Conventional Power Production Research Articles

Monolithic design of self-adaptive CMOS converter and robust event-triggered consensus control for integration of multi-renewable energy sources with battery storage system

Recently, integrating renewable energy sources (RESs) has been one of the most effective ways to overcome the power shortage problems due to the cumulative load demand, which cannot be covered using conventional power production. DC-DC converters with a wide voltage conversion range are highly important when integrating RESs to achieve voltage matching. In recent years, many large-scale improvements have been made to the DC-DC converters to improve reliability, effectiveness, flexibility, modularity, and cost-effectiveness. This study investigates the feasibility of integrating RESs and designing the most effective structure using complementary metal-oxide semiconductors (CMOS) for DC-DC converters. A novel monolithic CMOS buck converter with an adaptive sensing feedback system (ASFS) circuit is proposed for renewable integrated systems. The proposed converter based on ASFS provides a wide range of conversion voltages, low cost, and reliability. It depends on the pulse-width modulation (PWM) technique with a voltage-control duty-cycle (VCDC) circuit. The proposed multi-input DC-DC converter is tested to integrate three RESs to form an integrated hybrid system. The proposed converter is built to integrate the PV, wind turbine (WT), wave energy source, and battery energy storage system (BESS). The proposed DC-DC converter is tested to adjust the output voltage of the RESs at 12 V with a load current of 2.4 A to facilitate the integration process. The results show the success of the proposed converter in maintaining the output voltage at 12 V, with maximum efficiency of the CMOS buck DC-DC converter reaching 96.25 % over a wide input voltage range from 15 V to 35 V. Moreover, the maximum peak-peak ripple over the output voltage reaches 600 mV at the maximum input voltage of 35 V. A control method-based event-triggered consensus algorithm has been proposed to regulate the system voltage and ensure active power sharing in the microgrid system. The controller's settling time and rise time have been measured, and a robustness analysis has been performed based on the connections and disconnections of DGs and the impact of faults.

Application of the Slime Mould Algorithm on the Bi-Objective Environmental Economic Dispatch Problem

This paper investigates the performance of one of the latest metaheuristic swarm-based approaches called Slime Mould Algorithm (SMA). SMA is used here to solve the static bi-objective constrained Economic Emission Dispatch (EED) problem in the presence of renewable energy sources while considering the Valve-Point Effects (VPE). The SMA approach is applied to indicate the adequate optimal solutions for operating the committed thermal units under different operational constraints. The sought optimal solutions are the midpoint between cost saving and pollutant gas emission reduction. This study also examines the influence of integrating renewable energy sources (wind and solar) into the conventional power production network. SMA technique is applied on 3- and 6-unit IEEE test systems in several case studies. The simulation numerical results indicate that SMA has a high efficiency and a better performance compared to known state-of-the-art algorithms. The proposed approach was programmed and simulated in MATLAB.

Silica Nanoparticle Formation from Supercritical Geothermal Sources

Silica precipitation from high-enthalpy, depressurized supercritical fluids is investigated to determine the best method for accessing the scaling potential as a function of time, position and fluid composition. The most relevant knowledge application is for geothermal sources where the wells are drilled closed to magma and the temperature gradients in the rock are very high. The power potential per well for such a system is large compared to conventional geothermal power production, but several knowledge gaps, among them mineral precipitation from produced fluids, limit commercial use. For the high-enthalpy supercritical well fluid used as a base case in this review, conventional methods for reducing the silica content before it enters a turbine limit the power output. Knowledge of the particle-number density, size and time scales of growth in different depressurization scenarios, along with the silica solubility, kinetics and morphology, is essential to handle deposits and avoid scaling in inconvenient parts of the power plant. Experimental data on the precipitation of silica from highly supersaturated superheated steam are scarce, and it is known that the kinetics of precipitation in steam differ from those of liquid water. We argue that to quantify the number of solids in the depressurized supercritical fluid and superheated steam, dividing the process into three separate but dependable mathematical steps is a reliable approach: (1) the nucleation of nanocolloids, (2) growth by agglomeration, and (3) deposition onto a surface.

Optimal bidding strategy of a gas-fired power plant in interdependent low-carbon electricity and natural gas markets

This work presents a bi-level optimization framework to determine the optimal bidding strategies for a strategic gas-fired power plant, exerting market power in interdependent pool-based electricity and natural gas markets, under a carbon emission trading scheme (CETS). The upper-level problem aims at maximizing the profits of the strategic player, while at the lower-level problem, the day-ahead electricity and natural gas markets are cleared sequentially, considering the provision of carbon emission allowances for conventional power producers and high penetration of wind power generation. The bi-level formulation is initially recast into a mathematical program with equilibrium constraints (MPEC), using the Karush-Kuhn-Tucker optimality conditions and duality theory, and is further reformulated into a mixed integer linear program. The proposed algorithm is applied to a Pennsylvania-New Jersey-Maryland (PJM) 5-bus power grid, incurred by transmission constraints and a single node natural gas network. Numerical simulations provide CETS-embedded electricity clearing prices and optimal bidding decisions for the strategic gas-fired power plant, under plausible power transmission congestions and natural gas prices increment scenarios.

Introduction of optimal photovoltaic and wind power balance algorithm in power systems

Since 2021, Crete has been connected to the mainland’s power system grid providing security regarding load peak demand and intra-day fluctuations. The grid provides, also, the opportunity to take full advantage of it in order to alter the island’s energy mix, making the island’s power system more climate neutral and reduce the emissions produced by conventional power production means. In the current paper, the utilization of mathematical models and a few numerical solution algorithms lead to the optimization of the power production of RES, under certain constraints regarding the system’s rejections. The approximation of each optimal solution for all three cases is satisfactory, which is, for the first two cases, an immediate result of the linear properties of the objective function that expresses the annual production of RES in each case. Those linear properties prevent each approximated solution from deviating from the problem’s feasible region, while, also, permitting the use of optimization techniques which can be easily implemented and require very little computational time. For the third case, a search algorithm has been designed and implemented, yielding accurate, yet low-precision solutions, which approximate sufficiently the optimal ones.

MANAGING THE BIOGAS PRODUCTION USING THE GREEN MARKET WASTE

In recent years, countries around the globe have concentrated on renewable energy options in consideration of the ever-increasing demand for energy, the oil prices and unpredictable supplies for conventional power production, as well as the well-known adverse effects of conventional energy source on environment and human health. Raw biogas consists primarily of methane (CH4), ammonia (NH3), carbon dioxide (CO2), water (H2O), hydrogen sulphide (H2S), nitrogen (N2) and other trace components. The present research focuses on the processing of biogas in a domestic level scale biogas digester. Anaerobic digestion process was adopted. These experimental studies have been performed on domestic level to develop optimum process for biogas generation from organic waste of green market, for the purpose different samples were collected in different seasons. Pakistan has abundant raw material in the green market. Biogas produced from this green market waste is more cost effective and environment friendly, minimizes landfill waste, mitigates carbon dioxide.

New optimized configuration for a hybrid PV/diesel/battery system based on coyote optimization algorithm: A case study for Hotan county

The main objective of this study is to present a multi-objective and optimal hybrid PV/diesel generator/ battery Renewable Energy System (HRES) to provide this reliability in the Hotan county, placed in Taklamakan Desert. This study uses the ɛ-constraint method along with a developed version of the coyote optimization algorithm to achieve the best values of the component sized to decrease the loss of load probability, CO2 emission value, and the annualized cost of the system. Sensitivity analysis also is performed to show each component’s impact on the system. The results demonstrate that the DG backup system improves the yearly cost of the system from 8347.2 $ to 9318.4 $, which shows about 10.42% increasing by increasing the fuel consumption. Here, the LLP increases from 0% to 9.19% and the CO2 emissions improve from 2531.2 kg/yr to 13257 kg/yr. Accordingly, the COE value is reduced from 0.39 $/kWh to 0.24 $/kWh over the PV penetration, reducing from 92.27% to 59.42%. This decreasing indicates that the system fuel cost has more impact than the cost of PV on the COE, which is due to the low cost required of conventional power production than the PV system. The results also indicate a noteworthy upshot on the battery storage unit size such that the size of ɛCO2 has been enhanced from 27.4 kWh to 50 kWh in the range from 7000 kg/year to 25 kg/year. The results also are compared with the PSO-based optimal system and HOMER software results to show its excellence toward them.

Demand-side management strategy in a smart home using electric vehicle and hybrid renewable energy system

The residential area represents a sector that consumes more electricity especially with the rapid urban growth and the transition towards the automation and electrification of several daily activities of human beings, namely: urban mobility and the residents’ indoor comfort. As a result, meeting this increased demand requires a proportional rise in fuel use to generate energy. This type of conventional power production has significant impacts on the environment. The eco-friendly alternative is the use of renewable energies in its distributed form on buildings. However, this solution gives rise to some issues related to energy management especially with the penetration of a new domestic device, namely: the plug-in electric vehicle. For this purpose, we propose a management system for a future household equipped with controllable electric loads and an electric vehicle equipped with a PV–Wind–Battery hybrid renewable system connected to the national grid. The proposed management system is based on a linear programming model with non-linear constraints solved with MATLAB toolboxes. The simulation is based on a database of meteorological conditions resulting from TRNSYS and processed to achieve a frequency of one hour. The system decisions provide switch control states of the connection architecture as well as the variation according to the V2H (vehicle to home), H2V (home to vehicle) and involved G2V (grid to vehicle) scenarios when grid comes into play during H2V mode.

Environmental Sustainability Framework for Plastic Waste Management—a Case Study of Bubble Tea Industry in Malaysia

Economic growth and rapid industrialisation have led to enormous increase in municipal solid waste (MSW). Lack of waste management alternatives and ineffective waste policy implementation are the major challenges for government to materialise a sustainable solid waste management framework, especially for plastic waste. Booming of the food and beverage (F&B) industry has aggravated the situation by generating more plastic waste with no economic values. Hence, this study aims to evaluate the overall environmental performance of existing and alternative waste management technologies that are available in Malaysia based on net greenhouse gas (GHG) emission in terms of carbon dioxide equivalent (kg CO2-eq) per tonne of plastic waste that are analysed through life cycle assessment (LCA) methodology. LCA result has proven that Scenario B (waste to energy (WTE) incineration) is more environmentally preferable as it had a negative net GHG emission of − 573.80 kg CO2-eq as compared to GHG emission of existing Scenario A (sanitary landfill) of 566.15 kg CO2-eq. Negative net GHG emission in WTE incineration was mainly due to higher GHG saving achieved through cleaner electricity generation as compared to conventional power production. This alternative technology was proven to have the potential to reduce the dependence on landfills and is served as the basis of environmental sustainability framework development for plastic waste management based on case study in Malaysia. This framework can be served as the baseline for the local authorities or policy makers for other plastic waste generation hotspots other than bubble tea industry to improve plastic waste management via WTE incineration.

Coordination of wind power producers with an energy storage system for the optimal participation in wholesale electricity markets

The optimal participation of wind-based power resources within electricity markets confronts serious challenges due to the inherent uncertainty of wind speed. Accordingly, these units are forced to make take-or-pay contracts that are typically lower than market-clearing prices. Hence, wind power plants are not able to obtain the maximum possible amount of profit. One of the most promising solutions to deal with this matter is the coordination of wind-based units with flexible resources like energy storage systems. Therefore, this study presents a novel offering strategy of multiple Wind Producers (WPs) coordinated with a Battery Energy Storage System (BESS) in the form of a strategic Virtual Power Plant (VPP). To this end, a bi-level programming framework is proposed in which the VPP's expected profit is maximized at the upper-level (UL) through solving a two-stage stochastic problem. At the first stage, the VPP's optimal offers to the day-ahead (DA) market are determined before the realization of stochastic variables. At the second stage, this participant's real-time (RT) imbalance cost is optimized after determining the true value of uncertain parameters. On the contrary, at the lower-level (LL), the DA market-cleaning process is performed in the presence of conventional power producers. Moreover, this article aims to calculate the amount of net power trading of the VPP's components with the market and with one another. Ultimately, to assess the effectiveness of the provided framework, a sensitivity analysis is conducted by investigating the effect of the BESS presence on the wind-based VPP's optimal operation and expected benefit.

Parametric study on the exergetic and cyclic performance of a solar-powered organic Rankine cycle coupled with a thermal energy storage and complete flashing cycle

The amount of available, nonrenewable, natural resources for power generation is continuously decreasing and a need for a sustainable alternative is becoming more paramount. A recently proposed solution for a clean, renewable, sustainable small to mid-scale power generation system is analyzed involving a solar-powered organic Rankine cycle (ORC) with an intermediate thermal energy storage (TES) and complete flashing cycle (CFC). The system has better dispatchability over conventional power production methods as well as a simplified overall plant layout. The system under consideration is thoroughly discussed in the early sections of this paper. The focus of this paper is to complete an energy and exergy analysis of each component of the system to identify locations of irreversibilities or losses and quantify them. Multiple parametric studies and performance improvements are also completed whereby optimal operating temperatures are chosen, to maximize the system’s performance. Assumptions necessary for the analyses are stated and justified with a presentation of the findings. A discussion of the parametric studies and system alterations proposes potential improvements on the system regarding reduced exergy destruction and improved overall energy and exergy efficiencies.

Free Piston Stirling Engine as a new heat recovery option for an Internal Reforming Solid Oxide Fuel Cell

Energy demand increment besides the reduction of fossil fuel resources from one side, and climate issues concerning the conventional power production methods from another side lead humanity to more efficient and cleaner power production methods. One of these methods is polygeneration microgrids based on a renewable energy source. In the present study, a combined cycle of a Free Piston Stirling Engine with a Permanent Magnet Linear Synchronous Machine was proposed as a new heat recovery option for the high-quality thermal energy of an Internal Reforming Solid Oxide Fuel Cell as electricity. Then, a Double Effect Absorption Chiller and a heat exchanger were used to recover the rest of the heat as cooling and hot water, respectively. After modeling and validating all the systems, they were combined. The results of the combined system showed 31.7% (or 40% by including cooling production of Double Effect Absorption Chiller instead of its heat consumption for efficiency calculation) of total efficiency improvement compared to the standalone Internal Reforming Solid Oxide Fuel Cell. Furthermore, the electrical efficiency of the system was improved by 14.1%.

A personal retrospect on three decades of high temperature fuel cell research; ideas and lessons learned

In1986 the Dutch national fuel cell program started. Fuel cells were developed under the paradigm of replacing conventional technology. Coal-fired power plants were to be replaced by large-scale MCFC power plants fuelled by hydrogen in a full-scale future hydrogen economy. With today's knowledge we will reflect on these and other ideas with respect to high temperature fuel cell development including the choice for the type of high temperature fuel cell. It is explained that based on thermodynamics proton conducting fuel cells would have been a better choice and the direct carbon fuel cell even more so, with electrochemical gasification of carbon as the ultimate step. The specific characteristics of fuel cells and multisource multiproduct systems were not considered, whereas we understand now that these can provide huge driving forces for the implementation of fuel cells compared to just replacing conventional combined heat and power production technology.

A Review of Energy Management Schemes using EV Batteries

The population is increasing per minute and their energy demands are growing at an alarming rate. This begs the question of how this changing demand can be sustainably satisfied. There have been many strategies that were developed over the years that help the consumers to bring down their energy bills and their usage of energy to a reasonable level, but so far there are only few strategies that focus on both the consumer side and producer side. This project involves a new strategy for energy management in which we use the charging and discharging cycles of electric vehicle batteries as storage. In conventional power production stations, the generation depends on the demand at that particular time. Hence, the generators cannot always run at maximum efficiency and this may lead to losses. We are trying to introduce a “new strategy” where each electric vehicle acts both as load and storage. The period of low and high demand can be calculated from the values that are gathered from the respective load dispatch centre. During the time of low demand, the EV will charge and store energy in its battery. When the electric vehicles are not in use, they are plugged into the EV charging facilities. During the times of high demand, the EV will discharge to the connected load leaving behind a fixed percentage of charge in the battery for emergency vehicle usage. The amount of charge that should be retained in the battery can be controlled with the help of an application which will be available in the vehicle owner’s mobile phone. This will also help in promoting the interests of the increasing population. This strategy will also help the grid to have a storage system that is cost effective.

Virtual energy storage modeling based on electricity customers’ behavior to maximize wind profit

Abstract Nowadays utilizing renewable energy resources (RES) has become one of the main features of the modern power systems. Despite the many benefits of these resources, the output power uncertainty limits RES competitive ability with the other conventional power producers. Using the energy storage system (ESS) is an effective solution to resolve the output power uncertainty problem. However, ESS remains to be an expensive technology although there are declinations in the cost in recent years. To this end, this paper utilizes demand response resources as a virtual energy storage (VES) in which incentive and discount payment are applied to convince the customers to reduce or increase their consumptions, respectively. The consumption decreasing and increasing provide functions similar to discharging and charging an ESS. Customer behavior plays an important role in designing an effective VES. So, this paper employs the concept of the utility function considering different risk aversion coefficients to model the different customers’ behavior. In the numerical Section, the proposed VES is implemented considering different customer types with different risk aversion coefficients to improve the wind generation profit in the day-ahead. From the results, as the risk aversion coefficient increases, a high incentive/discount is needed to convince the customer to participate in the VES.

Multi-objective optimisation and planning of grid-connected cogeneration systems in presence of grid power fluctuations and energy storage dynamics

In recent years, multi-generation systems (MGS) have been at the centre of attention for incorporating various energy sources and technologies to provide a reliable and sustainable energy supply. However, deciding on the most suitable configuration and optimal operation strategy of MGSs has always been a challenging issue due to the nonlinear and complex interactions between different energy converters. Cogeneration solutions offer excellent energy efficiency through the coproduced heat from the electricity generation process. This will lead to significant economic profitability compared to conventional independent heat and power production plants. This paper presents a mixed-integer quadratic based multi-objective structural design strategy for grid-connected cogeneration systems comprising combined heat and power (CHP) devices, ancillary boiler, and energy storage devices in presence of nonlinear and dynamic behaviour of the energy storage systems. The power fluctuations smoothing index (PFSI) and energy storage depreciation factor (ESDF) are defined to effectively mitigate the power grid fluctuations and extend the lifetime of the energy storage systems. Presenting three case scenarios, the obtained results demonstrate the efficacy and applicability of the developed technique and reflect the impact of the introduced factors on the optimal configuration and operation of cogeneration systems.

Service dominant logic of marketing in smart grids

This manuscript considers the smart grids through the lenses of service dominant (S-D) logic of marketing, which focuses on the service prevision rather than the traditional good dominant logic in the conventional power production. Different premises of the S-D logic have been presented and contrasted to the features of the smart grid. It has been studied that the attentions are being shifted from prioritizing cost reduction to innovation service provision methods to satisfy the demands.

USAGE OF POWER PURCHASING AGREEMENTS IN THE DEVELOPMENT OF RENEWABLE ENERGY SOURCES

The purpose of this article is to indicate power purchase agreements (PPA) as an important supporting element of the development of renewable energy sources (RES). The author states that as result of the reduction of RES investment costs, PPA become the competitive way to support the development of generation capacities in power sector. That is why the RES power procurement done by large industrial plants in many markets is competitive in relation to conventional power producers. In this situation, the PPA contracts become an instrument replacing state subsidies in securing the financing of RES investments. The more so that PPAs are concluded by more and more industrial enterprises, also increasing their geographical coverage. The article defines PPAs, their classification and the most important examples of their application.

Withholding strategies for a conventional and wind generation portfolio in a joint energy and reserve pool market: A gaming-based approach

This work considers a strategic producer whose generation portfolio consists of conventional and wind power production. Based on the single leader-follower game, a bi-level complementarity model is constructed to derive optimal capacity withholding strategies for this portfolio in a pool-based market. The upper level of the model represents the maximization of the strategic producer’s expected profits while the lower level represents the security-constrained economic dispatch conducted by the independent system operator. The market clearing scheme refers to energy-only markets optimizing jointly scheduled energy and reserves through a two-stage stochastic programming. The first stage illustrates the day-ahead market clearing and the second stage illustrates the balancing market clearing taking into consideration the wind generation uncertainty. With the use of the Karush-Kuhn-Tacker optimality conditions the initial bi-level model is recast into a mathematical programming with equilibrium constraints model which is then reduced into an equivalent mixed integer linear programming using the strong duality theorem and disjunctive constraints. The proposed algorithm derives optimal scheduled thermal and wind energy as well as reserve deployments. It also provides optimal offers based on the endogenous formation of local marginal prices under network constraints and different wind energy penetration levels.

Combination of air-based high-temperature heat and power storage system with an Organic Rankine Cycle for an improved electricity efficiency

High-temperature heat and power storage technology is an electricity storage concepts recently proposed and being investigated. This technology stores electricity as high-temperature heat and then, as needed, reclaims it to co-generate heat and electricity via a conventional power production method. Based on the power block design, this technology may come in either a ‘steam-based’ or an ‘air-based’ configuration. Regardless of the configuration, this technology offers a very high overall energy efficiency (over 80%) but low power-to-power efficiency (about 32%). Relying on the fact that electricity is going to be certainly a more pricy and critical energy kind than heat in the future, the current study suggests combining the air-based high-temperature heat and power storage and an Organic Rankine Cycle together to improve the electricity production efficiency of this storage technology. The proposed combined system is thermodynamically analyzed and compared to the conventional configuration of that. The results show that this combination results in a significantly enhanced electricity efficiency, from 32% in the conventional configuration of the system to 43% in the proposed combined cycle.