Economic Dispatch Research Papers - Academia.edu (original) (raw)

2025, 2022 IEEE 6th Conference on Energy Internet and Energy System Integration (EI2)

The problem of heat and electricity pricing in combined heat and power (CHP) systems regarding the time scales of electricity and heat, as well as thermal energy quality, is studied. Based on the asynchronous coordinated dispatch of the CHP system, an energy-grade double pricing mechanism is proposed. Under the pricing mechanism, the resulting merchandise surplus of the heat system operator (HSO) at each heat dispatch interval can be decomposed into interpretable parts and its revenue adequacy can be guaranteed for all heat dispatch intervals. And the electric power system operator (ESO)'s resulting merchandise surplus is composed of non-negative components at each electricity dispatch interval, also ensuring its revenue adequacy. In addition, the effects of different time scales and co-generation are analyzed in different kinds of CHP units' pricing. Index Terms-Combined heat and power system, marginal pricing, thermal energy quality, time scale.

2025, arXiv (Cornell University)

2025, African Scientific Reports

Economic Dispatch Problem (EDP) is a power system optimization problem that is required to be solved accurately using an efficient optimization technique. Hybrid optimization solutions have provided better optimum results than either deterministic or non-deterministic optimization methods. The hybridization of both Particle Swarm Optimization (PSO) and Bat Algorithm (BA) to for Hybrid Particle Swarm Bat Algorithm (H-PS-BA) optimization technique for solving EDP of Nigerian 21 thermal generating station power system was carried out in this work. The result of the work revealed that H-PS-BA performed better and gave the best optimal generation costs when compared to other methods such as PSO, Interior Point Method and BA.

2025

Due to the extensive integration of distributed renewable energy resources, the Active Distribution Network (ADN) faces numerous challenges, including, for example, renewable energy curtailment and overloading. This paper proposes a collaborative optimization control method for electric-vehicle battery swapping stations that mitigates the mismatching between generation and load demand in the ADN. Energy storage sharing is considered in this study, that allows stations to exchange batteries via the traffic network, and this extends the capacity of Battery-Transferable Swapping Stations (BTSSs). First, the operational principles of the energy storage shared BTSS are carefully analyzed, including external and internal control mechanisms and energy storage sharing. Subsequently, a bi-level optimization model is proposed, whereby the upper level aims to minimize the total operational cost of the ADN and the lower level seeks to maximize the benefit of each BTSS. A two-stage transactive control is introduced to decompose the bi-level situation into two stages: the day-ahead stage and the real-time stage and this facilitates easier problem-solving. Finally, an IEEE 15-node system is utilized to verify the proposed method. The results indicate that the proposed method reduces the renewable energy curtailment, power shortages, and operational costs of the ADN, while at the same time increasing the earnings of BTSSs.

2025, IFIP Advances in Information and Communication Technology

Electric vehicles (EV) offer a great potential to address the integration of renewable energy sources (RES) in the power grid, and thus reduce the dependence on oil as well as the greenhouse gases (GHG) emissions. The high share of wind energy in the Portuguese energy mix expected for 2020 can led to eventual curtailment, especially during the winter when high levels of hydro generation occur. In this paper a methodology based on a unit commitment and economic dispatch is implemented, and a hydro-thermal dispatch is performed in order to evaluate the impact of the EVs integration into the grid. Results show that the considered 10 % penetration of EVs in the Portuguese fleet would increase load in 3 % and would not integrate a significant amount of wind energy because curtailment is already reduced in the absence of EVs. According to the results, the EV is charged mostly with thermal generation and the associated emissions are much higher than if they were calculated based on the generation mix.

2025, Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a modified particle swarm optimization considering time-varying acceleration coefficients for the economic-emission load dispatch (EELD) problem. The new adaptive parameter is introduced to update the particle movements through the modification of the velocity equation of the classical particle swarm optimization (PSO) algorithm. The idea is to enhance the performance and robustness of classical PSO. The price penalty factor method is used to transform the multiobjective EELD problem into a single-objective problem. Then the weighted sum method is applied for finding the Pareto front solution. The best compromise solution for this problem is determined based on the fuzzy ranking approach. The IEEE 30-bus system has been used to validate the effectiveness of the proposed algorithm. It was found that the proposed algorithm can provide better results in terms of best fuel cost, best emissions, convergence characteristics, and robustness compared to the reported results using other optimization algorithms.

2025, Indonesian Journal of Electrical Engineering and Computer Science

In this paper, Multiobjective Cuckoo Search Algorithm (MOCSA) is developed to solve Economic Load Dispatch (ELD) problem. The main goal of the ELD is to meet the load demand at minimum operating cost by determining the output of the committed generating unit while satisfying system equality and inequality constraints. The problem formulation is based on a multiobjective model in which the multiobjective are defined as fuel cost minimization and carbon emission minimization. MOCSA is based on the inspiration from the brooding parasitism of cuckoo species in nature. Three cases are considered to test the effectiveness of the proposed technique which are fuel cost minimization, carbon emission minimization and multiobjective function with fixed weighted sum. The effectiveness of the MOCSA’s performances are illustrated through comparative study with other techniques such as Multiobjective Genetic Algorithm (MOGA) and Multiobjective Particle Swarm Optimization (MOPSO) in terms of fitnes...

2025

The classical Particle Swarm Optimization (PSO) Algorithm is very efficient and effective in solving optimization problems (both minimization and maximization). But PSO algorithm has a shortcoming of converging prematurely after getting trapped into some local optima (local optimum solution point) and considers it to be the global optima (global optimum solution point). Moreover, when we apply it to a multi-dimensional complex problem scenario, then due to some constraints it becomes nearly impossible to get out from that local optima (apparent global optima) and reach out for the global optima. Instead, all the particles starts getting converged to that apparent optimum solution. On the contrary, Simulated Annealing (SA) Algorithm can hinder the premature convergence to the local optima and diverges the particles using its strong ability of local search. Here, we propose a new hybrid algorithm of Particle Swarm Optimization (PSO) and Simulated Annealing (SA) in optimization (We app...

2025, The Journal of Object Technology

Although multiple dispatch properly solves difficult programming problems such as binary methods, the large majority of existing object-oriented programming languages still don't support it. The few languages that provide such a mechanism do so in ways that either lie outside an object-oriented modular construct (class), or possess some other limitations, such as arbitrarily choosing one of the dispatch object types as the repository for dispatch methods. This article presents a new objectoriented language mechanism for single and multiple dispatch. As a proof of concept, we will use Java as the base language. This mechanism is compatible with existing object-oriented language constructs, and provides a simple, expressive, and universal dispatch tool. Our proposal introduces a new object-oriented external dispatch mechanism, which complements the traditional object-oriented internal single dispatch mechanism. This new mechanism is applicable not only to multiple dispatch, but can also be used as an alternative to decorators and some creational design patterns. A more complete realization for external dispatch motivated the definition of a new singleton language mechanism that is also presented.

2025, TELKOMNIKA (Telecommunication Computing Electronics and Control)

This paper presents a nature-inspired meta-heuristic, called a stochastic fractal search based method (SFS) for coping with complex economic load dispatch (ELD) problem. Two SFS methods are introduced in the paper by employing two different random walk generators for diffusion process in which SFS with Gaussian random walk is called SFS-Gauss and SFS with Levy Flight random walk is called SFS-Levy. The performance of the two applied methods is investigated comparing results obtained from three test system. These systems with 6, 10, and 20 units with different objective function forms and different constraints are inspected. Numerical result comparison can confirm that the applied approach has better solution quality and fast convergence time when compared with some recently published standard, modified, and hybrid methods. This elucidates that the two SFS methods are very favorable for solving the ELD problem.

2025, International Journal of Engineering

This research is aimed to design a power system using particle swarm algorithm (PSA) and test its efficiency on a standard IEEE bus bar system. The algorithm has been modified for power generating system and successfully demonstrates and provides optimization results for six generating units . Reducion in fuel cost by distributing load among the generating units in inter connected bus bar system is the core area of this research. The losses in power transmission as well as generation are also minimized. Moreover, the PSA coding was executed using MATLAB and the graphs are shown for comparison with other optimization techniques. The results obtained using PSA were compared with other optimization techniques and PSA was found comparatively better than other techniques. PSA has been found to be reliable for power system optimization and hence suitable for practical purposes.

2025, Electric Power Components and Systems

The increase in the usage of fossil fuels for energy production has led to the extermination of natural minerals, which gives rise to the hybridization of non-renewable resources with renewable resources. The energy generation system’s integration has confiscated a new problem in load dispatch to the consumers with economic satisfaction. In this research work, hybrid optimization is proposed for the economic load dispatch formation by allocating the power in the hybrid energy sources. The PV-WT-diesel generator is used for power generation, and the search- and rescue-based emperor penguin optimization algorithm is used to allocate the power to the corresponding generation unit. The implementation is done by considering the ramp rate limit and the valve point effect. The implementation is done on the MATLAB platform for modeling the hybrid energy source and the optimization process. As a result, the combination of tri-generators has proved for a better result, costing 27248.88$/hr. At 400 MW load, inducing the emission cost of 0.012$/hr. In contrast to other methods, the fuel and emission cost is reduced to 2.66%.

2025, Serbian Journal of Electrical Engineering

Hybrid Microgrids are being widespread for power generation in remote locations. The improvement in non-conventional energy sources and rise in the price of existing electrical energy production sources led to the advancement of hybrid renewable sources. Economic characteristics of these technologies are adequately capable to include in emerging power generation. Advances and research in solar, wind and other non-conventional energy sources are required to continue for improving their performance, creating techniques for exactly forecasting their outputs and reliably integrating with other conventional sources used for generation. Economic dispatch is being taken into consideration as the optimal output of the electricity generation facilities. These are to be met as per the load at the lowest possible cost. The problem on Economic Dispatch (ED) and different technical constraints considering power balance in the network satisfying the objective are to be formulated. This paper presents a brief review on economic dispatch of hybrid microgrids.

2025, International Journal of Electrical Power & Energy Systems

The industrialization and the growth of the population are the main factors, which increase the electricity consumption. This phenomenon comes with a deep restructuring of the electricity sector. Indeed, new constraints concerning reduction of the gas emissions and the use of renewable sources are imposed. The electric networks become more and more large and complex. The grid operation appears as non-linear problems, multi-objective, having a lot of variables and constraints. Complexity arises from the problem formulation and evolutionary algorithms appear as an efficient tool for the resolution. This paper presents three problems, which are related to the electric networks. The economic environmental dispatch (EED) problem consists to minimize the fuel cost and the gas emissions. The optimal reactive dispatch (RD) consists to minimize the active losses in the transmission lines, the voltage deviations and the cost of compensation devices. Finally the active, reactive and environmental dispatch problem (ARED) consists to minimize the cost of fuel, gas emissions and the active losses in the transmission lines. To solve these problems an Improving Strength Pareto Evolutionary Algorithm (SPEA2) method is applied to the New-England Power System (39 buses, 10 thermal generators). The results demonstrate the ability of the proposed approach to find and maintain a diverse Pareto optimal solution in one single run.

2025, Jurnal Kejuruteraan

Kajian ini mengemukakan kecekapan Algoritma Pendebungaan Bunga (APB) dalam menyelesaikan penghantaran ekonomi. Penghantaran ekonomi yang terbaik bagi sesuatu sistem kuasa adalah sistem terbabit dapat menjana tenaga pada kos penjanaan yang rendah. Pengiraan bagi kos penjanaan terbabit adalah tertakluk kepada beberapa kekangan, seperti permintaan kuasa bagi keseluruhan sistem dan had penjanaan bagi setiap unit penjana dalam sistem terbabit. Selain itu, sistem itu juga perlu menghasilkan kehilangan kuasa yang rendah bagi mengurangkan kesan penghasilan pencemaran gas rumah hijau. Teknik pengoptimuman APB dikembangkan berdasarkan pemindahan debunga dari satu bunga ke bunga lain pada pokok yang sama atau pokok yang lain menggunakan pendebunga semulajadi seperti lebah madu, burung, air, atau angin. Antara kelebihan APB berbanding teknik lain adalah kesederhanaan dalam rumus pengiraan dan masa simulasi pencarian yang pantas. Algoritma yang dicadangkan telah dilaksanakan dalam dua sistem iaitu sistem IEEE 9 bas 3 penjana dan IEEE 30 bas 6 penjana. Kedua-dua sistem ini diuji dalam persekitaran Matlab. Bagi menyerlahkan kemampuan FPA, keputusan menggunakan teknik yang dicadangkan ini dibandingkan dengan teknik Pengoptimum Kupu-Kupu Api (PKA) untuk menentukan kecekapan pendekatan yang dicadangkan dalam menyelesaikan pengiriman ekonomi. PKA merupakan teknik pengoptimuman yang telah banyak digunakan dalam mencari keputusan optimum, terutamanya dalam penyelidikan kejuruteraan. Hasil simulasi menunjukkan bahawa APB berprestasi lebih baik daripada PKA dalam menentukan nilai penjanaan kuasa optimum dengan kos penjanaan yang minimum dan kadar kehilangan kuasa yang rendah.

2025, Indonesian Journal of Electrical Engineering and Computer Science

Economic dispatch (ED) is one of the many important components in a power system operation. It is designed to calculate the exact amount of power generation needed to ensure a minimum cost of generation. A power system with multiple generators should be running under an economic condition. The operating cost has to be minimised for any feasible load demand. The increase of power demand is getting higher throughout the year. Economic dispatch is used to schedule and control all output of the fossil-fuel or coal-generators to satisfy the system load demand at a minimum cost. This paper presents the Multiverse Optimisation (MVO) for solving the economic dispatch in a power system. The proposed Multiverse optimisation engine developed in this study is implemented on the IEEE 30-Bus Reliability Test System (RTS). It has five generators, all of which are denoted as the control variables for the optimisation process. To reveal the superiority of MVO, a similar process was conducted using E...

2025, Lecture Notes in Computer Science

This paper presents an Artificial Immune-based optimization technique for solving the economic dispatch problem in a power system. The main role of electrical power utility is to ensure that electrical energy requirement from the customer is served. However in doing so, the power utility has also to ensure that the electrical power is generated with minimum cost. Hence, for economic operation of the system, the total demand must be appropriately shared among the generating units with an objective to minimize the total generation cost for the system. Economic Dispatch is a procedure to determine the electrical power to be generated by the committed generating units in a power system so that the total generation cost of the system is minimized, while satisfying the load demand simultaneously. The proposed technique implemented Clonal Selection algorithm with several cloning, mutation and selection approaches. These approaches were tested and compared in order to determine the best strategy for solving the economic dispatch problem. The feasibility of the proposed techniques was demonstrated on a system with 18 generating units at various loading conditions. The results show that Artificial Immune System optimization technique that employed adaptive cloning, selective mutation and pair-wise tournament selection has provided the best result in terms of cost minimization and least execution time. A comparative study with λ-iteration optimization method and Genetic Algorithm was also presented.

2025, HAL (Le Centre pour la Communication Scientifique Directe)

In a Smart Grid context, the increasing penetration of embedded generation units leads to a greater complexity in the management of production units. In this article, we focus on the impact of the introduction of decentralized generation for the unit commitment problem (UC). Unit Commitment Problems consist in finding the optimal schedules and amounts of power to be generated by a set of generating units in response to an electricity demand forecast. While this problem have received a significant amount of attention, classical approaches assume these problems are centralized and deterministic. However, these two assumptions are not realistic in a smart grid context. Indeed, finding the optimal schedules and amounts of power to be generated by multiple distributed generator units is not trivial since it requires to deal with distributed computation, privacy, stochastic planning, ... In this paper, we focus on smart grid scenarios where the main source of complexity comes from the proliferation of distributed generating units. In solving this issue, we consider distributed stochastic unit commitment problems. We introduce a novel distributed gradient descent algorithm which allow us to circumvent classical assumptions. This algorithm is evaluated through a set of experiments on real-time power grid simulator.

2025, Engineering Applications of Artificial Intelligence

2025

The Galaxy-based Search Algorithm (GbSA) is an optimization technique developed recently by Hamed Shah-Hosseini at Shahid Beheshti University-Iran [1, 2]. GbSA is a meta-heuristic that uses a modified Hill Climbing algorithm as a local search and resembles the spiral arms of some galaxies to search the optimum. In this paper, GbSA is proposed for solving the Combined Economic and Emission Dispatch (CEED) problem which is obtained by considering both the economy and emission objectives. In this paper GbSA is tested on three generators system and its results are quite encouraging showing the good applicability of GbSA for CEED problem.

2025

Tujuan dari sistem penjadwalan alokasi daya dari unit pembangkit adalah agar konsumsi bahan bakar setiap unit generator atau meminimalkan biaya operasi dari seluruh sistem dengan menentukan daya keluaran setiap unit generator pada kondisi dibawah beban sistem. Iterasi lamda digunakan untuk menentukan output dari setiap unit generator pada PLTD Sanggeng Manokwari. Sistem operasi unit pembangkit termal, biaya bahan bakar adalah biaya yang paling besar dalam sistem pembangkitan tenaga listrik. Sehingga, salah satu strategi yang dapat digunakan untuk meminimalkan biaya bahan bakar adalah dengan melakukan sistem penjadwalan unit generator dan pembagian beban sesuai dengan pola penggunaan beban masyakarat. Data pemakaian bahan bakar pada tanggal 23 November 2015 menunjukkan total biaya bahan yang gunaka dari pukul 01.00 – 09.00 dengan metode iterasi lamda adalah Rp. 163.663.106/jam sedangkan total biaya bahan bakar dengan sistem penjadwalan oleh operator PLTD adalah Rp. 167.420.636,5/jam....

2025, International Journal of Power Electronics and Drive System (IJPEDS)

The liberalization of the energy market has led to a surge in unforeseen power exchanges, which could jeopardize the security of the power system by overloading transmission lines. Flexible AC transmission system devices (FACTSDEV) has been developed in order to improve voltage profiles, reduce losses, and solve power system instability. However, because FACTSDEV devices have such high initial costs, careful planning and ideal placement are essential to maximizing their benefits. This paper proposes a genetic algorithm-based approach to arrange multiple FACTSDEV devices in a power system optimally under N-1 contingency conditions. The IEEE standard (IEEESTD) 14 bus network is where FACTSEDV are located using this optimization technique. The study makes use of MATLAB simulations to evaluate how different FACTSDEV and their placements affect the performance of the power system. The results of the generator and line outage simulations show how FACTDEV have an impact on generation costs, system loss components, and line loss reduction. The cost-optimized placement findings for FACTSDEVs in the IEEESTD 14 bus system are satisfactory and show an improvement in generation cost and system loss component with appropriate positioning and sizing of FACTDEVs.

2025, International journal of engineering research and technology

This paper presents an economic load dispatch (ELD) model, incorporating wind power with thermal generator units.ELD is a fundamental issue that simulates optimal scheduling and dispatch of available generation by minimizing overall cost subjected to physical and functional constraints. Uncertain nature of wind results in the calculation of overestimation and underestimation. Forecasting of wind power is an issue in economic load dispatch, that is why, the wind turbine output prediction, is being done by scenario analysis method. In this, a mathematical model is used which quantifies the dispatch flexibility of thermal generation by integrating the renewable energy source (wind energy). To investigate system operations, one of the modern optimizations technique named as Particle Swarm Optimization (PSO) is being used. The results are demonstrated on the basis of calculation of overestimation and underestimation cost factor separately. The optimization problem is numerically solved for a scenario involving six thermal generators units and a wind farm.

2025

NREL prints on paper that contains recycled content.

2025, IEEE Transactions on Control of Network Systems

A partially distributed economic dispatch algorithm, which renders optimal value in fixed time with the objective of supplying the load requirement as well as the power transmission losses, is proposed in this paper. The transmission losses are modeled using Kron's B-loss formula, under a standard assumption on the values of B-coefficients. The total power supplied by the generators is subjected to time-varying equality constraints due to time-varying nature of the transmission losses. Using Lyapunov and optimization theory, we rigorously prove the convergence of the proposed algorithm and show that the optimal value of power is reached within a fixed-time, whose upper bound dependents on the values of B-coefficients, parameters characterizing the convexity of the cost functions associated with each generator and the interaction topology among them. Finally, an example is simulated to illustrate the theoretical results.

2025, IEEE Transactions on Control of Network Systems

2025, International Journal of Electrical Power & Energy Systems

Transmission dispatch is a nonlinear optimisation problem due to the nonlinearity of the power flow equations. In the open literature, linearisation of power flow that yields only the active power is used for transmission dispatch problems. The solutions obtained are unacceptable when verified in nonlinear power flow equations, especially for smart grid applications because of the instability issues that result from such formulations. This paper overcomes this limitation by proposing a model that accounts for both active and reactive power in transmission dispatch problem formulations. Furthermore, this paper develops new formulations for transmission dispatch that covers the overall spectrum of operation of a power system network based on the load duration curve rather than the single period considered in the open literature. Transmission dispatch is considered in the context of minimising active power losses in this paper. The advantage of the proposed approach is that it gives acceptable results when verified with nonlinear power flow compared to the classical approach used in transmission dispatch problems. Also, the paper demonstrates that the global set of switchable lines that can minimise the active power losses of a network is obtainable from the multi-period formulations based on the consideration of varying load levels. The results indicate that only this set of switchable lines can reduce losses and ensure the stability of a network, hence useful for smart grid applications.

2025

Increasing electrical load demand and transition from regulated to deregulated power systems caused many challenges, such as: high transmission line losses and low voltage levels. An effective control of reactive power improves voltage profile, reduces power losses and improves overall system performance. In case of abnormal operations of power systems, the transmission lines become over loaded and the voltage at buses is decreased. To solve these problems, Flexible Alternating Current Transmission Systems (FACTS) represent a promising solution. One of the important FACTS devices is Thyristor Controlled Series Compensator (TCSC). Differential Evolution (DE) algorithm is one of the recent Meta heuristic optimization algorithms. Two modifications are applied to DE algorithm to enhance its convergence characteristic. In this paper, solving the Optimal Reactive Power Dispatch (ORPD) problem considering TCSC is introduced based on Modified Differential Evolution Algorithm (MDEA). The mul...

2025, Smart Grid

In order to enhance the management level of power system operation, PJM power market operator proposed the Perfect Dispatch Evaluation Method (PDEM) in 2007. Compared to the traditional evaluation methods, PDEM incorporated the actual operation boundaries and determined a virtual "Perfect Dispatch Scheme" (PDS) from post hoc perspectives. In this case, the deviations between the actual situation and the PDS could be quantitatively analyzed. This paper further implemented the PDS into various process of power system operation, identified the critical influencing factors, and formulated the influencing mechanisms. Based on information restoration and process analysis techniques, a novel PDEM is proposed to identify the effects incurred by decision and non-decision factors, respectively. In the end, a numerical case based on real operation data is studied to testify the effectiveness of the proposed method.

2025, 2013 IEEE 7th International Power Engineering and Optimization Conference (PEOCO)

This paper proposes a hybrid differential evolution (DE) and harmony search (HS) for solving optimalpowerflow(OPF)problemwithFACTSdevicesincludingstaticVarcompensator(SVC),... more

This paper proposes a hybrid differential evolution (DE) and harmony search (HS) for solving optimalpowerflow(OPF)problemwithFACTSdevicesincludingstaticVarcompensator(SVC), thyristor-controlledseriescompensation(TCSA),andthyristor-controlledphaseshifter(TCPS).The proposedhybridDE-HSistoutilizetheadvantagesoftheDEandHSmethodstoenhanceitssearch abilityfordealingwithlarge-scaleandcomplexproblems.Theproposedmethodhasbeentestedon theIEEE30bussystemwiththevarietyofobjectivefunctionsincludingquadraticfuelcost,power loss,voltagedeviation,andvoltagestabilityindexandtheobtainedresultsfromtheproposedhybrid DE-HShavebeencomparedtothosefromotheralgorithms.Theresultcomparisonhasindicatedthat theproposedhybridDE-HSalgorithmcanobtainbettersolutionqualitythanmanyothermethods. Therefore, the proposed hybrid DE-HS method can be an efficient method for solving the OPF problemincorporatingFACTSdevices.

2025, Advances in technology innovation

This article presents an optimal energy control system that considers economic dispatch (ED) for a campus microgrid to reduce its operating cost. A newly developed crow search algorithm (CSA) is used to enforce the ED in this work. To achieve this purpose, an optimal size of distributed energy resources (DERs) in the campus microgrid is assumed. CSA is used to optimize the energy control system and find the minimum operating cost of the campus microgrid. To indicate the effectiveness of CSA, several scenarios under various load demand conditions in gridconnected and stand-alone microgrid modes are investigated in this work. According to the findings, the suggested model is capable of sufficient power supply in all scenarios and reduces the operating costs more effectively than the reference delineated in the same case. The outcomes confirm that the suggested model's performance is optimal for the energy control system of a campus microgrid.

2025

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia Elétrica

2025, Procedia Environmental Sciences

Selection and peer-review under responsibility of SUSTAIN conference's committee and supported by Kyoto University; (OPIR), (GCOE-ES), (GCOE-HSE), (CSEAS), (RISH), (GCOE-ARS) and (GSS) as co-hosts.

2025

This article presents two novel methods based on the Marine Predators Algorithm (MPA) and the Tunicate Swarm Algorithm (TSA) for solving the economic dispatch problem in the electric power system. The objective of the study is to satisfy the power system's load demand and the operational constraints while incurring the minimum possible fuel cost. The objective function of the optimization is represented as the quadratic cost functions of the generators in the system. A penalty function is also incorporated into the objective function to ensure the solutions produced by MPA and TSA do not violate the system's operational constraints. The MPA and TSA models have been implemented on two test systems with six, and fifteen generator units. To determine the effectiveness of the proposed method to solve the ED problem, the results obtained using the MPA and TSA have been compared with other methods in the literature. The results show that the MPA and TSA perform very competitively with other methods.

2025, IEEE

A critical optimization job in power system
operation is the Optimal Power Dispatch (OPD) problem, which
aims to minimize the total generation cost while meeting power
demand and system constraints. The complicated, non-linear,
and non-convex character of ELD presents difficulties for
traditional optimization techniques, especially when taking valvepoint
effects, forbidden operating zones, and the integration of
renewable energy sources into account. In order to solve the ELD
problem, this study provides an improved Grey Jackal
Optimization-Pattern Search (GJO-PS) hybrid technique.

2025

In the electric power supply systems, there exist a wide range of problems involving optimization processes. Among them, the power system scheduling is one of the most important problems in the operation and management ANY power system optimization problems including economic dispatch (ED) have noconvex characteristics with heavy equality and inequality constraints . The objective of ED is to determine an optimal combination of power output to meet the demand at minimum cost while satisfying the constraints. For simplicity, the cost function for each unit in the ED problems has been approximately represented by a single quadratic function and is solved using mathematical programming techniques .Economic load dispatch has the objective of generation allocation to the power generators such that the total fuel cost is minimized and all operating constraints are satisfied. Generally ELD is solved without accounting for transmission constraints, however, in deregulated power system environment Economic load dispatch (ELD) has the objective of generation allocation to the power generators such that the total fuel cost is minimized and all operating constraints are satisfied. Generally ELD is solved without accounting for transmission constraints, however, in deregulated power system environment. A number of traditional methods are used for solving ELD and other power system problems. During the last decade soft computing methods like particle swarm optimization (PSO),GA and lemda iteration method have been increasingly proposed for complex optimization problems. The paper reviews and compares the performance of the proposed PSO,GA and iteration method variants with traditional solver GAMS for economic dispatch on TWO standard test systems having different sizes and complexity levels. A large 38-unit power system is included for validating the results.

2025, International Journal of Electrical and Computer Engineering (IJECE)

In recent years, many works have been done in order to discuss economic dispatch in which wind farms are installed in electrical grids in addition to conventional power plants. Nevertheless, the emissions caused by fossil fuels have not been considered in most of the studies done before. In fact, thermal power plants produce important quantities of emissions for instance, carbon dioxide (CO2) and sulphur dioxide (SO2) that are harmful to the environment. This paper presents an optimization algorithm with the objective to minimize the emission levels and the production cost. A comparison of the results obtained with different optimization methods leads us to opt for the grey wolf optimizer technique (GWO) to use for solving the proposed objective function. First, the method used to estimate the wind power of a plant is presented. Second, the economic dispatch models for wind and thermal generators are presented followed by the emission dispatch model for the thermal units.Then, the p...

2025, Bulletin of Electrical Engineering and Informatics

There are two significant issues with the incorporation of smart grid technology in power system operating studies including the economic emission, unit commitment problem (UCP). Economic dispatch problem (EDP) is a UCP sub-problem which find the optimum output for a given combination of running units. When using electro-energy systems to strategically distribute the power produced by all plants, the power economic dispatch problem is especially important. Pumped storage units that have the capacity to store energy can provide spinning reserves, which will lower overall costs and emissions. The general goal of this study is to develop control and optimization algorithms that are appropriate for managing new generation electrical networks. In this research work, the economic dispatch issue in a ten-unit smart grid system is resolved using the crow search algorithm (CSA), which acts as a local optimizer of the eagle strategy (ES). The outcomes of the ES-CSA program are compared to tho...

2025, arXiv (Cornell University)

We consider the problem of minimizing the difference in the demand and the supply of power using microgrids. We setup multiple microgrids, that provide electricity to a village. They have access to the batteries that can store renewable power and also the electrical lines from the main grid. During each time period, these microgrids need to take decision on the amount of renewable power to be used from the batteries as well as the amount of power needed from the main grid. We formulate this problem in the framework of Markov Decision Process (MDP), similar to the one discussed in . The power allotment to the village from the main grid is fixed and bounded, whereas the renewable energy generation is uncertain in nature. Therefore we adapt a distributed version of the popular Reinforcement learning technique, Multi-Agent Q-Learning to the problem. Finally, we also consider a variant of this problem where the cost of power production at the main site is taken into consideration. In this scenario the microgrids need to minimize the demand-supply deficit, while maintaining the desired average cost of the power production.

2025, Mathematics

Economic Load Dispatch (ELD) is a complicated and demanding problem for power engineers. ELD relates to the minimization of the economic cost of production, thereby allocating the produced power by each unit in the most possible economic manner. In recent years, emphasis has been laid on minimization of emissions, in addition to cost, resulting in the Combined Economic and Emission Dispatch (CEED) problem. The solutions of the ELD and CEED problems are mostly dominated by metaheuristics. The performance of the Chameleon Swarm Algorithm (CSA) for solving the ELD problem was tested in this work. CSA mimics the hunting and food searching mechanism of chameleons. This algorithm takes into account the dynamics of food hunting of the chameleon on trees, deserts, and near swamps. The performance of the aforementioned algorithm was compared with a number of advanced algorithms in solving the ELD and CEED problems, such as Sine Cosine Algorithm (SCA), Grey Wolf Optimization (GWO), and Earth ...

2025, International Transactions on Electrical Energy Systems

For accurate economic dispatch solution, it is necessary to periodically estimate the parameters of fuel cost function. This paper proposes an improved differential evolution algorithm for computing the optimal parameters of fuel cost functions for thermal power plants. A new mutation strategy is suggested to enhance convergence rate and improve solution quality of original differential evolution. The proposed approach is examined on different test systems with several generator cost curve models involving smooth and nonsmooth/ nonconvex functions. The results using the proposed approach are compared to those available in recent literature. The results show the efficiency of the proposed estimation approach for obtaining accurate fuel cost parameters without any restriction on the mathematical model of the generator cost curve.

2025

Economic power dispatch (EPD) is one of the main tools for optimal operation and planning of modern power systems. To solve effectively the EPD problem, most of the conventional calculus methods rely on the assumption that the fuel cost characteristic of a generating unit is a continuous and convex function, resulting in inaccurate dispatch. This paper presents the design and application of efficient adaptive differential evolution (ADE) algorithm for the solution of the economic power dispatch problem, where the non-convex characteristics of the generators, such us prohibited operating zones and ramp rate limits of the practical generator operation are considered. The 26 bus benchmark test system with 6 units having prohibited operating zones and ramp rate limits was used for testing and validation purposes. The results obtained demonstrate the effectiveness of the proposed method for solving the non-convex economic dispatch problem.

2025, International Journal of Electrical Power & Energy Systems

Power plants usually operate on the strategy of economic dispatch (ED) regardless of emissions produced. Environmental considerations have become one of the major management concerns. Under these circumstances, the alternative strategy of environmental/economic dispatch (EED) is becoming more and more desirable for not only resulting in great economical benefit, but also reducing the pollutants emission. Based on the literature survey, few attempts have been made at considering valve-point effects for the realistic environmental/economic dispatch (EED) problem. This paper proposes a new efficient hybrid differential evolution algorithm with harmony search (DE-HS) to solve the multiobjective environmental/ economic dispatch (EED) problems that feature nonsmooth cost curves. The proposed approach combines in the most effective way the properties of differential evolution (DE) and harmony search (HS) algorithms. To enhance the local search capability of the original DE method, the fresh individual generation mechanism of the HS is utilized. Numerical results for three case studies have been presented to illustrate the performance and applicability of the proposed hybrid method. The comparative results with some of the most recently published methods confirm the effectiveness of the proposed strategy to find accurate and feasible optimal solutions for practical EED problems.

2025

Power system scheduling problems like unit commitment and power dispatch methods have a vital role in the operation of electric power industry. Nowadays, global electricity consumption is growing rapidly while the supply of fossil fuels is dwindling and the concern about global warming is increasing. Therefore, power utilities are being forced to use hybrid power systems that consist of both conventional and renewable generation units. Optimum scheduling of such hybrid systems with Energy Storage Facilities (ESF) can ensure a consistent level of renewable power penetration throughout the operation periods, and thus, an economic, clean and energy efficient power generation can be achieved. Modelling of power system scheduling for hybrid power systems with ESF, optimization of such system’s scheduling and applications of scheduling under different scenarios are the main scopes of this thesis. The importance and applicability of this research are analyzed and illustrated by MATLAB simu...

2025, Nigerian Journal of Technology

This paper aims to solve the economic dispatch problem of the 28-bus Nigerian power system using genetic algorithm. The power flow solution of the network is first obtained using Newton-Raphson technique; the solution thus obtained is used to determine the loss coefficients of the network. For this study, a forecasted load demand of 2000MW will be considered, MATLAB's genetic algorithm optimization toolbox is used to obtain the optimum generation level of each unit. The optimal power output of each scheduled generating units was obtained after 200 iterations at a minimal generation cost of ₦136,370.205/hr. A power loss of 11.32MW in the network was also obtained using Kron's loss formula.

2025, IEEE Transactions on Components, Hybrids, and Manufacturing Technology

.4bstruct-Signature analysis is used to characterize lot dispatch priority schemes in wafer fabrication, a complex manufacturing operation. A number of idealized dispatch schemes are evaluated using a comprehensive assessment crilerion. The production system analyzed in tliis paper is large in comparison to previous studies on manufacturing scheduling. Real dispatch schemes depend strongly on the characteristics of human implementation. Signature analysis provides the basis for measuring organizational performance by comparing formal dispatch schemes with each other and with actual dispatch schemes used in wafer fabrication. W AFER FABRICATION is the set of processes which result in an array of integrated circuits fabricated on the surface of a silicon wafer. Wafer fabrication is a relatively new manufacturing process, and it has developed is own manufacturing culture. In the current state of technology, wafer fabrication areas (fabs) are partially automated and typically operate with large inventories (queues) at each work area. A common problem is deciding which lot or batch of wafers is to be processed next. The solution is a system of dispatching wherein priorities are assigned to wafer lots. These dispatch schemes are implemented by area supervisors and shift managers. Clearly, the dispatch scheme used can have a strong impact on the operation of the wafer factory (fab). Thus, comparisons of dispatch-system effectiveness are valuable. These comparisons may be obtained by simulation and signature analysis . Simulation enables modeling the effect of chosen dispatch priority systems on fab operations. A series of simulation runs can be used to construct a fab signature. A signature consists of a trio of graphs displaying inventory, cycle time, throughput trade-offs for varying lot start rates and can be used to assess operating efficiency. Analysis and comparison of signatures for different dispatch schemes provides an effective evaluation of different ,operations policies. Dispatch schemes are a key element in wafer fab operations because the integrated circuit manufacturing process requires key work areas to be used multiple times. In particular, the masking area of the fab may be required to perform as many as fifteen successive masking operations to fabricate a microcomputer chip. A given wafer, thus, visits the masking area fifteen t&es before it is completed. As a result, different process steps in the same processing sequence are actually competing Manuscript

2025, 2015 North American Power Symposium (NAPS)

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2025, IJSES

This study investigates the application of two novel meta-heuristic algorithms, Sand Cat Swarm Optimization (SCSO) and Starfish Optimization Algorithm (SFOA), to address the Renewable Energy-based Economic Load Dispatch (REB-ELD) problem. The primary objective is to minimize the overall fuel expense (OFE) of a 10-Thermal Power Unit (TPU) system by optimizing power allocation for load demands of 2500 MW and 2600 MW, considering renewable energy integration and multiple fuel options. Results demonstrate that SCSO consistently outperformed SFOA, exhibiting superior performance in minimizing objective function evaluations (OFE), achieving faster convergence, and demonstrating greater stability. Specifically, SCSO showed lower OFE value fluctuations across 50 trials and achieved optimal OFE values more rapidly than SFOA for both load demand levels. Furthermore, the average and maximum OFE values obtained by SCSO were lower than those of SFOA, indicating higher efficiency. These findings suggest that SCSO provides a more efficient and effective solution for optimizing power allocation in REB-ELD problems.

2025, VUBETA

The increasing global demand for electric power presents significant challenges for power utilities, as they must balance the need for reliable and sustainable power generation with the goal to minimize generation costs. This challenge has led to studying Economic Load Dispatch (ELD), which aims to optimize power generation at minimal fuel costs. This paper presents a comprehensive review of several primary techniques used in solving ELD problems, including traditional methods such as the Lambda Iteration, Gradient, and Newton-Raphson techniques, as well as modern optimization methods like Genetic Algorithm (GA), Simulated Annealing (SA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Sine Cosine Algorithm (SCA), and Gravitational Search Algorithm (GSA). The paper also provides a comparative analysis using tables and chart in section three outlining the advantages, disadvantages, and limitations of each technique discussed in section two. Additionally, this review examines the applications of these techniques on IEEE test systems in various studies, highlighting their effectiveness on practical utility making it easier for researchers to make a choice in selecting a technique for their ELD problem.