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]

With recent technology advances and price drop, battery energy storage systems (BESSs) are considered as a promising storage technology in power systems. In this paper, a stochastic BESS planning model is introduced, which determines optimal capacity and durations of BESSs to co-locate utility-scale solar photovoltaic (PV) systems in a high-voltage power system under the uncertainties of renewable resources and electric load. The optimization model minimizing total costs aims to obtain at least 20% electric energy from renewable sources, while satisfying all the physical constraints. Furthermore, two-stage stochastic programming is applied to formulate mathematical optimization problem to find out optimal durations and capacity of BESSs. In scheduling BESSs, chronology needs to be considered to represent temporal changes of BESS states; therefore, a scenario generation method to generate random sample paths with 1-h time step is adopted to explicitly represent uncertainty and temporal... [more]

With the transition towards renewable energy resources, the impact of small distributed generators (DGs) increases, leading to the need to actively stabilize distribution grids. DGs may be organized in virtual power plants (VPPs), where DGs’ schedules must be coordinated to enable the VPP to act as a single plant. One approach to solving this problem is using multi-agent systems (MAS) to offer autonomous, robust, and flexible control methods. The coordination of such systems requires communication between agents. The time required for this depends on communication characteristics, determined by the underlying communication infrastructure. In this paper, we investigate communication influences for the wireless technologies CDMA450 and LTE Advanced on the fully distributed optimization heuristic COHDA, which is used to perform optimized scheduling for a VPP. The use case under consideration is the adaptation of schedules to provide flexibility for regional congestion management for deliv... [more]

The optimal reactive power dispatch (ORPD) problem represents a fundamental concern in the efficient and reliable operation of power systems, based on the proper coordination of numerous devices. Therefore, the ORPD calculation is an elaborate nonlinear optimization problem that requires highly performing computational algorithms to identify the optimal solution. In this paper, the potential of metaheuristic methods is explored for solving complex optimization problems specific to power systems. In this regard, an improved salp swarm algorithm is proposed to solve the ORPD problem for the IEEE-14 and IEEE-30 bus systems, by approaching the reactive power planning as both a single- and a multi- objective problem and aiming at minimizing the real power losses and the bus voltage deviations. Multiple comparison studies are conducted based on the obtained results to assess the proposed approach performance with respect to other state-of-the-art techniques. In all cases, the results demonst... [more]

Ethiopia is a low-income country, with low electricity access (45%) and an inefficient power transmission network. The government aims to achieve universal access and become an electricity exporter in the region by 2025. This study provides an invaluable perspective on different aspects of Ethiopia’s energy transition, focusing on achieving universal access and covering the country’s electricity needs during 2015−2065. We co-developed and investigated three scenarios to examine the policy and technology levels available to the government to meet their national priorities. To conduct this analysis, we soft-linked OnSSET, a modelling tool used for geospatial analysis, with OSeMOSYS, a cost-optimization modelling tool used for medium to long-run energy planning. Our results show that the country needs to diversify its power generation system to achieve universal access and cover its future electricity needs by increasing its overall carbon dioxide emissions and fully exploit hydropower. W... [more]

The FlexPlan Horizon2020 project aims at establishing a new grid-planning methodology which considers the opportunity to introduce new storage and flexibility resources in electricity transmission and distribution grids as an alternative to building new grid elements, in accordance with the intentions of the Clean Energy for all Europeans regulatory package of the European Commission. FlexPlan creates a new innovative grid-planning tool whose ambition is to go beyond the state of the art of planning methodologies by including the following innovative features: assessment of the best planning strategy by analysing in one shot a high number of candidate expansion options provided by a pre-processor tool, simultaneous mid- and long-term planning assessment over three grid years (2030, 2040, 2050), incorporation of a full range of cost−benefit analysis criteria into the target function, integrated transmission distribution planning, embedded environmental analysis (air quality, carbon foot... [more]

The purpose of the study is to assess the efficiency of cash flow management at power supply companies of the CIS (Commonwealth of Independent States) countries. A methodological approach to cash flow forecasting with the use of linear and polynomial regression has been developed. The study is based on the data provided by 12 power supply companies operating in CIS member countries. Forecasting based on the generated polynomial models of multiple regression of cash flow for the power supply companies under study confirms the strong possibility of extrapolating the studied trends to future periods. Compared to the linear model, the polynomial one confirms higher values of the determination coefficients for the majority of power supply companies. The projected volumes of cash inflow, cash outflow, and net cash flows of power supply companies with the application of the described polynomial multiple regression models have a fairly high degree of approximation. The correlations between ope... [more]

With increasing deployment of offshore wind farms further from shore and in deeper waters, the efficient and effective planning of operation and maintenance (O&M) activities has received considerable attention from wind energy developers and operators in recent years. The O&M planning of offshore wind farms is a complicated task, as it depends on many factors such as asset degradation rates, availability of resources required to perform maintenance tasks (e.g., transport vessels, service crew, spare parts, and special tools) as well as the uncertainties associated with weather and climate variability. A brief review of the literature shows that a lot of research has been conducted on optimizing the O&M schedules for fixed-bottom offshore wind turbines; however, the literature for O&M planning of floating wind farms is too limited. This paper presents a stochastic Petri network (SPN) model for O&M planning of floating offshore wind turbines (FOWTs) and their support structure components... [more]

Municipalities are increasingly involved in energy transition planning. There are, however, doubts about whether municipalities are an adequate organization and scale level for this. In this context, the article aims to picture developments of local young technology firms in bringing energy inventions to market, in particular, how municipalities have provided support to them. Such aim, in the context of energy transition, is new. Derived from study in Nordic countries and The Netherlands, two findings make a valuable contribution to literature. Firstly, a share of almost 40% of young technology firms fails in market introduction, and if reached the market, a 30% is rather late. Barriers stem from high risk-taking, late (no) collaboration, and limiting circumstances in metropolitan cities. Secondly, municipalities’ initiatives appear useful in filling young technology firms’ needs, but the initiatives are fragmented and miss priority. However, partnering in professional start-up organiz... [more]

A competent methodology based on the active power loss reduction for optimal placement and sizing of distributed generators (DGs) in an active distribution network (ADN) with several soft open points (SOPs) is proposed. A series of SOP combinations are explored to generate different network structures and they are utilized in the optimization framework to identify the possible solutions with minimum power loss under normal network conditions. Furthermore, a generalized methodology to optimize the size and the location of a predefined number of DGs with a predefined number of SOPs is presented. A case study on the modified IEEE 33 bus system with three DGs and five SOPs was conducted and hence the overall network power loss and the voltage improvement were examined. The findings reveal that the system loss of the passive network without SOPs and DGs is reduced by 79.5% using three DGs and five SOPs. In addition, this research work introduces a framework using the DG size and the impedan... [more]

The current energy transition and the underlying growth in variable and uncertain renewable-based energy generation challenge the proper operation of power systems. Classical probabilistic uncertainty models, e.g., stochastic programming or robust optimisation, have been used widely to solve problems such as the day-ahead energy and reserve dispatch problem to enhance the day-ahead decisions with a probabilistic insight of renewable energy generation in real-time. By doing so, the scheduling of the power system becomes, production and consumption of electric power, more reliable (i.e., more robust because of potential deviations) while minimising the social costs given potential balancing actions. Nevertheless, these classical models are not valid when the uncertainty is imprecise, meaning that the system operator may not rely on a unique distribution function to describe the uncertainty. Given the Distributionally Robust Optimisation method, our approach can be implemented for any non... [more]

This paper proposes an Exponentially Varying Whale Optimization Algorithm (EVWOA) to solve the single-objective non-convex Cogeneration Units problem. This problem seeks to evaluate the optimal output of the generator unit to minimize a CHP system’s fuel costs. The nonlinear and non-convex characteristics of the objective function demands a powerful optimization technique. The traditional Whale Optimization Algorithm (WOA) is improved by incorporating four different acceleration functions to fine-tune its performance during exploration and exploitation phases. Among the four variants of the proposed WOA, the emphasis is laid on the EVWOA which uses the exponentially varying acceleration function (EVAF). The proposed EVWOA is tested on six different small-scale to large-scale systems. The results obtained for these six test systems, followed by a statistical study highlight the supremacy of EVWOA for finding the best optimal solution and the convergence traits.

In this paper, we apply the Failure Modes, Effects, and Criticality Analysis (FMECA) approach to the criticality and risk analysis of the efficiency, safety/reliability, environment, and financial criteria of the high voltage transmission line. In the efficiency analysis, the weighting-scoring method and analytical hierarchy process are applied to obtain the line renovation index, which is interpreted as efficiency severity. The safety/reliability severity relates to the system impacts are caused by failure of the equipment and the system. The environmental severity takes social impacts and pollution into consideration. The financial severity involves the cost of spare parts and maintenance costs, which are interpreted as the financial severity of the lines. Twenty practical transmission lines in Thailand with actual data for 115, 230, and 500 kV were studied. The transmission line components are divided into eight components including the conductor, conductor accessories, insulator, s... [more]

This century registers a significant expansion in the wind power market. However, the vast majority of these investments are concentrated in large wind turbines. The century begins with an installed capacity of about 20 GW, which reaches 650 GW in 2019. On the other hand, it is important to highlight that small wind turbines have not followed this virtuous path, a fact that is evident in Brazil’s reality. In this context, the article aims at evaluating the current situation of the wind energy market for Small Wind Turbines in Brazil (SWT) and its future perspectives, identifying the main characteristics of the sector, its challenges, and opportunities. It is an exploratory−explanatory research study that investigates the theme, generating knowledge that turns to practical application, as it seeks answers to solve local interests. This methodological approach provides objective evidence that the production of knowledge about the use of SWT in Brazil still remains embryonic, shaded by th... [more]

With a rapid increase in the awareness of carbon reduction worldwide, the industry of electric vehicles (EVs) has started to flourish. However, the large number of EVs connected to a power grid with a large power demand and uncertainty may result in significant challenges for a power system. In this study, the optimal charging and discharging scheduling strategies of G2V/V2G and battery energy storage system (BESS) were proposed for EV charging stations. A distributed computation architecture was employed to streamline the complexity of an optimization problem. By considering EV charging/discharging conversion efficiencies for different load conditions, the proposed method was used to maximize the operational profits of each EV and BESS based on the related electricity tariff and demand response programs. Moreover, the behavior model of drivers and cost of BESS degradation caused by charging and discharging cycles were considered to improve the overall practical applicability. An EV ch... [more]

In recent years, there has been dynamic changes in the industrial environment as a result of further innovations called Industry 4.0 (I.4.0), especially in the field of digital technology and manufacturing. Despite numerous examples of the implementation of Industry 4.0 in enterprises, there is no general framework for the implementation of Industry 4.0 with a detailed schedule. Researching the ways of implementing Industry 4.0 is still a current and unexplored area of research. The main aim of the paper is to present the concept of the theoretical framework for Industry 4.0 implementation based on selected schedules of the Industry 4.0 implementation. The paper was based on information from literature review and analysis of pilot enterprise projects to Industry 4.0 (case study) that were conducted in selected enterprises. The paper presents the key components of the framework of Industry 4.0 and the basic stage of implementing the concept in the enterprises, paying attention to their... [more]

An integrated energy system (IES) shows great potential in reducing the terminal energy supply cost and improving energy efficiency, but the operation scheduling of an IES, especially integrated with inter-connected multiple energy stations, is rather complex since it is affected by various factors. Toward a comprehensive operation scheduling of multiple energy stations, in this paper, a day-ahead and intra-day collaborative operation model is proposed. The targeted IES consists of electricity, gas, and thermal systems. First, the energy flow and equipment composition of the IES are analyzed, and a detailed operation model of combined equipment and networks is established. Then, with the objective of minimizing the total expected operation cost, a robust optimization of day-ahead and intra-day scheduling for energy stations is constructed subject to equipment operation constraints, network constraints, and so on. The day-ahead operation provides start-up and shut-down scheduling of uni... [more]

Owing to stricter building energy requirements, future buildings will be characterized by low base loads and occasional high peaks. However, future building areas will still contain existing and historical buildings with high energy demand. Meanwhile, there is a requirement that future building areas should obtain energy from renewable energy sources, while existing buildings need to be transited to renewables. Therefore, the aim of this study was to develop an approach for modelling energy pathways for future Norwegian residential building areas by analyzing different energy supply systems. Several calculation methods were combined: building simulation, energy supply technology simulation, heat demand aggregation, and data post-processing. The results showed that the energy pathways would be very dependent on CO2-factors for energy sources, and it is hard to predict accurate CO2-factors. An increasing housing stock development would slightly increase the CO2 emissions towards 2050, al... [more]

Peak-shaving is a very efficient and practical strategy for a day-ahead hydropower scheduling in power systems, usually aiming to appropriately schedule hourly (or in less time interval) power generations of individual plants so as to smooth the load curve while enforcing the energy production target of each plant. Nowadays, the power marketization and booming development of renewable energy resources are complicating the constraints and diversifying the objectives, bringing challenges for the peak-shaving method to be more flexible and efficient. Without a pre-set or fixed peak-shaving order of plants, this paper formulates a new peak-shaving model based on the mixed integer linear programming (MILP) to solve the scheduling problem in an optimization way. Compared with the traditional peak-shaving methods that need to determine the order of plants to peak-shave the load curve one by one, the present model has better flexibility as it can handle the plant-based operating zones and prio... [more]

The study presents a methodology for floating wind farms site selection with a Canary Islands case study. The frame combines geographical information systems (GIS) and multiple criteria decision methods (MCDMs). First, the problematic areas for the installation of the turbines are identified through a GIS database application. This tool generates thematic layers representing exclusion criteria. Then, at the second stage of the study, available maritime locations are analyzed and ranked using the analytical hierarchy process (AHP), based on technical, economic, and environmental aspects. AHP’s technique guarantee the elimination of the judgment’s subjectivity. The study also compared the solutions of the AHP technique with other methods, such as Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE), ELimination Et Choix Traduisant la Realité (ELECTRE III), Technique for Order Preferences by Similarity to Ideal Solution (TOPSIS) and Weighted Sum Algorithm (WSA(... [more]

Stirling units are a viable option for micro-cogeneration applications, but they operate often with multiple daily startups and shutdowns due to the variability of load profiles. This work focused on the experimental and numerical study of a small-size commercial Stirling unit when subjected to cycling operations. First, experimental data about energy flows and emissions were collected during on−off operations. Second, these data were utilized to tune an in-house code for the economic optimization of cogeneration plant scheduling. Lastly, the tuned code was applied to a case study of a residential flat in Northern Italy during a typical winter day to investigate the optimal scheduling of the Stirling unit equipped with a thermal storage tank of diverse sizes. Experimentally, the Stirling unit showed an integrated electric efficiency of 8.9% (8.0%) and thermal efficiency of 91.0% (82.2%), referred to as the fuel lower and, between parenthesis, higher heating value during the on−off cycl... [more]