Security constrained unit commitment is an essential part of the day-ahead energy markets. The presence of discrete and continuous variables makes it a complex, mixed-integer, and time-hungry optimization problem. Grid operators solve unit commitment problems multiple times daily with only minor changes in the operating conditions. Solving a large-scale unit commitment problem requires considerable computational effort and a reasonable time. However, the solution time can be improved by exploiting the fact that the operating conditions do not change significantly in the day-ahead market clearing. Therefore, in this paper, a novel multi-layer data-driven approach is proposed, which significantly improves the solution time (90% time-reduction on average for the three studied systems). The proposed approach not only provides a near-optimal solution (<1% optimality gap) but also ensures that it is feasible for the stable operation of the system (0% infeasible predicted solutions). The e... [more]

The European Commission introduced a package of measures to accelerate the shift to low-carbon energy transition in Europe. In 2014, EU member states agreed to reduce greenhouse gas emissions by at least 40% by 2030 compared to 1990 levels. The binding greenhouse gas emission targets for Member States from 2021 to 2030 for the transport, buildings, agriculture, waste, and land-use and forestry sectors were established. EU Member States should decide on their own how to meet the agreed upon 2030 target and implement climate-change-mitigation measures. All EU MSs have committed to prepare national energy and climate plans based on regulation on the governance of the energy union and climate action (EU)2018/1999, agreed as part of the Clean Energy for All Europeans package approved in 2019. The national plans outline how the EU Member States intend to implement the GHG reduction target by increasing their in energy efficiency, use of renewables, greenhouse-gas-emission reductions, interco... [more]

Distributed energy systems (DES) are currently at the forefront of the energy transition. Their placement brings production closer to the demand side of urban and sub-urban environments, making optimal design a necessity. However, the complexity of accurately addressing the energy demands via DES has received increasing research attention. This is mainly due to the impact they have on the energy transition’s socioeconomic aspect, as these systems are far from viable in most cases, especially when cutting-edge renewable technologies are involved. The current study aims to provide a practical and non-repetitive approach to DES design, explicitly referring to thermal distributed supply systems (TDESS). The authors present the last two of their three-layer Hierarchically Dependent Layering Methodology (HDLM) approach in designing a thermal local energy community (TLEC) from the ground up. The 2nd layer is the superstructure design of the TLEC, where a map approach is introduced and explore... [more]

Increasing distributed generations (DGs) are integrated into the distribution network. The risk of not satisfying operation constraints caused by the uncertainty of renewable energy output is increasing. The energy storage (ES) could stabilize the fluctuation of renewable energy generation output. Therefore, it can promote the consumption of renewable energy. A distributed photovoltaic (PV) and ES optimal allocation method based on the security region is proposed. Firstly, a bi-level optimal allocation model of PV and ES is established. The outer layer is a nonlinear optimization model, taking the maximum power supply benefit as the objective function. The inner layer is a day-ahead economic dispatching model. Then, a quick model solving method based on the steady-state security region is proposed. An initial allocation scheme of PV and ES is determined with the redundancy capacity. In addition, the linear hyperplane coefficient of the security region is used to convert the nonlinear d... [more]

Multi-criteria decision analyses (MCDAs) have been developed to support and evaluate decision-making on multi-layered problems. The benefit lies in creating transparency, among other benefits, especially in tackling divergent stakeholder interests. Within the energy transition, area shortage can lead to sustainability trade-offs, calling for the reconciliation of planning processes and satisfactory compromises. While ex ante MCDAs complement planning, the ex post consideration of processes has been less widely studied. Using a case study of offshore wind energy (OWP) within German marine spatial planning, we investigated the shifting weights of sustainability criteria and stakeholder interests. A multi-criteria approach (Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE)) addressed how decision-making can be iteratively traced, and the winners and losers indicated in sustainability dilemmas, such as between climate and biodiversity implications. Findings i... [more]

The large-scale integration of variable renewable energy sources into the energy system presents techno−economic challenges. Long−term energy system optimization models fail to adequately capture these challenges because of the low temporal resolution of these tools. This limitation has often been addressed either by direct improvements within the long−term models or by coupling them to higher resolution power system models. In this study, a combined approach is proposed to capitalize on the advantages and overcome the disadvantages of both methods. First, the temporal resolution of an energy model was enhanced by approximating the joint probability of the electricity load and the supply of intermittent sources. Second, the projected electricity mix was simulated by a power model at an hourly resolution. This framework was used to analyze mid−century deep decarbonization trajectories for Colombia, subject to future uncertainties of hydroclimatic variability and the development of the b... [more]

There are two situations of transmission redundancy and transmission congestion when large-scale offshore wind farms send power out. The energy storage system can store the power blocked by wind power due to insufficient transmission capacity and release it in the period when the wind power output level is low. In this paper, a full-life-cycle cost model is established for energy storage, and a joint planning model for offshore wind power storage and transmission considering carbon emission reduction benefits is established, which integrates power grid transmission benefits, carbon emission reduction benefits, energy storage construction costs, transmission project construction costs and wind abandonment penalty costs. The channel construction and energy storage configuration scheme with the greatest net benefit can be obtained. The relationship between the transmission channel capacity setting and the energy storage parameter configuration under this model is studied, and the combined... [more]

The integrated scheduling problem in automated storage and retrieval systems (AS/RS) and the hybrid flowshop is critical for the realization of lean logistics and just-in-time distribution in manufacturing systems. The bi-objective model that minimizes the operation time in AS/RS and the makespan in the hybrid flowshop is established to optimize the problem. A mixed algorithm, named GA-MBO algorithm, is proposed to solve the model, which combines the advantages of the strong global optimization ability of genetic algorithm (GA) and the strong local search ability of migratory birds optimization (MBO). To avoid useless solutions, different cross operations of storage and retrieval tasks are designed. Compared with three algorithms, including improved genetic algorithm, improved particle swam optimization, and a hybrid algorithm of GA and particle swam optimization, the experimental results showed that the GA-MBO algorithm improves the operation efficiency by 9.48%, 19.54%, and 5.12% and... [more]

For decision-making and governance, smart cities depend on tracking data collected via a substantial percentage of wireless sensing nodes. However, several limitations affect Wireless Sensor Network (WSN)-based Internet of Things (IoT) services, such as low battery life, recurrent connectivity problems due to multi-hop connections, and a limited channel capacity. Furthermore, in many systems, clustering and routing are handled independently, which prevents the adaptation of effective strategies for optimal energy usage and prolonged network lifespan. This research gathers data from heterogeneous IoT nodes linked via WSN and distributed across a smart infrastructure. There are two interrelated problems to be addressed with respect to energy efficiency computations: clustering and routing. We provide a new clustering strategy through which efficient routing of critical and regular data is handled. As a result, both clustering and routing have been significantly strengthened, which balanc... [more]

Microgrids using renewable energy sources play an important role in providing universal electricity access in rural areas in the Global South. Current methods of system dimensioning rely on stochastic load profile modeling, which has limitations in microgrids with industrial consumers due to high demand side uncertainties. In this paper, we propose an alternative approach considering demand side management during system design which we implemented using a genetic scheduling algorithm. The developed method is applied to a test case system on Idjwi Island, Democratic Republic of the Congo (DRC), which is to be powered by a micro hydropower plant (MHP) in combination with a photovoltaic (PV) system and a battery energy storage system (BESS). The results show that the increased flexibility of industrial consumers can significantly reduce the cost of electricity. Most importantly, the presented method quantifies the trade-off between electricity cost and consumer flexibility. This gives loc... [more]

Keeping the global temperature rise below 2 degrees Celsius, as foreseen by the Paris Agreement, requires a new global roadmap for the energy transition. For this reason, the European Commission decided to directly involve local municipalities in reaching these objectives through multilevel, bottom-up actions for sustainable energy. The Covenant of Mayors is a very concrete demonstration of this trend of development and adoption of sustainable energy action plans (SEAP), rethinking the way cities operate and bringing them closer to energy self-sufficiency, with measures favouring local economic development and improving citizens’ quality of life. The numerous RES/RUE actions included in SEAPs at the regional level have led both to the request for huge funding and to increased complexity for regional managers to identify the best projects to be financed. To manage the multitude of data (emissions, energy consumption, cost, etc.) present in the SEAPs at a regional level, a web-based plat... [more]

The Kingdom of Saudi Arabia (KSA) has an ambitious plan to install 40 GW of solar photovoltaic (PV) capacity via large scale projects (majority of which are >100 MW) across the country by 2030. These projects are required to achieve a threshold percentage of the overall project cost as in country expenditure, termed “local content”. This threshold will rise to 40−45% by 2028, ensuring solar projects do not simply become investment opportunities for overseas companies but deliver jobs and skills development within the Kingdom. Local content is assessed across all aspects of a PV system—module, inverter, structure, etc. Typically, the PV module cost can range between ~34% to ~44% of the overall system cost. However, 56% of this module cost represents the manufacture of the solar cells. To maximise local content, the opportunity for KSA lies in module fabrication of imported solar cells. This study assesses the capacity readiness of the KSA to meet this opportunity in relation to its 2030... [more]

Optimal power flow (OPF) represents one of the most important issues in the electrical power system for energy management, planning, and operation via finding optimal control variables with satisfying the equality and inequality constraints. Several optimization methods have been proposed to solve OPF problems, but there is still a need to achieve optimum performance. A Slime Mould Algorithm (SMA) is one of the new stochastic optimization methods inspired by the behaviour of the oscillation mode of slime mould in nature. The proposed algorithm is characterized as easy, simple, efficient, avoiding stagnation in the local optima and moving toward the optimal solution. Different frameworks have been applied to achieve single and conflicting multi-objective functions simultaneously (Bi, Tri, Quad, and Quinta objective functions) for solving OPF problems. These objective functions are total fuel cost of generation units, real power loss on transmission lines, total emission issued by fossil... [more]

This article deals with the issue of human capital as a factor responsible for the emergence of development inequalities in rural areas. Its main goal is to analyze and evaluate the existing differences in the distribution of human capital resources in rural areas in Poland in relation to their socio-economic situation. The essence of human capital is expressed through the analogy of energy and capital in relation to the concept of homo energeticus. The essence of human capital is also expressed in terms of two components of its structure, i.e., health and the labor market. The level of human capital was expressed using two synthetic measures, i.e., the human capital ratio in the field of health (HCH) and the labor market (HCLM). The obtained research results indicate the existing differences in the spatial distribution of human capital, resulting in a polarization effect in the center-periphery system, and showing relations with the socio-economic structure of rural areas, their agric... [more]

As city areas have been experiencing dynamic growth, the efficient development of cities is becoming a priority for technologically advanced countries and for states further down on the list from the global leaders. Smart cities are friendly for both people and the environment, in which life is better, safer, and healthier, the results of a creative approach to developing and implementing various innovations. Boasting sustainable and modern infrastructure and management, ecological city centres are perceived as key foundations of the future. Still, developing cities towards being “smart” is a serious challenge, not just for self-government and government administrators, but also for entities offering technical and technological solutions used for the purpose of implementing the improvements. The research objective was an attempt to indicate the expected changes in the shaping of the idea of smart cities in Poland. The authors’ own research was conducted from 2 August to 31 August. The... [more]

The integration of large-scale wind and photovoltaic power into modern power grids leads to an imbalance between the supply and demand for resources of the system, where this threatens the safety and stable operation of the grid. The traditional mode of grid dispatch and the capability of regulation of conventional thermal power units cannot satisfy the demands of grid connection for large-scale renewable energy, where the system requires the compensation and coordinated dispatch of flexible power sources. In light of this problem, this paper establishes a model to quantify the uncertainty in the forecasted outputs of wind and photovoltaic power. This is used to develop forecasts of the output of wind and photovoltaic power for several groups of scenarios, and predictions with the best complementarity are selected as a typical set of scenarios by means of their generation, reduction, and combination. By taking full advantage of the complementarity in the rates of regulation of conventi... [more]

The large-scale development of renewable energy has an urgent demand for an adjustable power supply. For a multi-energy system with multiple types of heterogeneous power sources, including wind power, photovoltaic (PV) power, hydropower, thermal power and pumped storage, a novel semi-scheduling mode and a solution method were proposed in this paper. Firstly, based on the load and the reserve demand during the peak load period, the semi-scheduling mode was adopted to determine the start-up combination of thermal power units. Furthermore, by predicting the generating/pumping power, the working state of pumped storage units was determined to realize the independent solution of discrete integer variables. Secondly, the risk−utility function was constructed to quantify the attitude of pumped storage towards the uncertainty of renewable energy output, which completed the quotation and clearing of the pumped storage in the ancillary service market. Finally, by taking the minimum total quotati... [more]

Spatially separated locations may differ greatly with respect to their electricity demand, available space, and local weather conditions. Thus, the regions that are best suited to operating wind turbines are often not those where electricity is demanded the most. Optimally, renewable generation facilities are constructed where the maximum generation can be expected. With transmission lines limited in capacity though, it might be economically rational to install renewable power sources in geographically less favourable locations. In this paper, a stochastic bilevel optimisation is developed as a mixed-integer linear programme to find the socially optimal investment decisions for generation expansion in a multi-node system with transmission constraints under an emissions reduction policy. The geographic heterogeneity is captured by using differently skewed distributions as a basis for scenario generation for wind speeds as well as different opportunities to install generation facilities... [more]

This research focuses on finding the optimal location of reactive compensation in an unbalanced electrical power system (EPS). An EPS is named unbalanced when there is uncertainty in the behaviour of the power demand, which causes changes in the voltage profile and angle of each of the electrical power phases. For this reason, using reactive compensation will improve the voltage profiles and the magnitudes of reactive power in the transmission lines. The proposed methodology uses the optimal AC power flows as a basis, which is applied to each power phase and, through this methodology, the operating conditions of the EPS are determined. Then, based on the voltage profiles of each power phase, it was possible to determine the critical nodes of the system, so that afterwards, through heuristics, it was possible to find the optimal location of the reactive compensation that independently meets the needs of each phase. To evaluate the proposed methodology, the IEEE test systems of 9, 14, 30... [more]

In order to improve the efficiency of UAVs in transmission tower inspections, the UAV transmission tower inspection energy consumption model is proposed for the existing research in which there is no accurate energy consumption calculation method in transmission tower inspection, and the optimal energy consumption path for UAV transmission tower inspection is designed by combining with simulated annealing algorithm. Firstly, a real experimental environment is built for experimental data collection and analysis, and the energy consumption model for transmission tower inspection is constructed and the influencing factors are discussed and analyzed, and the energy consumption coefficients under different situations are obtained. Second, according to the constructed transmission tower inspection energy consumption model combined with the path planning algorithm, experimental simulation is conducted to plan the optimal energy consumption inspection path, and finally, the above results are v... [more]

Energy consumption schedulers have been widely adopted for energy management in smart microgrids. Energy management aims to alleviate energy expenses and peak-to-average ratio (PAR) without compromising user comfort. This work proposes an energy consumption scheduler using heuristic optimization algorithms: Binary Particle Swarm Optimization (BPSO), Wind Driven Optimization (WDO), Genetic Algorithm (GA), Differential Evolution (DE), and Enhanced DE (EDE). The energy consumption scheduler based on these algorithms under a price-based demand response program creates a schedule of home appliances. Based on the energy consumption behavior, appliances within the home are classified as interruptible, noninterruptible, and hybrid loads, considered as scenario-I, scenario-II, and scenario-III, respectively. The developed model based on optimization algorithms is the more appropriate solution to achieve the desired objectives. Simulation results show that the expense and PAR of schedule power u... [more]

Synchronized converters are being studied as a viable alternative to address the transition from synchronous generation to power-electronics-based generation systems. One of the important features that make the synchronous generator an unrivaled alternative for power generation is its stability properties and inherent inertial response. This work presents a stability analysis of a synchronverter-based system conducted through the bifurcation theory to expose its stability regions in a grid-connected configuration with an aggregate load model conformed by a ZIP model and an induction motor model. One and two-parameter bifurcation diagrams on the gain, load, and Thévenin equivalent plane are computed and analyzed. All the results confirm the strong stability properties of the syncronverter. Some relevant findings are that the reduction in a droop gain or time constant results in Hopf bifurcations and inertia reduction, but the increase in the time constant leads to decoupling between the... [more]

Demand forecasting produces valuable information for optimal supply chain management. The basic metals industry is the most energy-intensive industries in the electricity supply chain. There are some differences between this chain and other supply chains including the impossibility of large-scale energy storage, reservation constraints, high costs, limitations on electricity transmission lines capacity, real-time response to high-priority strategic demand, and a variety of energy rates at different hours and seasons. A coupled demand forecasting approach is presented in this paper to forecast the demand time series of the metal industries microgrid with minimum available input data (only demand time series). The proposed method consists of wavelet decomposition in the first step. The training subsets and the validation subsets are used in the training and fine-tuning of the LSTM model using the ELATLBO method. The ESC dataset used in this study for electrical demand forecasting include... [more]

Oil has historically been the most significant primary energy source for our daily lives and business activities. However, recent skyrocketing oil prices have been one of the greatest concerns among policymakers, business executives, and the general public due to their impacts on daily necessities, including food, clothing, and automobile transportation. As a result, fast-rising inflation on the global scale is attributed to mounting oil prices. Even though many countries have made a conscious effort to tame oil prices and the subsequent inflation, their efforts are often in vain due to some uncontrollable situations. These situations include the ongoing war between Ukraine and Russia, where Russia began weaponizing its oil resources and limiting oil supplies to its neighboring European countries. Faced with the current energy crisis, a growing number of policymakers and business executives have attempted to develop energy-induced risk mitigation strategies. With this in mind, the prim... [more]

Interoperability becomes a key issue for smart grid systems, as the interaction between diverse components needs to lead to a normal system operation. In this paper, we test interoperability issues with respect to home automation. In particular, interaction of a home energy management system (HEMS) is examined with an external actor for home/building remote control. We show the importance and the feasibility of remotely controlling domestic loads from outside the house premises, which can be crucial for energy saving operations, such as demand response. The Smart Grid Architecture Model (SGAM) is used, where the different actors are depicted. The interoperability testing methodology for smart grids, developed by our unit, is followed in order to design the necessary tests and execute them. For the experimental part, we develop an HEMS in our lab along with a Home Automation End Device (HAED), used to transform two normal plugs, and consequently, normal loads into smart ones, thus creat... [more]