In recent years electricity sectors worldwide have undergone major transformations, referred to as the “energy transition”. This has required energy planning to quickly adapt to provide useful inputs to the regulation activity so that a cost-effective electricity market emerges to facilitate the integration of renewables. This paper analyzes the role of system planning and regulations on two specific elements in the energy market design: the concept of firm capacity and the presence of distributed energy resources, both of which can be influenced by regulation. We assess the total cost of different regulatory mechanisms in the Brazilian and Mexican systems using optimization tools to determine optimal long-term expansion for a given regulatory framework. In particular, we quantitatively analyze the role of the current regulation in the total cost of these two electricity systems when compared to a reference “efficient” energy planning scenario that adopts standard cost-minimization pri... [more]

Universal access to electricity is a crucial challenge in many developing countries. Establishing the electrification agenda of an underserved region is a complicated task where computer models play a critical role in calculating geospatial plans that efficiently allocate resources. Such plans should include—among other things—reasonable estimations of the designs and economic costs of standalone systems, mini-grids, and grid extensions. This implies that computer models need to estimate the network cost for many potential mini-grids. To that end, most planning tools apply quick rules of thumb or geometric methods that ignore power flows and electric constraints, which play a significant role in network designs. This paper presents a methodology that rapidly estimates any low-voltage mini-grid network cost without neglecting the impact of electrical feasibility in such cost. We present a case study where we evaluate our method in terms of accuracy and computation time. We also compare... [more]

This paper develops the coordination structure and method for utilizing flexibilities in a Micro-Grid (MG), an Active Distribution Network (ADN) and a Transmission Grid (TG), which can play an essential role in addressing the uncertainties caused by renewable energy power generation (REPG). For cooperative dispatching, both flexibilities and uncertainties on the interface of MG−ADN and ADN−TG are portrayed in unified forms utilizing robust optimization (RO), based on the modified equipment-level model of flexible resources. The Constraint-and-Column Generation method is adopted to solve the RO control problems. Simulations on the modified IEEE case-6 and case-33 systems are carried out. The results suggest that the proposed algorithm can exploit flexible resources in both an MG and an ADN, improving the economy and promoting REPG consumption within each level (MG, ADN and TG) while reducing uncertainties and providing flexibilities for superior operators.

Due to the rapid changes in the energy situation on a global scale, the amount of RES installed using clean renewable energy sources such as Photovoltaic (PV) and Wind-power Generators (WGs) is rapidly increasing. As a result, there has been a great deal of research aimed at promoting the adoption of renewable energy. Research on Demand-side Management (DSM) has also been important in promoting the adoption of RES. However, the massive introduction of PV has changed the shape of the demand curve for electricity, which significantly impacts the operational planning of thermal generators. Therefore, this paper proposes an Advanced Direct Load Control (ADLC) model to temporarily shutdown the electric connection between the power grid and Smart Houses (SHs). The most important feature of the proposed model is that it temporarily shuts down the electric connection with the power grid. The shutdown is performed twice to increase the load demand during daytime hours and reduce the peak load d... [more]

The main challenge with the penetration of variable renewable energy (VRE) in thermal-dominated systems has been the increase in the need for operating reserves, relying on dispatchable and flexible resources. In the case of hydro-dominated systems, the cost-effective flexibility provided by hydro-plants facilitates the penetration of VRE, but the compounded production variability of these resources challenges the integration of baseload gas-fired plants. The Brazilian power system illustrates this situation, in which the development of large associated gas fields economically depends on the operation of gas-fired plants. Given the current competitiveness of VRE, a natural question is the economic value and tradeoffs for expanding the system opting between baseload gas-fired generation and VRE in an already flexible hydropower system. This paper presents a methodology based on a multi-stage and stochastic capacity expansion model to estimate the optimal mix of baseload thermal power pl... [more]

In the European Green Deal, EU Commission has set a goal to reduce greenhouse gas emissions in the transport sector by 90% by 2050 compared to the 1990 level. Most likely, transport decarbonization will rely on a rapid expansion of electric and hydrogen vehicle fleet, which would seriously affect not just overall electricity demand, but also the shape of the electricity consumption curve. Consequently, our research focuses on integrated energy and transport modelling when analyzing its development pathways up to 2050 and beyond. This paper describes how already established transport modeling practices can be further improved by differentiating vehicles by age groups and setting vehicle age distributions to improve the representation of vehicle stock, fuel efficiencies and emissions, especially for countries that have non-declining vehicle age distributions. Modeling results using proposed and traditional approaches were compared for the Lithuanian case. It shows that the transport fuel... [more]

Assessment of gendered energy transition at an urban scale has emerged as a challenging issue for researchers, policy makers and practitioners. With municipalities becoming players in the energy markets, their involvement raises policy issues that need to be better assessed in supporting gendered energy transition. This paper, therefore, contributes to gendered energy transition assessments at urban household level from a policy maker perspective. We developed a system dynamics model to assess the effects of urban energy policy interventions on household energy consumption and gendered measures using Drakenstein Municipality as a case study. The study used secondary data from various sources for the model parameters. We tested three hypothetical policy scenarios: the business-as-usual, the energy subsidy policy and the energy efficiency policy. The results show that understanding the changes in urban household energy consumption and gendered measures due to energy transition interventi... [more]

Natural dimension stone processing generates large volumes of stone waste, which have a significant impact on the environment, as well as on the efficiency and profitability of the stone-processing plant. The article presents the characteristics of waste produced as a result of natural dimension stone processing and the structure of the waste production process. Solid stone scraps and sludge were distinguished. On the basis of the performed analyses, it was shown that stone waste constitutes 10−35% in relation to the quantity of the processed stone material, with the quantity of sludge being even threefold greater than the volume of solid scraps. According to the circular economy principles, the aim should be to reduce the amount of waste generated by reducing primary resources in favour of secondary material. Reducing the volume of stone waste is possible through rational planning of stone production while at the same time maximising the efficiency of stone material usage and introduc... [more]

The power system responsiveness may be improved by determining the ideal size of each component and performing a reliability analysis. This study evaluated the design and optimization of an islanded hybrid microgrid system with multiple dispatch algorithms. As the penetration of renewable power increases in microgrids, the importance and influence of efficient design and operation of islanded hybrid microgrids grow. The Kangaroo Island in South Australia served as the study’s test microgrid. The sizing of the Kangaroo Island hybrid microgrid system, which includes solar PV, wind, a diesel engine, and battery storage, was adjusted for four dispatch schemes. In this study, the following dispatch strategies were used: (i) load following, (ii) cycle charging, (iii) generator order, and (iv) combination dispatch. The CO2 emissions, net present cost (NPC), and energy cost of the islanded microgrid were all optimized (COE). The HOMER microgrid software platform was used to build all four disp... [more]

The operation of on-site power plants in the chemical industry is typically determined by the steam demand of the production plants. This demand is uncertain due to deviations from the production plan and fluctuations in the operation of the plants. The steam demand uncertainty can result in an inefficient operation of the power plant due to a surplus or deficiency of steam that is needed to balance the steam network. In this contribution, it is proposed to use two-stage stochastic programming on a moving horizon to cope with the uncertainty. In each iteration of the moving horizon scheme, the model parameters are updated according to the new information acquired from the plants and the optimisation is re-executed. Hedging against steam demand uncertainty results in a reduction of the fuel consumption and a more economic generation of electric power, which can result in significant savings in the operating cost of the power plant. Moreover, unplanned load reductions due to lack of stea... [more]

The tunneling work belongs to the group operation of semi-closed space, and the work is difficult with a high risk coefficient. It is an urgent requirement of coal mining to achieve unmanned and intelligent tunneling work. The path rectification planning of roadheaders is a necessary step before roadway cutting. In the traditional dynamic modeling analysis of roadhead tracks, problems such as compaction resistance, bulldozing resistance, steering resistance, tunnel dip angle, ditching, and obstacle-crossing capacity are not considered. In order to approximate the kinematic and dynamic parameters of a roadheader’s deviation correction under actual working conditions, this paper establishes kinematic and dynamic models of a roadheader’s path rectification at low speeds and under complex working conditions, and calculates the obstacle-crossing ability of roadheaders in the course of path rectification by modes based on roadway conditions, crawler resistance, and driving performance of the... [more]

So far, little is known about the Business Model Canvas development in the energy sector. In this paper, we fill this knowledge gap and modify the Business Model Canvas. Based on the cause−effect analysis combined with the literature searching method, we suggest that Osterwalder’s Canvas for energy enterprise should be modified because the available Canvas adaptations cannot fully capture the energy enterprise’s business model or realise its business operations combined with the public interest. We propose a new original Canvas adaptation by adding two crucial blocks representing the mission, energy accountability, and impact on stakeholders in the Business Model Canvas. The findings make two main contributions. First, they contribute to developing entrepreneurship theory. We formulate an original definition of a business model, first showing the limitations of current definitions. We verify Chesbrough’s functions of business models. Second, compared to earlier business model framework... [more]

Fuel cell electric vehicles (FCEV) are emerging as one of the prominent zero emission vehicle technologies. This study follows a deterministic modeling approach to project two scenarios of FCEV adoption and the resulting hydrogen demand (low and high) up to 2050 in California, using a transportation transition model. The study then estimates the number of hydrogen production and refueling facilities required to meet demand. The impact of system scale-up and learning rates on hydrogen price is evaluated using standalone supply chain models: H2A, HDSAM, HRSAM and HDRSAM. A sensitivity analysis explores key factors that affect hydrogen prices. In the high scenario, light and heavy-duty fuel cell vehicle stocks reach 12.5 million and 1 million by 2050, respectively. The resulting annual hydrogen demand is 3.9 billion kg, making hydrogen the dominant transportation fuel. Satisfying such high future demands will require rapid increases in infrastructure investments starting now, but especial... [more]

The uncertainty associated with loads and renewable-energy sources affects active distribution networks in terms of the operation and voltage stability on different time scales. To address this problem, a multi-time-scale voltage stability constrained optimal scheduling framework is proposed, which includes a day-ahead model with a coarse-grained time resolution and an intra-day model with a fine-grained time resolution. The day-ahead economic-scheduling model maps out a scheme to operate different types of devices with the aim of minimizing the network losses. Following the scheme, the intra-day corrective-adjustment model based on model predictive control is proposed to regulate the flexible devices, such as the energy storage systems and the photovoltaic converters. In particular, the proposed optimal scheduling framework embeds a voltage stability constraint which is constructed by using a novel index, defined based on the Distflow model Jacobian. As the index at each bus is a line... [more]

The unevenness of the electricity consumption schedule at enterprises leads to a peak power increase, which leads to an increase in the cost of electricity supply. Energy storage devices can optimize the energy schedule by compensating the planned schedule deviations, as well as reducing consumption from the external network when participating in a demand response. However, during the day, there may be several peaks in consumption, which lead to a complete discharge of the battery to one of the peaks; as a result, total peak power consumption does not decrease. To optimize the operation of storage devices, a day-ahead forecast is often used, which allows to determine the total number of peaks. However, the power of the storage system may not be sufficient for optimal peak compensation. In this study, a long-term forecast of power consumption based on the use of exogenous parameters in the decision tree model is used. Based on the forecast, a novel algorithm for determining the optimal... [more]

Inland navigation is hardly ever used to transport cargo in cities. In most urban areas, it is performed almost exclusively via road transport, with the virtual exclusion of rail and inland transport. Research and implementation projects in several European cities have shown that employing inland navigation is a viable alternative for road transport in urban areas. The research involved a case study of transporting the same number of 40-foot containers by inland waterway and road and then comparing the results in terms of transport time, transport costs, and carbon dioxide emissions between two metropolitan areas in Poland. The article shows that River Information Services (RIS) system can contribute to improving freight transport efficiency not only on longer routes, but also in urban and inter-urban conditions. The findings were that inland shipping is much cheaper and more environmentally friendly, but transport takes much longer and is not always possible due to insufficient waterw... [more]

Apart from numerous technical challenges, the transition towards a carbon-neutral energy supply is greatly hindered by limited economic feasibility of renewable energy sources. This results in their slow and bounded penetration in both commercial and residential sectors that are responsible for over 40% of final energy consumption. This paper aims to demonstrate that combined application of sophisticated planning methodologies at building-level and presents incentive mechanisms for renewables that can result in prosumers, featuring hybrid renewable energy systems (HRES), with economic performance comparable to that of conventional energy systems. The presented research enhances existing planning methodologies by integrating appliance-level demand side management into the decision process and investigates its effect on the planning problem. Moreover, the proposed methodology features an innovative and holistic approach that simultaneously assess electrical and thermal domain in both an... [more]

The aim of the study is to explore the intellectual structure of the field and fronts in research on energy efficiency in the context of cloud computing and thus to contribute to science mapping of the research field. The research process was driven by the following study questions: (1) what are the most influential publications in the research field? and (2) what are the research fronts in the research field? The method of direct citation analysis was employed in the research process. Data for analysis were obtained from the Scopus database and analyzed with the use of VOSviewer science mapping software. In response to the first question, we identified the most influential publications in the research field and analyzed their types (i.e., whether they are original research papers or rather the “context” papers e.g., survey or review papers, framework papers, challenges papers, and study papers). Moreover, a comparison analysis between the types of papers among the most cited “classica... [more]

With the global net-zero strategy implementation, decarbonisation of transport by massive deployment of electric vehicles (EVs) has been considered to be an essential solution. However, charging EVs and integration into electricity grids is going to be a fundamental challenge to future electricity systems. Hence, in this situation, how to effectively deploy massive numbers of EVs, and in the meantime what can be developed to deliver vehicle-to-grid (V2G) services, become a fundamental yet interesting tech-economical issues. Furthermore, uncertainty in lack of vehicle availability and EV battery degradation could lead to revenue loss when using EVs as ancillary services aggregators. With such considerations, this paper presents a new optimised V2G aggregator scheduling service that has taken into consideration of a number of risks, including EV availability and battery degradation through conditional value-at-risk. The proposed method for V2G scheduling service, as an independent aggreg... [more]

According to South Africa’s national energy policy, network penetration of variable renewable energy (VRE) generation will significantly increase by 2030. Increased associated network uncertainty creates the need for an additional flexible generation. As the planned VRE is mostly non-synchronous PV and wind generators, additional ancillary services will also be required. Pumped Storage (PS), which is a well-established flexible generation technology with fast ramping capability and the ability to contribute various ancillary services, could help integrate increased VRE penetration on the South African network. However, in the latest revision of South Africa’s energy policy, PS was left out in favor of gas turbines and batteries as favored flexible generation options. This paper explores the two-part hypothesis that PS was disadvantaged in the formulation of a national energy mix due to: (a) ancillary services provided by PS not being explicitly monetized in energy modeling software; (b... [more]

Non-cooperative scheduling games can be used to coordinate residential loads in order to achieve a common goal while accounting for individual consumer’s interests, privacy, and autonomy. However, a significant portion of the residential flexibility—Thermostatically Controlled Loads (TCLs) such as water and space heating/cooling appliances—has not been fully addressed under this game theoretic approach: their comfort constraints and integer control were not considered. This paper presents a method for properly including TCLs in this framework and discusses its application in energy communities. Specifically, we propose a general mathematical formulation for considering users’ comfort in non-cooperative games. We model the integer nature of the TCLs control with binary variables and show that optimal or close to optimal (less than 1%) solutions are reached. Moreover, different total cost functions can be used depending on the market context and the objective of the demand management pro... [more]

Hydrogen and its energy carriers, such as liquid hydrogen (LH2), methylcyclohexane (MCH), and ammonia (NH3), are essential components of low-carbon energy systems. To utilize hydrogen energy, the complete environmental merits of its supply chain should be evaluated. To understand the expected environmental benefit under the uncertainty of hydrogen technology development, we conducted life-cycle inventory analysis and calculated CO2 emissions and their uncertainties attributed to the entire supply chain of hydrogen and NH3 power generation (co-firing and mono-firing) in Japan. Hydrogen was assumed to be produced from overseas renewable energy sources with LH2/MCH as the carrier, and NH3 from natural gas or renewable energy sources. The Japanese life-cycle inventory database was used to calculate emissions. Monte Carlo simulations were performed to evaluate emission uncertainty and mitigation factors using hydrogen energy. For LH2, CO2 emission uncertainty during hydrogen liquefaction ca... [more]

The definition of multiple slicing types in 5G has created a wide field for service innovation in communications. However, the advantages that network slicing has to offer remain to be fully exploited by today’s applications and users. An important area that can potentially benefit from 5G slicing is emergency communications for First Responders. The latter consists of heterogeneous teams, imposing different requirements on the connectivity network. In this paper, the RESPOND-A platform is presented, which provides First Responders with network-enabled tools on top of 5G on-scene planning, with enhanced service slicing capabilities tailored to emergency communications. Furthermore, a mapping of emergency services and communications to specific slice types is proposed to identify the current challenges in the field. Additionally, the proposed tentative mechanism is evaluated in terms of energy efficiency. Finally, the approach is summarized by discussing future steps in the convergence... [more]

Considerable investment in India’s electricity system may be required in the coming decades in order to help accommodate the expected increase of renewables capacity as part of the country’s commitment to decarbonize its energy sector. In addition, electricity demand is geared to significantly increase due to the ongoing electrification of the transport sector, the growing population, and the improving economy. However, the multi-dimensional uncertainty surrounding these aspects gives rise to the prospect of stranded investments and underutilized network assets, rendering investment decision making challenging for network planners. In this work, a stochastic optimization model is applied to the transmission network in India to identify the optimal expansion strategy in the period from 2020 until 2060, considering conventional network reinforcements as well as energy storage investments. An advanced Nested Benders decomposition algorithm was used to overcome the complexity of the multis... [more]

The goal of this paper is to optimally combine day-ahead solar and demand forecasts for the optimal battery schedule of a hybrid solar and battery farm connected to a distribution station. The objective is to achieve the maximum daily peak load reduction and charge battery with maximum solar photovoltaic energy. The innovative part of the paper lies in the treatment for the errors in solar and demand forecasts to then optimize the battery scheduler. To test the effectiveness of the proposed methodology, it was applied in the data science challenge Presumed Open Data 2021. With the historical Numerical Weather Prediction (NWP) data, solar power plant generation and distribution-level demand data provided, the proposed methodology was tested for four different seasons. The evaluation metric used is the peak reduction score (defined in the paper), and our approach has improved this KPI from 82.84 to 89.83. The solution developed achieved a final place of 5th (out of 55 teams) in the chall... [more]