The fault data of the secondary system of smart substations hide some information that the association analysis algorithm can mine. The convergence speed of the Apriori algorithm and FP-growth algorithm is slow, and there is a lack of indicators to evaluate the correlation of association rules and the method to determine the parameter threshold. In this paper, the H-mine algorithm is used to realize the fast mining of fault data. The algorithm can traverse data faster by using the data structure of the H-struct. This paper also sets the lift and CF value to screen the association rules with good correlation. When setting the three key parameters of association analysis, namely, support threshold, confidence threshold, and lift threshold, an objective function composed of weighted average lift, CF value, and data coverage rate was selected, and the adaptive fireworks algorithm was used to optimize the parameters in the association analysis. In particular, the rule screening strategy is... [more]

In recent years, wind farm layout optimization (WFLO) has been extendedly developed to address the minimization of turbine wake effects in a wind farm. Considering that increasing the degrees of freedom in the decision space can lead to more efficient solutions in an optimization problem, in this work the WFLO problem that grants total freedom to the wind farm area shape is addressed for the first time. We apply multi-objective optimization with the power output (PO) and the electricity cable length (CL) as objective functions in Horns Rev I (Denmark) via 13 different genetic algorithms: a traditionally used algorithm, a newly developed algorithm, and 11 hybridizations resulted from the two. Turbine wakes and their interactions in the wind farm are computed through the in-house Gaussian wake model. Results show that several of the new algorithms outperform NSGA-II. Length-unconstrained layouts provide up to 5.9% PO improvements against the baseline. When limited to 20 km long, the obta... [more]

Considering nonlinear variation of working fluid’s specific heat with its temperature, finite-time thermodynamic theory is applied to analyze and optimize the characteristics of an irreversible Atkinson cycle. Through numerical calculations, performance relationships between cycle dimensionless power density versus compression ratio and dimensionless power density versus thermal efficiency are obtained, respectively. When the design parameters take certain specific values, the performance differences of reversible, endoreversible and irreversible Atkinson cycles are compared. The maximum specific volume ratio, maximum pressure ratio, and thermal efficiency under the conditions of the maximum power output and maximum power density are compared. Based on NSGA-II, the single-, bi-, tri-, and quadru-objective optimizations are performed when the compression ratio is used as the optimization variable, and the cycle dimensionless power output, thermal efficiency, dimensionless ecological fun... [more]

Power systems optimization is generally subject to the compromise between performance and cost. The 2021 Texas grid outage illustrates the worldwide dangers for the regional-centralized power grid, with comparable advantages to safety and flexibility for the distributed energy system. The storage of household batteries helps balance grid load and increase system stability and flexibility. However, household storage battery is still not widely used today because of its high costs. Currently, research on increasing household battery storage applicability is focused largely on optimizing economic strategies, such as configuration, dispatching and subsidy policies, which rely substantially more on technologies and financial perspectives. Consumers are not ‘rational’ individuals, and non-economic incentives can affect their decisions without raising prices. This paper consequently proposes to encourage users to acquire household battery storage to increase efficiency of power dispatching an... [more]

To relieve the peak operating power of the electric grid for an electric bus fast-charging station, this paper proposes to install a stationary energy storage system and introduces an optimization problem for obtaining the optimal sizes of an energy buffer. The charging power demands of the fast-charging station are uncertain due to arrival time of the electric bus and returned state of charge of the onboard energy storage system can be affected by actual traffic conditions, ambient temperature and other factors. The introduced optimization is formulated as a stochastic program, where the power matching equality of the total charging demands of connected electric buses is described as a chance constraint by denoting a satisfaction probability, then a stochastic supremum for the operating power of the electric grid is defined by actual data and the problem finally can be solved by convex programming. A case study for an existing electric bus fast-charging station in Beijing, China was u... [more]

The transformation of energy grids towards smart grids is driven by numerous political, economic, and ecological goals. As part of this process, the centralized top-down architecture of energy grids changes towards increasingly decentralized structures. It is widely accepted that the challenges emerging from this transition threaten the resilient operation of energy grids. For instance, the volatility of renewable energy sources challenges the required balance between demand and supply; their distribution in the energy grid likewise complicates their coordination. Holarchies are a promising (systems-of-systems) architectural pattern for smart grids fostering fast isolation and self-sustained operation of subparts (so-called holons), as well as supporting dynamic reconfigurations of the grid’s structure. To leverage these properties to increase the resilience of smart grids, we propose a system model that combines a holonic architecture and locally available resources offered by prosume... [more]

This paper proposes the application of a metaheuristic algorithm inspired by the social behavior of chimps in nature, called Chimp Optimization Algorithm (ChOA), for the maximum power point tracking of solar photovoltaic (PV) strings. In this algorithm, the chimps hunting process is mathematically articulated, and new mechanisms are designed to perform the exploration and exploitation. To evaluate the ChOA, it is applied to some fixed dimension benchmark functions and engineering problem application of tracking maximum power from solar PV systems under partial shading conditions. Partial shading condition is a common problem that appears in the solar PV modules installed in domestic areas. This shading alters the power developed by the solar PV panel, and exhibits multiple peaks on the power variation with voltage (P-V) characteristic curve. The dynamics of the solar PV system have been considered, and the mathematical model of a single objective function has been framed for tuning the... [more]

Electricity consumption forecasting plays an important role in investment planning of electricity infrastructure, and in electricity production/generation and distribution. Accurate electricity consumption prediction over the mid/long term is of great interest to both practitioners and academics. Considering that monthly electricity consumption series usually show an obvious seasonal variation due to their inherent nature subject to temperature during the year, in this paper, seasonal exponential smoothing (SES) models were employed as the modeling technique, and the particle swarm optimization (PSO) algorithm was applied to find a set of near-optimal smoothing parameters. Quantitative and comprehensive assessments were performed with two real-world electricity consumption datasets on the basis of prediction accuracy and computational cost. The experimental results indicated that (1) whether the accuracy measure or the elapsed time was considered, the PSO performed better than grid sea... [more]

It is common practice, in the production of photovoltaic energy to only use the south-exposed roof surface of a building, in order to achieve the maximum production of solar energy while lowering the costs of the energy and the solar technologies. However, using the south-exposed surface of a roof only allows a small quota of the energy demand to be covered. Roof surfaces oriented in other directions could also be used to better cover the energy load profile. The aim of this work is to investigate the benefits, in terms of costs, self-sufficiency and self-consumption, of roof integrated photovoltaic technologies on residential buildings with different orientations. A cost-optimal analysis has been carried out taking into account the economic incentives for a collective self-consumer configuration. It has emerged, from this analysis, that the better the orientation is, the higher the energy security and the lower the energy costs and those for the installation of photovoltaic technologi... [more]

The design of energy systems is very important in order to reduce operating costs and guarantee the reliability of a system. This paper proposes a new algorithm to solve the design problem of optimal multi-objective redundancy of series-parallel power systems. The chosen algorithm is based on the hybridization of two metaheuristics, which are the bat algorithm (BA) and the generalized evolutionary walk algorithm (GEWA), also called BAG (bat algorithm with generalized flight). The approach is combined with the Ushakov method, the universal moment generating function (UMGF), to evaluate the reliability of the multi-state series-parallel system. The multi-objective design aims to minimize the design cost, and to maximize the reliability and the performance of the electric power generation system from solar and gas generators by taking into account the reliability indices. Power subsystem devices are labeled according to their reliabilities, costs and performances. Reliability hangs on an... [more]

Local flexibility markets or smart markets are new tools used to harness regional flexibility for congestion management. In order to benefit from the available flexibility potential for grid-oriented or even grid-supportive applications, complex but efficient and transparent allocation is necessary. This paper proposes a constrained optimization method for matching the flexibility demand of grid operators to the flexibility supply using decentralized flexibility options located in the distribution grid. Starting with a definition of the operational and stakeholder environment of smart market design, various existing approaches are analyzed based on a literature review and a resulting meta-analysis. In the next step, a categorization of the allocation method is conducted followed by the definition of the optimization goal. The optimization problem, including all relevant input parameters, is identified and formulated by introducing the relevant boundary conditions and constraints of fle... [more]

This study proposes a calculation methodology that determines the optimal boundary parameters of the single-diode photovoltaic model. It allows the calculation of the single-diode photovoltaic model when no reference parameter boundaries are available. The differential evolution algorithm, integrated with a step-by-step boundary definition module, is used to calculate the optimal parameters of the single-diode photovoltaic model, improving the performance of the classic algorithm compared with other studies. The solution is validated by comparing the results with well-established algorithms described in the state-of-the-art, and by estimating the five important points (cardinal points) of an IV curve, namely short-circuit, maximum power, and open circuit points, using a database composed of 100 solar photovoltaic modules. The results show that an optimal set of parameter boundaries enables the differential evolution algorithm to minimize the error of the estimated cardinal points. More... [more]

The participation of household prosumers in wholesale electricity markets is very limited, considering the minimum participation limit imposed by most market participation rules. The generation capacity of households has been increasing since the installation of distributed generation from renewable sources in their facilities brings advantages for themselves and the system. Due to the growth of self-consumption, network operators have been putting aside the purchase of electricity from households, and there has been a reduction in the price of these transactions. This paper proposes an innovative model that uses the aggregation of households to reach the minimum limits of electricity volume needed to participate in the wholesale market. In this way, the Aggregator represents the community of households in market sales and purchases. An electricity transactions portfolio optimization model is proposed to enable the Aggregator reaching the decisions on which markets to participate to ma... [more]

Efficient and accurate estimations of unidentified parameters of photovoltaic (PV) models are essential to their simulation. This study suggests two new variants of the whale optimization algorithm (WOA) for identifying the nine parameters of the three-diode PV model. The first variant abbreviated as RWOA is based on integrating the WOA with ranking methods under a novel updating scheme to utilize each whale within the population as much as possible during the optimization process. The second variant, namely HWOA, has been based on employing a novel cyclic exploration-exploitation operator with the RWOA to promote its local and global search for averting stagnation into local minima and accelerating the convergence speed in the right direction of the near-optimal solution. Experimentally, RWOA and HWOA are validated on a solar cell (RTC France) and two PV modules (Photowatt-PWP201 and Kyocera KC200GT). Further, these proposed variants are compared with five well-known parameter extract... [more]

The constant problems evidenced in the Brazilian hydrological scenario, where the source of hydraulic potential corresponds to about 63.9% of the energy matrix, coupled with the exponential growth in the supply of renewable energy, corroborates the importance of thermal power generation as the basis of Brazilian’s energy matrix. With the operation of thermal power plants, which characteristically involve a large number of systems, subsystems, and auxiliary equipment, there is a high demand for the use of methodologies for monitoring and controlling processes, analyzing failures, and implementing improvements and actions that increase the reliability and, consequently, reduce the failure rate. In this context, decision-making about prioritizing criticality for operational monitoring of an asset’s components, from the perspective of operation and maintenance planning and based on reliability-centered maintenance (RCM) concepts, can be considered a complex task. Given this, the research s... [more]

Cryosorption pumps create a vacuum by adsorbing gas at low temperature through porous solid adsorbents. The transmission probability of gas molecules and heat loads of cryosorption pumps are important factors affecting its performance. Herein, Molflow software based on the Monte Carlo principle is used to analyze the effects of the structural design of cryosorption pumps on transmission probability. The influence of structural design on radiation heat transfer is analyzed by ANSYS Steady-State Thermal software. This provides a reference for the design of a cryosorption pump to validate the prototype of a neutral beam injector for the China Engineering Fusion Experimental Reactor (CFETR).

Green energy has become a media issue due to climate changes, and consequently, the population has become more aware of pollution. Wind farms are an essential energy production alternative to fossil energy. The incentive to produce wind energy was a government policy some decades ago to decrease carbon emissions. In recent decades, wind farms were formed by a substation and a couple of turbines. Nowadays, wind farms are designed with hundreds of turbines requiring more than one substation. This paper formulates an integer linear programming model to design wind farms’ cable layout with several turbines. The proposed model obtains the optimal solution considering different cable types, infrastructure costs, and energy losses. An additional constraint was considered to limit the number of cables that cross a walkway, i.e., the number of connections between a set of wind turbines and the remaining wind farm. Furthermore, considering a discrete set of possible turbine locations, the model... [more]

In this article, an efficient long-term novel scheduling technique is proposed for allocating capacitors in a combined system involving distributed generation (DG) along with radial distribution systems (RDS). We introduce a unique multi-objective function that focuses on the reduction of power loss with the maximization of voltage stability index (VSI) subjected to constraints of equality and inequality systems. Loss sensitivity factor and VSI together are involved in pre-identifying the locations of capacitors and DG. Determination of the optimal size of capacitor and DG is performed by utilizing the Bat algorithm (BA) for all the loads in RDS. The conventional approach considers the medium load of (1.0) condition generally, but the proposed method changes the feeder loads linearly, ranging from light load (0.5) to peak load (1.6) with the value of step size as 1%. BA determines the optimal size of the capacitor and DG for each step load. The curve fitting technique is used for deduc... [more]

The adoption of electric buses in public transport requires careful planning for the bus fleet and charging infrastructure. A mathematical model of an urban bus service was developed to support the deployment of charging infrastructure. The novelty of the model is that it incorporates infrastructure elements for both static and dynamic charging technologies at the same time. The model supports the electrification of the bus lines without route and schedule adjustments. The volume of charged energy at charging units is considered as a variable in the objective function to determine the location of charging units at minimum cost. The model was verified by a case study based on actual bus service data. It was found that the use of static chargers is more favorable if the cost of a static charging unit is less than the cost of a dynamic charger with a length of 1600 m and the charging power of static chargers is three times greater than the charging power of dynamic chargers. The relations... [more]

Transient stability preventive control (TSPC) ensures that power systems have a sufficient stability margin by adjusting power flow before faults occur. The generation of TSPC measures requires accuracy and efficiency. In this paper, a novel model interpretation-based multi-fault coordinated data-driven preventive control optimization strategy is proposed. First, an augmented dataset covering the fault information is constructed, enabling the transient stability assessment (TSA) model to discriminate the system stability under different fault scenarios. Then, the adaptive synthetic sampling (ADASYN) method is implemented to deal with the imbalanced instances of power systems. Next, an instance-based machine model interpretation tool, Shapley additive explanations (SHAP), is embedded to explain the TSA model’s predictions and to find out the most effective control objects, thus narrowing the number of control objects. Finally, differential evolution is deployed to optimize the generatio... [more]

The world community is worried about the effects of global warming. A few agreements on the reduction of CO2 emissions have been signed recently. A large part of these emissions is produced by the power production industry. Soon, the requirements for thermal power plant ecology and efficiency performance may become significantly higher. Thus, the contemporary problem is the development of highly efficient power production facilities with low toxic and greenhouse gas emission. An efficient way to reduce CO2 emissions into the atmosphere, which implies maintaining economic growth, is the creation of closed thermodynamic cycles with oxy-fuel combustion. The Allam cycle is one of the most promising among oxy-fuel power plants. A 50 MW pilot Allam cycle plant was built in Texas. The design for a commercial system with an electrical output of 300 MW is under development. This work is devoted to the improvement of the efficiency and environmental safety of oxy-fuel combustion power cycles via... [more]

In the paper, an analytical method for determining the optimal positioning of intelligent electronic devices in medium voltage grids is proposed. Intelligent electronic devices are automated devices able to communicate one with each other and command the circuit breaker in order to localize and isolate a line fault as fast as possible. However, the number of intelligent electronic devices to install has to be limited, due to the relevant installation costs and the reduction in the transmission bandwidth caused by the increased number of exchanged messages. So, the electrical distributor has to carefully detect the nodes of the grid where the intelligent electronic devices have to be installed. The authors propose a method based on integer linear programming, which, given the number of intelligent electronic devices to install, finds their optimal position, i.e., the one that minimizes the penalties associated with the power down experienced by customers. In order to highlight the offer... [more]

Energy storage systems are expected to play a fundamental part in the integration of increasing renewable energy sources into the electric system. They are already used in power plants for different purposes, such as absorbing the effect of intermittent energy sources or providing ancillary services. For this reason, it is imperative to research managing and sizing methods that make power plants with storage viable and profitable projects. In this paper, a managing method is presented, where particle swarm optimisation is used to reach maximum profits. This method is compared to expert systems, proving that the former achieves better results, while respecting similar rules. The paper further presents a sizing method which uses the previous one to make the power plant as profitable as possible. Finally, both methods are tested through simulations to show their potential.

The reliability of the electrical system is a fundamental study that is carried out to determine the possible deficiencies that an electrical system can have in case of failures, since a failure can cause disturbances, power cuts, and load disconnections. For this reason, Optimal Transmission Switching (OTS) with Optimal AC Power Flows (OPF-AC) is used to reduce disturbances when faults occur and minimize equipment load and disconnections, but OTS offers possible switches in order to make it possible to reduce the damage that can be done for a fault with operating limitations in voltage, power, and angular deviation. However, to have a complete study, it is proposed to use a reliability analysis through contingency ranking to know the risks that a switched system may have at the time of simultaneous or consecutive failures. In addition, a load capacity investigation is conducted to determine if the transmission lines are within their operating limits. The study presents an analysis of... [more]

Real-time estimation of transmission line (TL) parameters is essential for proper management of transmission and distribution networks. These parameters can be used to detect incipient faults within the line and hence avoid any potential consequences. While some attempts can be found in the literature to estimate TL parameters, the presented techniques are either complex or impractical. Moreover, none of the presented techniques published in the literature so far can be implemented in real time. This paper presents a cost-effective technique to estimate TL parameters in real time. The proposed technique employs easily accessible voltage and current data measured at both ends of the line. For simplicity, only one quarter of the measured data is sampled and utilized in a developed objective function that is solved using the whale optimization algorithm (WOA) to estimate the TL parameters. The proposed objective function comprises the sum of square errors of the measured data and the corr... [more]