler to achieve optimal task error rate and schedule length performance. The single-layer feedforward neural network (SLFN) and lightweight learning approaches are designed to distribute each task to the a... [more]

At present, electric vehicles (EVs) are attracting increasing attention and have great potential for replacing fossil-fueled vehicles, especially for logistics applications. However, energy management for EVs is essential for them to be advantageous owing to their limitations with regard to battery capacity and recharging times. Therefore, inefficiencies can be expected for EV-based logistical operations without an energy management plan, which is not necessarily considered in traditional routing exercises. In this study, for the logistics application of EVs to manage energy and schedule the vehicle route, a system is proposed. The system comprises two parts: (1) a case-based reasoning subsystem to forecast the energy consumption and travel time for each route section, and (2) a genetic algorithm to optimize vehicle routing with an energy consumption situation as a new constraint. A dynamic adjustment algorithm is also adopted to achieve a rapid response to accidents in which the vehic... [more]

Economic analysis allows for determining the required daily output under certain natural and mining conditions based on the costs of the production process in a particular mine infrastructure. Therefore, there is a need to determine the potential daily output of a longwall using the technical equipment at the disposal of the mine. In the case of mines, when exploiting a few longwalls simultaneously in the conditions of bumping hazards, it is indispensable to ensure safety. Due to a necessity of keeping a safe distance among the longwall fronts, when planning their exploitation, developing a prediction of the longwalls in advance during the planning period is needed. To predict the daily production from a longwall and daily advance of the longwall in the analyzed period, it is necessary to know the current operating time of machines and the capacity of the shearer under given conditions. The current working time of machines results from the available time and the degree of its utilizati... [more]

Solar energy planning becomes crucial to develop adaptive policies ensuring both energy efficiency and climate change mitigation. Cities, particularly building’s rooftops, constitute a promising infrastructure for enabling the use of locale solar resources. This study proposes a combined engineering−statistical methodology to assess the photovoltaic potential of residential rooftops. Using validated algorithms for solar simulation and geographical information system (GIS) for spatial dissemination, the proposed methodology deals with the lack of data and allows an accurate investigation of the geographical and technical potential. Applied to the municipality of Laghouat, the results reveal that suitable rooftops areas for PV installations in the examined typologies were approximately between 18 and 35%. Moreover, the deployment of distributed PV systems on residential rooftops provides significant technical potential, which could cover up to 55% of the annual electricity needs. These o... [more]

Refrigerators play an important role in perishable goods supply chains and are expected to operate efficiently. Thermoelectric refrigerators need specific criteria for assessing their energy efficiency. The existing criteria do not take into account the insulation properties of a refrigerator cabinet, which results in a low credibility of the assessment of energy parameters of thermoelectric coolers. The aim of the research was to develop and approve a new universal criterion for assessing the energy efficiency of stationary thermoelectric refrigerators used in supply chains. It was proposed to replace the known criterion of specific power consumption with a new indicator Pk, that takes into account the overall thermal transfer coefficient of the refrigerator cabinet. Based on experimental studies, the approval of the proposed indicator was carried out on the example of a comparative analysis of four thermoelectric refrigerators from different manufacturers. The indicator application r... [more]

This paper presents an optimal scheduling solution for building thermal loads that simultaneously participate in the wholesale energy and frequency regulation markets. The solution combines (1) a lower-level regulation capacity reset strategy that identifies the available regulation capacity for each hour, and (2) an upper-level zone temperature scheduling algorithm to find the optimal load trajectory with a minimum net electricity cost. In the supervisory scheduling strategy, piece-wise linear approximations of representative air-conditioning equipment behaviors, derived from an offline analysis of the capacity reset mechanism, are used to predict the cooling power and regulation capacity; and a mixed-integer convex program is formulated and solved to determine the optimal control actions. In order to evaluate the performance of the developed control solution, two baseline strategies are considered, one with a conventional night setup/back control and the other utilizing an optimizati... [more]

This paper presents a methodology to maximize the self-sufficiency or cost-effectiveness of grid-connected prosumers by optimizing the sizes of photovoltaic (PV) systems and electrochemical batteries. In the optimal sizing procedure, a limitation on the maximum injection in the grid can affect the energy flows, the economic effectiveness of the investments, and thus the sizing results. After the explanation of the procedure, a case study is presented, and a parametric analysis of the effect of possible injection limits is shown. The procedure is applied to size plants for an Italian domestic prosumer, whose electric load profile was measured for a year. A software program developed using the proposed methodology is also briefly presented. It is used for both research and educational purposes, both in laboratory classes and in remote lessons.

Risk management is a fundamental approach to improving critical infrastructure systems’ safety against disruptive events. This approach focuses on designing robust critical infrastructure systems (CISs) that could resist disruptive events by minimizing the possible events’ probability and consequences using preventive and protective programs. However, recent disasters like COVID-19 have shown that most CISs cannot stand against all potential disruptions. Recently there is a transition from robust design to resilience design of CISs, increasing the focus on preparedness, response, and recovery. Resilient CISs withstand most of the internal and external shocks, and if they fail, they can bounce back to the operational phase as soon as possible using minimum resources. Moreover, in resilient CISs, early warning enables managers to get timely information about the proximity and development of distributions. An understanding of the concept of resilience, its influential factors, and availab... [more]

There has been an effort for a few decades to keep energy consumption at a minimum or at least within a low-level range. This effort is more meaningful and complex by including a customer’s satisfaction variable to ensure that customers can achieve the best quality of life that could be derived from how energy is used by different devices. We use the concept of Shapley Value from cooperative game theory to solve the multi-objective optimization problem (MOO) to responsibly fulfill user’s satisfaction by maximizing satisfaction while minimizing the power consumption, with energy constrains since highly limited resources scenarios are studied. The novel method uses the concept of a quantifiable user satisfaction, along the concepts of power satisfaction (PS) and energy satisfaction (ES). The model is being validated by representing a single house (with a small PV system) that is connected to the utility grid. The main objectives are to (i) present the innovative energy satisfaction model... [more]

Energy planning increasingly revolves around the use of tools for energy system modelling and analysis with a view to generating scenarios to show implications and possibilities for decision makers. Municipalities engage in the transition to renewable energy systems through the formulation of strategies and goals at a local level despite often lacking appropriate tools and resources to conduct the needed complex analyses. Tools for energy system analyses have traditionally been designed either with the scope of national energy systems or detailed project-specific analysis in mind, leaving municipal planners in a state of flux. This study aims to identify important specifications and critical design principles for future energy system modelling tools designed for municipal planners. Through a qualitative case-oriented approach, this study investigates the planning practices of four municipalities. It is found that future tools for municipal planning purposes need to combine the need for... [more]

The Daily Operation Scheduling (DOS) gets new challenges while a large-scale of renewable energy is inserted into the power system. In addition to the operation, the power variability of these sources also causes a problem in the hourly pricing, represented here by Locational Marginal Pricing (LMP). Therefore, new applications, such as energy shifting, offer greater efficiency to the system, minimizing the negative effects caused by wind power curtailment (WPC). This paper shows the LMP formation in the DOS of the hydro-thermal-wind-photovoltaic power system with a battery energy storage system and the reduction of WPC. Here, the wind and photovoltaic power plants are designed to be dispatched, not mandatory, to be able to cut the generation, and the insertion of Distributed Generation is considered. Moreover, to solve the DOS problem, the interior-point method is used. Additionally, the DC optimal power flow, used to represent the DOS in addition to the representation of the electric... [more]

Designing district-scale energy systems with renewable energy sources is still a challenge, as it involves modeling of multiple loads and many options to combine energy system components. In the current study, two different energy system scenarios for a district in Montreal/Canada are compared to choose the most cost-effective and energy-efficient energy system scenario for the studied area. In the first scenario, a decentral energy system comprised of ground-source heat pumps provides heating and cooling for each building, while, in the second scenario, a district heating and cooling system with a central heat pump is designed. Firstly, heating and cooling demand are calculated in a completely automated process using an Automatic Urban Building Energy Modeling System approach (AUBEM). Then, the Integrated Simulation Environment Language (INSEL) is used to prepare a model for the energy system. The proposed model provides heat pump capacity and the number of required heat pumps (HP), t... [more]

This paper proposes a flexible framework for scheduling and real time operation of electric vehicle charging stations (EVCS). The methodology applies a multi-objective evolutionary particle swarm optimization algorithm (EPSO) for electric vehicles (EVs) scheduling based on a day-ahead scenario. Then, real time operation is managed based on a rule-based (RB) approach. Two types of consumer were considered: EV owners with a day-ahead request for charging (scheduled consumers, SCh) and non-scheduling users (NSCh). EPSO has two main objectives: cost reduction and reduce overloading for high demand in grid. The EVCS has support by photovoltaic generation (PV), battery energy storage systems (BESS), and the distribution grid. The method allows the selection between three types of charging, distributing it according to EV demand. The model estimates SC remaining state of charge (SoC) for arriving to EVCS and then adjusts the actual difference by the RB. The results showed a profit for EVCS by... [more]

We integrate life cycle indicators for various technologies of an energy system model with high spatiotemporal detail and a focus on Europe and North Africa. Using multi-objective optimization, we calculate a pareto front that allows us to assess the trade-offs between system costs and life cycle greenhouse gas (GHG) emissions of future power systems. Furthermore, we perform environmental ex-post assessments of selected solutions using a broad set of life cycle impact categories. In a system with the least life cycle GHG emissions, the costs would increase by ~63%, thereby reducing life cycle GHG emissions by ~82% compared to the cost-optimal solution. Power systems mitigating a substantial part of life cycle GHG emissions with small increases in system costs show a trend towards a deployment of wind onshore, electricity grid and a decline in photovoltaic plants and Li-ion storage. Further reductions are achieved by the deployment of concentrated solar power, wind offshore and nuclear... [more]

In light of global warming and the energy turn, sector coupling has gained increasing interest in recent years, from both the scientific community and politics. In the following article it is hypothesized that efficient multifaceted sector coupling solutions depend on detailed spatial and temporal characteristics of energy demand and supply. Hence, spatiotemporal modelling is used as a methodology of integrated spatial and energy planning, in order to determine favourable sector coupling strategies at the local level. A case study evaluation was carried out for both central and decentral renewable energy sources. Considering the high temporal resolutions of energy demand and supply, the results revealed a feasible operation of a district heating network in the central areas of the case study municipalities. Additionally, building integrated solar energy technologies are capable of providing large amount of excess energy that could serve other demand sectors, such as the mobility sector... [more]

Environmental sustainability, defined as the responsibility to protect the global ecosystem in a holistic way, has become an integral factor of city strategies. Designing and implementing environment-friendly solutions to make the standard of living in cities better is indispensable for present and future generations. This article’s main objective is to identify the most environmentally friendly urban logistics measures from the perspective of urban transport system stakeholders. A multi-method approach was implemented to achieve the article’s main findings. Firstly, the literature review provided the basics for designing the research framework. Then, a three-layer methodological approach was used: The first layer included designing and carrying out the case study approach; the second layer comprised a Delphi study involving interviews with urban logistics stakeholders; and the third layer included analyzing the voices of Delphi interviewees to assess which urban logistics measures are... [more]

Due to increasing numbers of intermittent and distributed generators in power systems, there is an increasing need for demand responses to maintain the balance between electricity generation and use at all times. For example, the electrification of transportation significantly adds to the amount of flexible electricity demand. Several methods have been developed to schedule such flexible energy consumption. However, an objective way of comparing these methods is lacking, especially when decisions are made based on incomplete information which is repeatedly updated. This paper presents a new benchmarking framework designed to bridge this gap. Surveys that classify flexibility planning algorithms were an input to define this benchmarking standard. The benchmarking framework can be used for different objectives and under diverse conditions faced by electricity production stakeholders interested in flexibility scheduling algorithms. Our contribution was implemented in a software toolbox pr... [more]