Social Welfare Maximization of Competitive Congested Power Market Considering Wind Farm and Pumped Hydroelectric Storage System

The utilization of wind energy sources with energy storage systems has been increased in the power sector to satisfy the consumer’s energy demand with minimum price. This paper presents the impact of a wind farm (WF) and pumped hydroelectric storage (PHS) system in the competitive electricity market under a congested transmission system. The PHS system is used to compensate for the deviation of WF generation in the real-time electricity market. To investigate the impact of the proposed method, initially, the market-clearing power problem is solved without consideration of WF and PHS systems, and again it is solved with the WF and PHS systems. The optimal location of the WF and PHS systems is decided by the bus sensitivity factor (BSF) of these systems. The analysis is carried out by using generator sensitivity factor (GSF) with the help of the moth flame optimization (MFO) algorithm and thereby calculating market clearing price (MCP) and market clearing volume (MCV). The MFO algorithm is used here for the first time for solving the congested market-clearing power problem with the integration of WF and PHS systems under deregulated environment. The presented approach shows the improvement of social welfare after the placement of WF and PHS in the congested deregulated system. Modified IEEE 30 bus system is used to solve the market-clearing power problem and results obtained from the MFO algorithm are compared with the firefly algorithm (FA). Three different real-time wind speed data have been considered here to verify the proposed approach with uncertainty and the continuously changing nature of wind flow. It is discovered that social welfare is improved with the quantity addition of wind power, regardless of optimization techniques

ANTI-ULCER AGENTS: A PHARMACOLOGICAL UPDATE OF THE PAST TEN YEARS

New anti-ulcer substances are still vitally necessary for the people of countries such as India and South Africa to avoid high cost of the most prescribed marketed anti-ulcer drugs (proton-pump inhibitors). New candidate against gastric ulcer is also necessary to avoid the potential problem (enterochromaffin-like cell hyperplasia may be induced) associated with the long-term use of synthetic proton-pump inhibitors. However, the search for the novel entity against ulceration is challenging because of the complexity of the ulcer process and its role in host defense to infections. Nature is the source of remedies for the humankind. Among the different biological activities of the natural products that have been published till date, anti-ulcer is one of the most reported effects. Some single natural products such as curcumin, 1-hydroxy-3,7,8-trimethoxyxanthone, cinnamic acid, thymol, epoxycarvone, and menthol; single synthetic products such as, 4,6-diaryl-3, 4-dihydropyrimidin-2(1H)-thiones, 1,4-dihydropyrimidine derivatives, and dihydropyrimidinone and piperidine hybrids; plant products such as Aloe vera, Mangifera indica, Zingiber officinale, Azadirachta indica, Psidium guava, Carica papaya, Panax ginseng, Terminalia chebula, Ocimum sanctum, Daucus carota, and Mimosa pudica, Alpinia galangal; nutraceuticals such as garlic, cauliflower, banana, honey, cucumber, and cod liver oil with anti-ulcer effects have been discussed in this review. A complete review of literature was conducted using different databases on ScienceDirect, Scopus, PubMed, and Google Scholar. This review is a genuine attempt to explore the past 10 years’ pharmacological update of some anti-ulcer agents

A Risk Curtailment Strategy for Solar PV-Battery Integrated Competitive Power System

Power system networks are becoming more complex and decentralized with the foreword of deregulation in the global power sector. In this scenario, an independent system operator (ISO) is responsible for determining the appropriate actions to deliver stable and quality power to the customers connected to the network at the lowest cost without violating the system security limits. Violations of any security limit may result in system risk. The unstable and non-reliable system always has some drawbacks and is not desirable from the consumer’s point of view. A deregulated power market always keeps the consumer on the advantage side by giving stable, reliable, and less costly power. By using risk assessment tools, we identify the fault conditions and we try to minimize the risk by various uses of sequential programming methods. In this paper, a novel power system risk analysis and congestion management approach are introduced with considering meta-heuristic algorithms i.e., Slime Mould Algorithm (SMA) and Artificial Bee Colony Algorithm (ABC) in renewable energy integrated electricity market. The proposed power system risk analysis is constructed with the help of two risk valuation tools named Conditional-Value-at-risk (CVaR) and Value-at-risk (VaR). The higher negative value of VaR and CVaR represents the higher risk system and lower negative value or towards a positive value of VaR and CVaR denotes the less risk or stable system. The projected method has been experienced on the IEEE 14-bus test system and IEEE 30-bus test system to examine the usefulness of the meta-heuristic algorithm in system risk analysis under the deregulated environment. The importance of renewable energy integration in system risk curtailment has also been depicted in this work: basically, to measure the system’s risk, hence enhancing the system’s reliability and societal welfare. As a result, it will benefit both supply and demand-side participants

A Strategy for System Risk Mitigation Using FACTS Devices in a Wind Incorporated Competitive Power System

Electricity demand is sharply increasing with the growing population of human beings. Due to financial, social, and political barriers, there are lots of difficulties when building new thermal power plants and transmission lines. To solve this problem, renewable energy sources and flexible AC transmission systems (FACTS) can operate together in a power network. Renewable energy sources can provide additional power to the grid, whereas FACTS devices can increase the thermal limit of existing transmission lines. It is always desirable for an electrical network to operate under stable and secure conditions. The system runs at risk if any abnormality occurs in the generation, transmission, or distribution sections. This paper outlines a strategy for reducing system risks via the optimal operation of wind farms and FACTS devices. Here, a thyristor-controlled series compensator (TCSC) and a unified power flow controller (UPFC) have both been considered for differing the thermal limit of transmission lines. The impact of the wind farm, as well as the combined effect of the wind farm and FACTS devices on system economy, were investigated in this work. Both regulated and deregulated environments have been chosen to verify the proposed approach. Value at risk (VaR) and cumulative value at risk (CVaR) calculations were used to evaluate the system risk. The work was performed on modified IEEE 14 bus and modified IEEE 30-bus systems. A comparative study was carried out using different optimization techniques, i.e., Artificial Gorilla Troops Optimizer Algorithm (AGTO), Honey Badger Algorithm (HBA), and Sequential Quadratic Programming (SQP) to check the effect of renewable integration in the regulated and deregulated power systems in terms of system risk and operating cost

Existing Stature and Possible Outlook of Renewable Power in Comprehensive Electricity Market

The massive growth in power demand and the sharp decay in the availability of conventional energy sources forces society to move toward renewable power consumption. The rise in renewable energy utilization is one of the greatest strategies involved in making the environment clean, green, and emission-free. The investment cost is slightly high for this kind of resource, but their running costsare very minimal, which encourages power producers to invest in renewable power plants. Power producers always focus on their economic profit and possible feasibilities before the investment in a new power plant setup. Wind, small hydro, and solar photovoltaics have been considered the foremost efficient and feasible renewable sources. In 2021, the worldwide renewable power capacity had grown to 17%, despite supply chain disturbances and surges in prices. The renewable power market set a target of achieving a 95% increment in global power capacity by 2026. Hence, humankind should consider wind, hydro, and solar photovoltaics as the main energy sources, and there is a need to increase use of such sources. This paper highlights the latest developments, enormous technologies, and upcoming aspects of wind power, hydropower, and solar photovoltaics in India, as well as around the globe. The present status of renewable energy can motivate global power producers to spend their money on the installation of a new renewable power plant to obtain more economic benefits and give societal economic and environmental payback to humans

Profit Maximization with Imbalance Cost Improvement by Solar PV-Battery Hybrid System in Deregulated Power Market

The changeable nature of renewable sources creates difficulties in system security and stability. Therefore, it is necessary to study system risk in several power system scenarios. In a wind-integrated deregulated power network, the wind farm needs to submit the bid for its power-generating quantities a minimum of one day ahead of the operation. The wind farm submits the data based on the expected wind speed (EWS). If any mismatch occurs between real wind speed (RWS) and expected wind speed, ISO enforces the penalty/rewards to the wind farm. In a single word, this is called the power market imbalance cost, which directly distresses the system profit. Here, solar PV and battery energy storage systems are used along by the wind farm to exploit system profit by grasping the negative outcome of imbalance cost. Along with system profit, the focus has also been on system risk. The system risk has been calculated using the risk assessment factors, i.e., Value-at-Risk (VaR) and Cumulative Value-at-risk (CVaR). The work is performed on a modified IEEE 14 and modified IEEE 30 bus test system. The solar PV-battery storage system can supply the demand locally first, and then the remaining power is given to the electrical grid. By using this concept, the system risk can be minimized by the incorporation of solar PV and battery storage systems, which have been studied in this work. A comparative study has been performed using three dissimilar optimization methods, i.e., Artificial Gorilla Troops Optimizer Algorithm (AGTO), Artificial Bee Colony Algorithm (ABC), and Sequential Quadratic Programming (SQP) to examine the consequence of the presented technique. The AGTO has been used for the first time in the risk assessment and alleviation problem, which is the distinctiveness of this work

Development of an Enhanced Selective Harmonic Elimination for a Single-Phase Multilevel Inverter with Staircase Modulation

A low device switching frequency is recommended for the operation of multilevel inverters (MLIs) to achieve reduced switching losses. Selective harmonic elimination (SHE) and total harmonic distortion (THD) minimization are the two primary switching angle estimation methodologies for low-frequency modulation control. In this regard, a new generalized condition has been developed in this paper for the SHE technique. This original condition will give an output voltage with improved THD in comparison to the conventional SHE technique, while achieving its primary objective of eliminating the specific harmonic content from the output voltage. The proposed condition has been formulated by estimating the error associated with the staircase waveform and the desired sinusoidal output at the fundamental frequency. An infinite harmonic count has been considered for the evaluation of the quality of output, to obtain an accurate THD value without any underestimation. The proposed technique is analyzed, and its critical features are studied in Simulink. The effectiveness of the present work has been also validated by the experimental results

An Economic Risk Analysis in Wind and Pumped Hydro Energy Storage Integrated Power System Using Meta-Heuristic Algorithm

Due to the restructuring of the power system, customers always try to obtain low-cost power efficiently and reliably. As a result, there is a chance to violate the system security limit, or the system may run in risk conditions. In this paper, an economic risk analysis of a power system considering wind and pumped hydroelectric storage (WPHS) hybrid system is presented with the help of meta-heuristic algorithms. The value-at-risk (VaR) and conditional value-at-risk (CVaR) are used as the economic risk analysis tool with two different confidence levels (i.e., 95% and 99%). The VaR and CVaR with higher negative values represent the system in a higher-risk condition. The value of VaR and CVaR on the lower negative side or towards a positive value side indicates a less risky system. The main objective of this work is to minimize the system risk as well as minimize the system generation cost by optimal placement of wind farm and pumped hydro storage systems in the power system. Sequential quadratic programming (SQP), artificial bee colony algorithms (ABC), and moth flame optimization algorithms (MFO) are used to solve optimal power flow problems. The novelty of this paper is that the MFO algorithm is used for the first time in this type of power risk curtailment problem. The IEEE 30 bus system is considered to analyze the system risk with the different confidence levels. The MVA flow of all transmission lines is considered here to calculate the value of VaR and CVaR. The hourly VaR and CVaR values of the hybrid system considering the WPHS system are reported here and the numerical case studies of the hybrid WPHS system demonstrate the effectiveness of the proposed approach. To validate the presented approach, the results obtained by using the MFO algorithm are compared with the SQP and ABC algorithms’ results

A Joint Scheduling Strategy for Wind and Solar Photovoltaic Systems to Grasp Imbalance Cost in Competitive Market

The integration of renewable energy sources with active thermal power plants contributes to the green environment all over the globe. To achieve maximum reliability and sustainability of the renewable-thermal hybrid system, plentiful constraints need to be considered for minimizing the situation, which creates due to the unpredictable nature of renewable energy. In wind integrated deregulated system, wind farms need to submit the power generation scenario for future days to Independent System Operator (ISO) before the date of operation. Based on their submitted bid, ISO scheduled the power generation from different generating stations, including thermal and renewable. Due to the uncertain nature of the wind flow, there is always a chance of not fulfilling the scheduling amount of power from the wind farm. This violation in the market can impose an economic burden (i.e., imbalance cost) on the generating companies. The solar photovoltaic cell can be used to decrease the adverse economic effects of unpredicted wind saturation in the deregulated system. This paper presents consistent, competent, and effective operating schemes for the hybrid operation of solar PV and wind farms to maximize the economic profit by minimizing the imbalance cost, which occurs due to the mismatch between the actual and predicted wind speed. Modified IEEE 14-bus and modified IEEE 30-bus test systems have been used to check the usefulness of the proposed approach. Three optimization techniques (i.e., Sequential Quadratic Programming (SQP), Smart Flower Optimization Algorithm (SFOA), Honey Badger Algorithm (HBA)) have been used in this work for the comparative study. Bus Loading Factor (BLF) has been proposed here to identify the most sensitive bus in the system, used to place wind farms. The SFOA and HBA optimization technique has been used first time in this type of economic assessment problem, which is the novelty of this paper. The Bus Loading Factor (BLF) has been introduced here to identify the most sensitive bus in the system. After implementing the work, it has been seen that the operation of the solar PV system has reduced the adverse effect of imbalance cost on the renewable integrated deregulated power system