Advances in Energy Market and Power System Modelling and Optimization

This article aims to analyze agents’ behavior in a competitive hydrothermal energy market. The idea is to investigate how much the day-to-day behavior of the market can be different from the predictions presented by cost-based models because of the risk perception of each agent (hydroelectric energy producer, in this case) as a participant of the market. The main contribution is in determining the impact on the agents’ revenue in the short-term market due to the variation in the amount of energy generated and the market price, which other methodologies may not be able to capture. For this reason, a case study was made using daily simulations in a given month, observing the strategy and bids of eight hydroelectric agents for a central market operator emulated by an energy price offer simulator called SOPEE. The study reflected qualitative and quantitative examples of how the risk perception and the behavior of each agent can influence market behavior due to the variation in their perceptions of the parameters that form the energy price. Full article

Transformer failures have a significant cost impact on the operation of an electrical network. In many utilities, transformers have been operating for many years past their expected usable life. As power demand has surged, transformers in some areas are being loaded beyond their rated capacity to meet the demand. One of the vital components in a transformer is the on-load tap changer (OLTC), which regulates the voltage in the distribution network. This study aims to review several condition-monitoring techniques (online and offline) that can monitor the health of the OLTC and assure the safety of the transformer’s OLTC from irreparable damage by detecting the defect at an earlier stage, which is preceded by the specification of typical faults. This paper also discussed the common faults of the OLTC and the root causes of these faults. The OLTC is prone to mechanical faults due to its frequently changing mechanism in the tap operation. The OLTC are also prone to oil as well as thermal faults. As a result, it is critical to monitor OLTC conditions while they are in use. Proper management of condition monitoring (CM) for the OLTC is useful and necessary to increase availability and achieve optimised operating. Condition monitoring (CM) and diagnostics methods (DM) have been developing since the 1950s. CM and DM have been implemented to diagnose and detect an incipient fault, especially for the OLTC. Many techniques, online and offline, are being used to monitor the condition of the OLTC to prevent failure and minimize outages. These DM and CM will prolong the operational cycle and avoid a major disaster for the OLTC, which is an unfavorable scenario. Full article

The penetration of renewable energy sources (RESs) in the electrical power system has increased significantly over the past years due to increasing global concern about climate change. However, integrating RESs into the power market is highly problematic. The output of RESs such as wind turbines (WTs) and photovoltaics (PVs) is highly uncertain. Their correlation with load demand is not always guaranteed, which compromises system reliability. Distributed energy resources (DERs), especially demand response (DR) programs and energy storage systems (ESSs), are possible options to overcome these operational challenges under the virtual power plant (VPP) setting. This study investigates the impact of using a DR program and battery energy storage system (BESS) on the VPP’s internal electricity market, and also cost-minimization analysis from a utility viewpoint. Three different constrained optimal power flow (OPF) problems are solved such as base case, DR case, and BESS case to determine total incurred costs, locational marginal prices (LMPs), and generator commitments. A scenario tree approach is used to model the uncertainties associated with WTs, PVs, and load demand. The proposed model is investigated on a 14-bus distribution system. The simulation results obtained demonstrate a favorable impact of DR and a BESS on renewable operational challenges. Full article

The growing share of renewable energies needs more flexible services to balance their intermittency and variance. The existing coal fired units and electrical energy storage (EES) systems may play an important role in delivering flexible services. The value of their flexibility services, along with the value of renewable energies, has to be analyzed from the perspective of the power system, in which the capacity costs and operation costs of renewable energy power units, EES systems, and thermal power generation units have to be taken into consideration. An optimal model is built to analyze the renewable energy integration and the flexibility services delivered by the EES systems and thermal power units in a power system. Taking the existing thermal power units and EES systems in North China Power Grid as an instance, the overall cost of the grid is examined for the penetration of renewable energies and flexible service provision. The results show that the growing shares of renewable energies are affected by their capacity credits and flexibility sources in the grid, and that the potential of thermal power units to provide flexible services will be reduced due to the replacement of renewable energies for thermal power generation. The results also indicate that the thermal units may be dispatched to have priority to delivering flexible services for the renewable energy integration, and that the curtailment of renewable energies may be regarded as one type of flexible service. According to these results, policy and strategy recommendations are put forward to weigh the role of existing coal-fired units and EES systems in providing flexible services, and to improve their compensation mechanism and their coordination. Full article

Energy management and utilization for commercial users is becoming increasingly intelligent and refined, fostering a closer and growing connection with the electricity market. In this paper, a novel energy management optimization theoretical framework for commercial users is proposed based on the hybrid simulation of electricity market bidding. The hybrid simulation model based on Multi-Agent Simulation (MAS) with reinforcement learning and System Dynamic Simulation (SDS) is established to solve the problem using a single simulation method: it cannot adjust the clearing price when considering the whole market; considering the uncertainty of Electric Vehicles (EVs) travel and Lighting Loads (LLs), the multi-objective optimization model of energy management for commercial users is constructed to minimize the total energy cost of commercial users, as well as maximize the lighting comfort of indoor office staff, which compensates for the lack of the single-objective optimization of the power consumption for commercial users. A multi-objective optimization model of energy management for commercial users is established based on the hybrid simulation of electricity market bidding. By running the multi-objective optimization model based on hybrid simulation, the results show that the proposed method can realize the optimization of energy management for commercial users considering electricity market bidding. Full article

The effective identification of the economic withholding behavior of the generators can help ensure the fair operation of the electricity market. A SCAD-logit model is proposed to improve the performance of the logit model for the massive data of electricity market. First, a social network analysis method is used to construct an equity relationship graph of the generators to obtain a set of key monitoring generators. An indicator system for identifying the economic withholding behavior of the generators is constructed based on structure conduct performance (SCP) theory. The indicators are screened by the smoothed clipped absolute deviation (SCAD) penalty regression method to reduce the collinearity and improve identification efficiency. Then, a SCAD-logit model is established to identify the economic withholding of key monitoring generators, so that the boundary contributions of each indicator to the economic withholding behavior are obtained. The confusion matrix, ROC curve, and AUC values are used to evaluate the model’s performance. Finally, the model is applied to the electricity spot market, and the method can identify the generators that exercise economic withholding behavior with a correct rate of 96.83%. Indicators such as market share, quotation fluctuation degree, high quotation index, and volume price index can be used as important indicators for identifying the economic withholding behavior. Full article

A new optimization technique is proposed for solving optimization problems having single and multiple objectives, with objective functions such as generation cost, loss, and severity value. This algorithm was developed to satisfy the constraints, such as OPF constraints, and practical constraints, such as ram rate limits. Single and multi-objective optimization problems were implemented with the proposed hybrid fruit fly-based artificial bee colony (HFABC) algorithm and the non-dominated sorting hybrid fruit fly-based artificial bee colony (NSHFABC) algorithm. HFABC is a hybrid model of the fruit fly and ABC algorithms. Selecting the user choice-based solution from the Pareto set by the proposed NSHFABC algorithm is performed by a fuzzy decision-based mechanism. The proposed HFABC method for single-objective optimization was analyzed using the Himmelblau test function, Booth’s test function, and IEEE 30 and IEEE 118 bus standard test systems. The proposed NSHFABC method for multi-objective optimization was analyzed using Schaffer1, Schaffer2, and Kursawe test functions, and the IEEE 30 bus test system. The obtained results of the proposed methods were compared with the existing literature. Full article

To avoid the potential adverse impacts of climate change from global warming, it is suggested that the target of net zero emissions should be reached by this mid-century. Thailand is aiming to achieve carbon neutrality by 2050. Since electricity generation is one of the largest producers of carbon dioxide emission, the associated emissions must be greatly reduced to achieve the targets mentioned above. Thus, new generation expansion plans must be well developed. This paper discusses the development of generation expansion plans considering Thailand’s latest policies along with enhancement of the existing multi-period linear programming model, allowing new electricity generation technologies having low emissions, e.g., solar PV with battery and hydrogen blending in natural gas, to be integrated into generation expansion planning. Then, four generation expansion plans with different levels of hydrogen blending in natural gas are proposed and discussed. It is found that Thailand can achieve carbon neutrality by 2050 by promoting more use of renewable energy altogether with trade-off between land for solar PV installation and amount of hydrogen blended in natural gas. The lesson learned from this study provides crucial information about possible pathways to achieve carbon neutrality in the electricity sector for policy makers in other countries. Full article

The increasing number of residential buildings that are installing distributed energy resources enforces the need for schemes to facilitate a local energy balance. With the continuing evolution of Internet of Things (IoT) technology, Peer-to-Peer (P2P) energy trading is becoming a viable solution to incentivize prosumers and promote efficient energy sharing in a community. This paper develops a model to quantitatively analyze the potential benefits of P2P energy trading for residential buildings that have installed photovoltaic battery systems. The integration of the bidding strategy into a residential energy-management system is feasible to realize cost savings for prosumers. However, the coordination between the bidding strategy and the optimal scheduling of energy has received far too little attention. To better participate in the P2P market, we propose a novel separate bidding energy-management system (SBEMS) that can realize rolling optimal energy scheduling while determining energy bids. The model’s effectiveness is verified via case studies of 75 participants in a community. The results indicate that the prosumers can reduce their costs by up to 24% by employing the proposed SBEMS in the P2P market. In addition, the proposed method is found to offer better performance in terms of economic and technical indices. Full article

This paper presents a method for multi-period optimization of natural gas and electric power systems incorporating gas-fired power plants to analyze the impact of the interdependence between those commodities, in terms of cost and energy supply. The proposed method considers electricity network constraints, such as voltage profile, electrical losses, and limits of the transmission lines, as well as the technical restrictions on the gas network, such as the diameter, length, pressure, and limits for those variables. The proposed method was applied to a 12-bus electric network and a 7-node gas network, and several interdependencies between the electricity and the natural gas system network can be observed. The results show how the restrictions cause the behavior of the gas-fired power plants—in a low demand stage, it is restricted even when the gas-fired power generation prices are below the hydraulic generation prices, while in scenarios of higher demand, saturated cargo flows are observed, causing bus bar prices to be affected with higher operating costs. In this sense, the results of the variation in bus bar prices show little price stability in some bus bars in different stages, due to the behavior of the generation supply that is forced to operate by system restrictions. Full article

Transition to green energy is the dominant process in the electricity sector globally, including in North-East Asia (NEA). The interstate power grid expansion in the NEA will facilitate the large-scale development of intermittent and uncertain green generation. This paper is aimed at considering the structural and operating features and effectiveness of a potential NEA power grid with large-scale penetration of renewables. A computing and geo-information system provides collection, processing, storage, and geo-visualization of technical and economic data. It incorporates a mathematical model for the optimization of the expansion and operation of power systems. Benefits (including saving the capacity, investment, fuel cost, and total cost) of power interconnection have been estimated in the study. Transfer capability required for the interstate electric ties was calculated and proved quite significant. A tax on greenhouse gases emission from thermal power plants, including carbon dioxide (CO₂), has been used in the study as an economic incentive to facilitate the penetration of renewable energy sources in NEA power interconnection. An installed capacity, power generation mix, power exchange among countries, and operating modes (dispatching) have been calculated for different levels of CO₂ emission tax. This study has shown the economic viability of the interconnection, defined major indices of interstate transmission grid infrastructure, revealed the changes in the mix of generating capacities and their operation under conditions of large-scale expansion of renewables, and found out the roles of various countries with different levels of CO₂ tax, detailed the impact of CO₂ emission tax in encouraging capacity additions and power generation growth from renewables. These capacities altogether suppress the expansion of coal-fired power plants in the potential North-East Asia power grid and contribute to achieving Sustainable Development Goals (SDG), particularly SDG 7, to ensure access to affordable, reliable, sustainable, and modern energy for all. Full article

During the last few years, nuclear energy has received great attention due to the increase in climate change awareness. According to the Paris agreement, global temperature is to be kept below 2 °C and preferably below 1.5 °C by 2050. This approach has been substantially confirmed in the recent COP 26 in Glasgow. This research investigates the effects of integrating SMR nuclear power plants (small modular reactors) into the Nordhaus Dynamic Integrated Climate Economy (DICE) model for reducing the CO₂ emissions in the atmosphere by substituting all existing fossil-fueled power plants (FPPP). The software is based on the VENSIM dynamic systems modeling platform. Simulations were carried out from the year 2019 to 2100 using 10-year increments. Several scenarios were thus simulated replacing roughly 70,000 FPPPs operating at this time in the world. Simulations indicate a CO₂ reduction of approximately 12.63% relative to the initial conditions used and using 87,830 SMR core units of 80 MWe electric each to meet such demand. The DICE model further predicts the cost of climate damage impacting the upper ocean and atmospheric temperatures, and the deep ocean temperature as USD 1.515 trillion (US Dollar; (US) trillion = 1,000,000,000,000 (1 × 10¹²)) by the end of this century. From a modified section of the model, a cost of USD 1.073 trillion is predicted as the toll on human health costs. This is thus equal to a USD 2.59 trillion loss in the economy. Full article

Recently, the integration of distributed generation and energy systems has been associated with new approaches to plant operations. As a result, it is becoming increasingly important to improve management skills related to distributed generation and demand aggregation through different types of virtual power plants (VPPs). It is also important to leverage their ability to participate in electricity markets to maximize operating profits. The present study focuses on VPP concepts, its different potential services, various control methodologies, distinct optimization approaches, and some practical implemented real cases. To this end, a comprehensive review of the most recent scientific literature is conducted. The paper concludes with remained challenges and future trends in the topic. Full article

In high-voltage cables, because of the close fit of their internal structures, interface pressure is generated between conductor and insulator, which affects the performance of the cable. Studies on the calculation and testing of the interfacial pressure of cable conductors are scarce because of the lack of a unified formula and the difficulty of direct measurement. As such, in this study, we devised two methods for calculating and measuring the interface pressure of cable conductors. In the first, we used two physical experimental methods. We used the friction between cable components to perform the calculation and create an experimental method for determining cable conductor interface pressure; on the basis of the equation of the pressure inside and outside a thick-walled cylinder using elasticity mechanics, we calculated the interface pressure on the basis of the measurement of the strain state of the inner and outer diameters of each layer of the cable under different assembly and stripping conditions. We verified the effectiveness of the methods through physical tests and simulations using a YJLW03 1 × 1200 high-voltage cable. Then, we used simulation software ANSYS and SolidWorks to calculate the interface pressure. With different simulation settings, we obtained results regarding interface pressure. Lastly, these simulated values were individually compared with two physical tests, and the error was calculated. Results obtained in the ANSYS environment showed that interface pressure values determined by the geometric interference normal stress, geometric interference pressure, contact interference normal stress, and contact interference pressure methods were 39.75, 36.84, 5.76, and 36.57 MPa, respectively. In SolidWorks software, we used the contact-stress and X-axis normal stress methods. Results were all 37.36 MPa. Then, simulation results and experimental results were compared, and error was calculated. The comparison showed that the X-axis orthogonal stress method was the most accurate. Errors between the X-axis orthogonal stress method and the two physical experiments were 1.5% and 0.48%. Through the above simulation and physical experiments, we determined the interface pressure between conductors and insulators in a high-voltage power cable. We obtained the cable interface pressure value through two kinds of physical experiments, and these two methods were clearly reliable. Simulation experiments showed that using SolidWorks software to simulate this problem obtained better results. Research results provide technical support and reference for the calculation and measurement of cable interface pressure and the optimization of cable performance. Full article

This paper proposes the analysis and design of the linear active disturbance rejection controller (LADRC) for the pitch angle model of a large wind turbine generator (WTG). Since the transfer function of the pitch control system exhibits nonminimum-phase characteristics, the parameters of LADRC are difficult to tune using the conventional bandwidth method. On the basis of PI controller parameters to first-order LADRC parameters, an optimization problem is proposed in this paper to find the parameters of an LADRC for the pitch control system under the constraint of robustness measure, and the extremum-seeking (ES) algorithm is used to solve the problem. Simulation results show that LADRC can achieve better tracking and disturbance rejection performance than traditional PI control without loss of robustness against time delay. Full article

In order to adapt to the development of the green power certificate trading (GPCT) and carbon emissions trading (CET) market, reduce the carbon emissions of the distribution network and increase the investment income, this paper proposes a new distribution network (NDN) planning and simulation operation bi-layer model with new energy (NE) as the main body, considering the GPCT and CET mechanisms. First, the upper layer determines the capacity and location of wind turbine (WT), photovoltaic (PV), hydraulic turbine (HT), micro turbine (MT), and energy storage (ES), while the lower simulation operation considers the operation costs of WT, PV, HT, MT, ES, load demand response (DR) and carbon emissions. The planning objective was to minimize the total cost of investment, operation and carbon emissions in the planning period. Then, on the basis of a traditional distribution network (TDN), security constraints, carbon emissions intensity, GPCT volume and CET volume were added. Finally, the cases study of the improved IEEE33 node and PG&E69 node NDN planning were provided. The results of NDN planning and TDN planning are compared and analyzed, and a sensitivity analysis was carried out to study the impact of GPCT and CET mechanisms with different price levels on investment planning. The results verify the applicability and rationality of the model. Full article

In this paper, a new method using wind turbulence excitation is proposed to estimate the parameters of the mechanical system (drivetrain and pitch angle controller) in a Doubly Fed Induction Generator (DFIG) Wind Turbine (WT). Firstly, simulations were carried out for a DFIG WT under turbulence excitations. The spectral contents of the responses imply that the transients of the electrical system (generator and converter), which are much faster than those of the mechanical system, can be neglected when estimating the mechanical parameters. Based on this, a simplified model related to the mechanical system of the DFIG WT was derived by applying the model reduction technique. Secondly, the parameter sensitivity of Power Spectral Density (PSD) was used to quantify the impacts of individual parameters on the dynamics of the mechanical system, and the influential parameters were selected on the basis of the sensitivity results. Finally, a weighted least-squares optimization problem, which is suitable for a system with close oscillation modes, was formulated for parameter estimation. The estimation results based on two different types of optimization methods were compared, and their estimation accuracies validate the effectiveness of the proposed method. Full article

Performance guarantees and tests of thermal power plants are usually carried out at 100% rate output capacity. However, fossil-fired power plants have decreased full load hours, affecting energy efficiency, and are subjected to frequent load changes caused by variable renewable electricity and potential grid stability. Therefore, this study is conducted to calculate and draw the characteristic curves for all stable loads of coal-fired power units including the 60%, 75%, and 100% rate output. The study focuses on the corrected plant net heat rates—gross unit outputs, net standard coal consumption rates—throttle steam pressures, and corrected plant net efficiencies—carbonic emission rates. In addition, the experimental investigation for energy efficiency and carbonic emission of the latest larger-scale (+600 MW) coal-fired power generation units in Vietnam are also implemented using a performance guarantee calculation software called “PG_Cal” version 0.0, which is based on a mass and energy balance method by MATLAB programing language. From the results of this study, it is suggested that the performance guarantees and tests of new coal-fired units should be carried out at different stable loads, including minimum load. Vietnam should apply the ultra-supercritical technology for new units in order to increase their efficiency and decrease carbon dioxide emissions. Full article

This paper presents a Nash equilibrium approach to model a non-cooperative game that takes place among Brazilian hydro-generating companies in the annual process called “seasonalization”. We have “remade” the seasonalizations that occurred in the period of 2013–2020 by using our model and comparing the financial outcomes with the current ones that resulted from the seasonalizations the generators made each year, with financial improvements in almost every year. By using the Nash equilibrium approach, it is possible to achieve optimal decisions concerning the seasonalization process that were not evident by using traditional methods. This approach is useful for companies willing to enhance their income and to improve their risk management by making better choices in seasonalization. Full article

Electric power systems (EPS) are exposed to disconnections of their elements, such as transmission lines and generation units, due to meteorological factors or electrical failures. Thus, this research proposes a smart methodology for the re-entry of elements that have been disconnected from the EPS due to unforeseen events. This methodology is based on optimal AC power flows (OPF-AC) which allow verifying the state of variables such as voltage, angular deviation, and power (these variables are monitored in normal and fault conditions). The proposed study considers contingencies N-2, N-3, N-4, and N-5, for which the disconnection of transmission lines and generation units are carried out randomly. The analysis of the EPS after the disconnections of the elements is carried out by means of the contingency index, with which the impact that the disconnections of the elements have on the EPS is verified. In this way, the optimal route is generated to restore the elements that went out of operation, verifying that when the elements re-enter the acceptable limits, voltage and voltage angle are not exceeded. According to the results of the methodology used, it was found that NM contingencies can be applied in the proposed model, in addition to considering stability restrictions, modeled as restrictions on acceptable voltage limits, and a new restriction for the voltage angle between the differences of the bars. Full article

Local voltage controllers (LVCs) are important components of a modern distribution system for regulating the voltage within permissible limits. This manuscript presents a sensitivity-based three-phase weather-dependent power flow algorithm for distribution networks with LVCs. More specifically, the proposed algorithm has four distinct characteristics: (a) it considers the three-phase unbalanced nature of distribution systems, (b) the operating state of LVCs is calculated using sensitivity parameters having accelerated convergence, (c) it considers the precise switching sequence of LVCs based on their reaction time delays, and (d) the nonlinear influence of weather variations in the power flow is also taken into consideration. Simulations and validation results presented indicate that the proposed approach outperforms other existing algorithms with respect to the accuracy and speed of convergence, thus making it a promising power flow tool for accurate distribution system analysis. Full article

Connecting photovoltaic micro-installations to a low-voltage network changes the operating conditions of the network. As a result, in certain situations, the permissible operating limits may be periodically exceeded. The risk of exceeding the normal operating conditions of the network depends on multiple factors, including the installed capacity of the photovoltaic sources. In this article, we use a time-series method to determine the annual risks of exceeding the bus voltage limits, the rated current of the lines and transformer, and the acceptable limit of the negative sequence component of bus voltage, as well as the risk of a reverse flow occurring, and the risk of energy losses increasing. We calculate these risks for different levels of penetration of the photovoltaic sources, different divisions of the rated power of the photovoltaic sources between individual phases, and different consumer load profiles. We perform calculations on a CIGRE test network using OpenDSS and statistical meteorological data for the Katowice (Poland) weather station. The results obtained indicate that connecting photovoltaic micro-installations to a low-voltage network has the greatest impact on the risk of reverse flow occurring and the risk of energy losses increasing. In addition, the risk of overvoltage and branch overload increases substantially. The method we present allows one to determine the value of the hosting capacity of a given low-voltage network, ensuring that the assumed risk of exceeding the normal operating conditions of the network is retained. Full article

In the medium- and long-term market, the power generation side and the power purchase side ensure to avoid the fluctuation of delivery prices through the medium- and long-term power contract, to avoid some market risks. This paper combines virtual power plants to aggregate distributed renewable energy to participate in market transactions. Firstly, this paper analyzes the two operation modes of power markets and combs the transaction varieties and modes in the medium- and long-term market. Secondly, the common contract power decomposition methods in the medium- and long-term market are analyzed, and the revenue model of virtual power plants is established. Then, combined with the renewable energy quota system and the green certificate trading mechanism, this paper constructs an optimization model of medium- and long-term contract trading of virtual power plants considering renewable energy derivatives. Finally, different renewable energy output scenarios are designed to analyze the benefits of virtual power plants in centralized and decentralized power markets. The example analysis shows the effectiveness of price difference contract for virtual power plants to ensure the renewable power revenue, which provides a certain reference for virtual power plants to participate in the power market. Full article

The main objective of this study is to apply structural equation modeling with partial least squares, and based on covariance, to assess the satisfaction of residential electricity consumers. The methodology used compares the results of both structural equation models to indicate the model that best fits the problem of measuring the satisfaction of residential consumers with electricity concessionaires and licensees. The sample used in the survey contained questionnaire responses from 86,175 individuals considering the period from 2014 to 2018. The constructs evaluated were satisfaction, quality, value, loyalty, and trust. A confidence interval analysis shows that all weights are significant, demonstrating the importance of all the indicators that represent the constructs. The trust, quality, and value constructs can explain 74.4% of the satisfaction construct variability, so this relationship’s explanatory capacity is considered substantial. Finally, the evaluation of the performance of the service provided by the electric energy concessionaires/licensees, measured by customer satisfaction, allows for the continuous improvement of services, and meeting, even if minimally, the expectations of its consumers. Full article

This paper presents the analysis of an energy management system (EMS) implemented to fulfill the requirements of a microgrid (MG) power supply owned by a small industrial company and connected to the rural power system. The main goal of this system is to ensure connection with the existing rural power system in terms of energy exchange, as well as to perform islanding mode operation of the microgrid based on the energy demand of the company. Power generated in the implemented microgrid is based on a hybrid system supported by renewable energy sources and an energy storage system. The aim of the developed energy management system implemented in this MG power system is to enable the microgrid to operate according to scheduled diagrams related to different load events. The presented investigation, analysis, and assessment of the implemented energy management system are based on the on-site measurements and observations of the long-term operation of the microgrid concerning the hybrid renewable energy-based generation system and the company energy demand, which is useful from perspective of the predicted deficiency of electrical energy in Poland, both for customers and transmission system operators. Furthermore, the observed drawbacks and failures of the implemented EMS and the MG are pointed out and discussed to overcome and minimize these disadvantages, and to improve the operational reliability of the whole system. Full article

This research proposes an optimization technique for an integrated energy system that includes an accurate prediction model and various energy storage forms to increase load forecast accuracy and coordinated control of various energies in the current integrated energy system. An artificial neural network is utilized to create an accurate short-term load forecasting model to effectively predict user demand. The 0–1 mixed integer linear programming approach is used to analyze the optimal control strategy for multiple energy systems with storage, cold energy, heat energy, and electricity to solve the problem of optimal coordination. Simultaneously, a precise load forecasting method and an optimal scheduling strategy for multienergy systems are proposed. The equipment scheduling plan of the integrated energy system of gas, heat, cold, and electricity is proposed after researching the operation characteristics and energy use process of the equipment in the combined power supply system. A system economic operation model is created with profit maximization in mind, while also taking into account energy coordination between energy and the power grid. The rationality of the algorithm and model is verified by analyzing the real data of a distributed energy station in Wuhan for two years. Full article

Global optimization of industrial plant configurations using organic Rankine cycles (ORC) to recover heat is becoming attractive nowadays. This kind of optimization requires structural and parametric decisions to be made; the number of variables is usually high, and some of them generate disruptive responses. Surrogate models can be developed to replace the main components of the complex models reducing the computational requirements. This paper aims to create, evaluate, and compare surrogates built to replace a complex thermodynamic-economic code used to indicate the specific cost (US$/kWe) and efficiency of optimized ORCs. The ORCs are optimized under different heat sources conditions in respect to their operational state, configuration, working fluid and thermal fluid, aiming at a minimal specific cost. The costs of 1449.05, 1045.24, and 638.80 US$/kWe and energy efficiencies of 11.1%, 10.9%, and 10.4% were found for 100, 1000, and 50,000 kWt of heat transfer rate at average temperature of 345 °C. The R-square varied from 0.96 to 0.99 while the number of results with error lower than 5% varied from 88% to 75% depending on the surrogate model (random forest or polynomial regression) and output (specific cost or efficiency). The computational time was reduced in more than 99.9% for all surrogates indicated. Full article

The present work proposes a Monte Carlo Simulation (MCS) to obtain availability projections for Hydroelectric Power Plants (HPP), based mainly on regulatory aspects involving the Availability Factor (AFA). The main purpose of the simulation is to generate scenarios to obtain statistics for risk analysis and decision-making in relation to the HPP. The proposed methodology consists of two steps, firstly, the optimization of the maintenance schedule of the hydroelectric plant is carried out, in order to allocate the mandatory maintenance in the simulation horizon. Then, for the MCS, scenarios of forced shutdowns of the Generating Units (GU) will be generated, which directly influence the operation and, consequently, the availability of the HPP. The scenarios will be inserted into an operation optimization model, which considers the impact of forced shutdown samples on the MCS. The proposed modeling was applied using real data from the Santo Antônio HPP, which is one of the largest hydroelectric plants in Brazil. Full article

This paper aims to provide the smart grid research community with an open and accessible general mathematical framework to develop and implement optimal flexibility mechanisms in large-scale network applications. The motivation of this paper is twofold. On the one hand, flexibility mechanisms are currently a hot topic of research, which is aimed to mitigate variation and uncertainty of electricity demand and supply in decentralised grids with a high aggregated share of renewables. On the other hand, a large part of such related research is performed by heuristic methods, which are generally inefficient (such methods do not guarantee optimality) and difficult to extrapolate for different use cases. Alternatively, this paper presents an MPC-based (model predictive control) framework explicitly including a generic flexibility mechanism, which is easy to particularise to specific strategies such as demand response, flexible production and energy efficiency services. The proposed framework is benchmarked with other non-optimal control configurations to better show the advantages it provides. The work of this paper is completed by the implementation of a generic use case, which aims to further clarify the use of the framework and, thus, to ease its adoption by other researchers in their specific flexibility mechanism applications. Full article

Clean and renewable energy sources are the preferable power system generations for the overall world. This research aims to present a very highly integrated, economic, professional, and simple construction, clean and natural resources usage of the renewable hybrid generation system. This research performs analysis, systematic representation, evaluation, and design of the hybrid proposed system—pico-hydraulic from home usage water and photovoltaic (PV)—to generate an optimal renewable generation system using a new professional control system. Applying this proposed technique in Egypt shows that the hybrid system successfully overcame Egypt’s energy crisis. Renewable energy will rise to 8.782% by increasing 7.323% (14,408.83 GWh/Y). Besides, this system increases the power supply reliability; it gives an additional emergency supply and reduces the exhausts from other generation stations (e.g., CO₂). The saving from this hybrid system is very effective for; the residential sector (subscribes), which will be ranged from 9599.298 million E£/10Ys up to 86,393.68 million E£/10Ys that equals 5399.6 million $, government to use this extra generation energy to reduce the maximum loads from various stations. A practical model has been presented with results to verify the high efficiency of the proposed system that illustrates the effective performance of the used hybrid system. Full article

Power quality can have a large detrimental effect on industrial processes and the commercial sector. Thus, this paper proposes a new technique to improve the power quality of electric power systems. This technique relies on auto-adjusting of the blade angle to mitigate the harmonics in wind generator active power. A new adaptive PI blade-angle controller is applied in this technique to reduce the total harmonic distortion (THD) of the output power. The parameters of the adaptive PI controller are initialized by using the Harmony Search algorithm (HSA), hybrid Harmony Search optimization and Equilibrium optimization (EO), and hybrid Harmony Search optimization and Teaching learning-based optimization (TLBO). The execution of the optimization algorithms relies mainly on the optimization objective function. Two optimization objective functions are mathematically modeled and compared to enhance the power quality. The first one is to minimize the sum square of error, while the second objective is to minimize the THD. Many case studies are applied with various wind-speed profiles under normal and faulty conditions. Results show the superiority of HSA hybrid EO algorithm with the second objective functions through reducing the harmonics and enhancing the power quality. Moreover, laboratory studies are applied to investigate the effect of the blade-angle variations on the extracted active power. Full article

In this research, an alternative methodology is proposed for the location of Static VAR Compensators (SVC) in power systems, considering the reconfiguration of reactive power flows through the optimal switching of the transmission stage, which resembles the contingency restriction N-1 usually considered in transmission expansion planning. Based on this methodology, the contingency index was determined, which made it possible to determine which is the contingency that generates the greatest voltage degradation in the system. For the quantification of reactive flows, optimal AC power flows were used, which minimize the operating costs of the power system subject to transmission line switching restrictions, line charge-ability, voltages and node angles. To determine the node in which the compensation should be placed, the contingency index criterion was used, verifying the voltage profile in the nodes. The proposed methodology was tested in the IEEE test systems of 9, 14 nodes and large-scale systems of 200, 500 and 2000 bus-bars; to verify that the proposed methodology is adequate, the stability of the EPS was verified. Finally, the model allows satisfactorily to determine the node in which the SVC is implemented and its compensation value. Full article

This paper proposes an optimal design method to suppress critical harmonics and improve the power factor by using passive power filters (PPFs). The main objectives include (1) minimizing the total harmonic distortion of voltage and current, (2) minimizing the initial investment cost, and (3) maximizing the total fundamental reactive power compensation. A methodology based on teaching–learning-based optimization (TLBO) and Pareto optimality is proposed and used to solve this multi-objective PPF design problem. The proposed method is integrated with both external archive and fuzzy decision making. The sub-group search strategy and teacher selection strategy are used to improve the diversity of non-dominated solutions (NDSs). In addition, a selection mechanism for topology combinations for PPFs is proposed. A series of case studies are also conducted to demonstrate the performance and effectiveness of the proposed method. With the proposed selection mechanisms for the topology combinations and parameters for PPFs, the best compromise solution for a complete PPF design is achieved. Full article

Ternary low melting point mixtures with the addition of LiNO₃ and Ca(NO₃)₂ have been presented as direct system candidates for CSP technologies due to having better physical and chemical properties than those of Solar Salt. In this study, thermal, physical and chemical properties are measured as is the corrosive behavior of stainless alloy VM12 (Cr 12%) when in contact with Solar Salt, 60% NaNO₃-40% KNO₃ (wt.%) and ternary 46% NaNO₃-19% Ca(NO₃)₂-35% LiNO₃ (wt.%). Gravimetric weight change measurements were performed on the test specimens, which were tested under accelerated fluid conditions (0.2 m s⁻¹) at 500 °C for 2000 h. This research confirms the potential of this novel formulation as a thermal storage medium and validates the suitability of ferritic VM12-SHC stainless steel as a structural material for CSP technology with Solar Salt. Meanwhile, the results obtained by scanning electron microscopy and X-ray diffraction indicate a reduction in the protective character of the oxide layer formed on this alloy when the medium contains calcium and lithium components. Full article

Gas insulated transmission lines (GILs) are used in electrical systems mainly for power transmission and High Voltage substation interconnection. In this paper, we focus on the development of complex numerical tools for the optimization of gas insulated HVDC components by the estimation of realistic electric field distribution and the voltage holding of the designed geometry. In particular, the paper aims at describing the correct modelling approach suitable to study high voltage components in DC, considering the nonlinear behaviour characterizing the electrical conductivity of solid and gas insulators. The simulated field distribution is then adopted to estimate the voltage holding of the dielectric gas, with a convenient engineering technique, based on the streamer criterion. These two tools are integrated in an automatic optimization package developed in COMSOL^® and MATLAB^®, with the purpose of adjusting the critical geometry features, suffering from excessive electrical stress and possibly giving rise to electrical breakdown, in order to guide the designer towards a robust solution. Full article

Various algorithms predominantly use data-driven methods for forecasting building electricity consumption. Among them, algorithms that use deep learning methods and, long and short-term memory (LSTM) have shown strong prediction accuracy in numerous fields. However, the LSTM algorithm still has certain limitations, e.g., the accuracy of forecasting the building air conditioning power consumption was not very high. To explore ways of improving the prediction accuracy, this study selects a high-rise office building in Shanghai to predict the air conditioning power consumption and lighting power consumption, respectively and discusses the influence of weather parameters and schedule parameters on the prediction accuracy. The results demonstrate that using the LSTM algorithm to accurately predict the electricity consumption of air conditioners is more challenging than predicting lighting electricity consumption. To improve the prediction accuracy of air conditioning power consumption, two parameters, relative humidity, and scheduling, must be added to the prediction model. Full article

Integrated energy systems have become an important research topic in the pursuit of sustainable energy development. This paper examines regional integrated energy systems, presents the typical architecture of regional integrated energy systems, and builds an integrated energy system model. Two evaluation indexes are proposed: the integrated energy self-sufficiency rate and the expected energy deficiency index. Based on these evaluation indexes and taking into account the uncertainty of wind power generation, a bi-level optimization model based on meta-heuristic algorithms and multi-objective programming is established to solve the problem of regional integrated energy system planning under different load structures and for multi-period and multi-scenario operation modes. A quantum evolutionary algorithm is combined with genetic algorithms to solve the problem. Full article

The article presents the concept of application of a multiphase matrix converter (MMC)-based device working as a phase-shifting control device in a power system. A matrix M × M multiphase converter is a simple structure incorporating M × M bidirectional switches, connecting M input phases to M output phases (a square structure is used). The device, in this research and under proposed control, is able to build M output sinusoidal-shape phases (desired output) from parts of input voltages. The proposed MMC-based device can be considered as a new flexible AC transmission system (FACTS) apparatus. Three basic control systems that enabled the creation of output waveforms as the combination of input ones were presented. Both 6 × 6 and 12 × 12 matrix structures were introduced, since 3 × 6 and 3 × 12 transformers are already in use. The mathematical, Simulink, and laboratory models were built to extract characteristic features of the MMC. The chosen “area-based” control procedure was based on finding a common point of area representing a certain switch (connecting a certain input and a certain output) and a time-dependent trajectory. Practical application of the MMC in a power system involves not only MMC analysis, but also the study of application requirements, possible converter topologies, and the development of new, reliable control algorithms. Particular consideration was given to the simplicity of the control and the analysis of the converter properties. The proposed control procedure did not use the PWM technique, but created output in similar way to a multilevel converter. Full article

Many studies have proposed a peer-to-peer energy market where the prosumers’ actions, including energy consumption, charge and discharge schedule of energy storage systems, and transactions in local energy markets, are controlled by a central operator. In this paper, prosumers’ actions are not controlled by an operator, and the prosumers freely participate in the local energy market to trade energy with other prosumers. We designed and modeled a local energy market with a management algorithm that uses community energy storage for prosumers who competitively participate in trade in the real-time energy market. We propose an energy-trade management algorithm that manages the trades of prosumers in two phases based on bids and offers submitted by prosumers. The first phase is to manage the trade of prosumers who have submitted fair prices to trade with other prosumers in the real-time energy market. The second phase is managing the trade of prosumers that could not trade in the first phase. Community energy storage is employed in the second phase and controlled by a reinforcement learning-based trading algorithm to decide whether to buy, sell, or do nothing with the prosumers. The action of buying and selling means charging and discharging the community energy storage, respectively. Numerical results show that the proposed trading algorithm gains a near-maximum profit. Besides, we verified that community energy storage yields more profit than the battery wear-out cost. Full article

For the future development of integrated energy systems with high penetration of renewable energy, an integrated community energy systems (ICES) dispatch model is proposed including various renewable energy sources and energy conversion units. Energy coupling matrices of ICES based on traditional energy hub (EH) models are constructed. Uncertainties of long-term forecast data of renewable energy sources and internal loads are depicted by multi-interval uncertainty sets (MIUS). To cope with the impacts caused by uncertainties of renewable energy sources and internal loads, the whole dispatch process is divided into two stages. Considering various constraints of ICES, we solved the dispatch model through the improved particle swarm optimization (IPSO) algorithm in the first stage. The optimal evolutionary dispatch is then proposed in the second stage to overcome the evolution and errors of short-term forecast data and obtain the optimal dispatch plan. The effectiveness of the proposed dispatch method is demonstrated using an example considering dramatic uncertainties. Compared with the traditional methods, the proposed dispatch method effectively reduces system operating costs and improves the environmental benefits, which helps to achieve a win-win situation for both energy companies and users. Full article

Recent works have addressed the analysis of some situations that alter the gearbox oil results in wind energy conversion systems (WECS). This work contributes by completing the analysis of additional situations, based on key operational data collected from 10 different multi-megawatt wind turbines at two different locations with two top-tier technologies, and has demonstrated that the oil analysis results can be altered in practice. As important as detecting these situations is to verify how the data collected by the different operators and transferred to the laboratories, this relevant information is not included in most cases. The issues that can stem from this lack of valuable data can be mitigated with a new and more complete template. This paper proposes a detailed template that is ready for an industrial use and contributes to standardizing the information handled by all actors. The suggested template, which is designed based on extensive experimental results and an in-depth analysis, provides detailed information for laboratories to improve conclusions, recommendations and action plans. The investigation provides a high archival value for researchers whose investigation deals with gearbox oil maintenance. Furthermore, the global impact of the proposal on the wind industry can be very relevant in terms of benefits and it will ultimately be an advance in the evolution of the operation and maintenance of wind farms. Full article

A novel hybrid state space modeling approach for a dual armature generator is presented. The model uses finite element analysis to obtain the rotor angle-dependent parameters, namely the flux linkage, stator inductances and cogging torque, which are then incorporated into the dynamic equations of the hybrid model using Fourier representations of the physical parameters as function of the rotor angle. The proposed hybrid model addresses many of the limitations of the classical modeling approach, which uses analytical expressions to obtain flux linkage and stator inductances based on significant simplifications. The proposed model is verified experimentally by simulating the dynamics of a three-phase permanent magnet generator. Predictions based on the new hybrid model are compared to both experimental measurements and predictions based on the classic modeling approach. It is shown that the proposed hybrid model simulates the dynamics of the demonstration machine to within 7% peak error in the stator current and provides a 13% improvement to the prediction of the rotor velocity compared with the classic model. Full article