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In the power system, the economic dispatch (ED) problem is the key issue, while fossil fuels cause environmental pollution. The allocation of power generation is included in the actual economic load dispatch issue of power generation for reducing the operating cost. This creates the economic load dispatch issue, a large-scale, highly nonlinear controlled optimization issue. The major issue in the power systems is the loss, fuel cost, and emission. The existing algorithms can optimize the parameters mentioned above, but it is not much better. Hence, this paper presents the multi-objective multi-verse optimization (MOMVO) for the dynamic load dispatch problem. The dynamic load dispatch issue is evaluated by cost and emission evaluation with hybrid renewable energy Sources (RES). Here, the proposed algorithm generates the thermal, photovoltaic (PV) and wind power values, reducing the cost and emission values. The unit's power generation is the foremost aim of dynamic economic load dispatch (DELD) to meet the load demand while sustaining various operational constrictions; the generation's total cost is reduced. The MVO algorithm is applied to nonlinear DELD issues and is a reliable and robust optimization algorithm. The introduced scheme is implemented and tested over three test systems, such as 6, 10, and 11 generating units. The implementation is performed on the MATLAB R2016a platform, and the performance results are evaluated based on with and without valve-point loading (VPL). Finally, VPL produced better solutions than the without VPL case. [ABSTRACT FROM AUTHOR]

The main object of this article is to examine to what extent the concept of generations applies to the Polish 68ers and their oral testimonies. To provide a deepened analysis of this problem, I divided my text into two major parts. In the first one, I drew both methodological and historical context of the '68 generation controversy, including, for example, long-lasting discussions about the advantages and limitations of using "generation" as an analytical tool in social science and humanities. The second part of my article consists of the original analysis of oral testimonies -- gathered mostly by myself -- of the participants of the so-called "March events" from Łódź. Here I seek to find answers to such questions, for example, as: to what extent does the dominant narrative about the Polish '68 generation apply to more provisional circumstances? Is Mannheim's distinction between "generation" and "generation unit" a possible solution to a problem of different, and in many cases even opposing, generations rooted in the same historical events? [ABSTRACT FROM AUTHOR]

This study proposes a single-leader-multi follower game to model a bilevel retail market among an aggregator and multiple microgrids to determine the optimal demand scheduling of the consumer, as well as price-power bidding strategies of microgrids in an interactive scheme. In the lower level, microgrids which include several distributed energy resources and energy storage units, compete with each other and offer the optimal energy-price bids such that their individual profit is maximised, while energy dispatch among their energy resources is also determined. Then, in the upper-level problem, the aggregator leads the competition taking advantages of demand-side management including interruptible and shiftable loads to minimise its energy payment for real-time pricing of generation units. By means of Karush–Kuhn–Tucker optimality condition, the bilevel optimisation of Stackelberg game is reduced to a single-level mixed-integer linear programming problem. Moreover, impact of microgrids’ integration on the retail market clearance mechanism, as well as required incentives for such integration has been discussed in a separate scenario.

The operation of a standalone microgrid is often optimised by the central controller that decides the set-points of the local controllers of the distributed generators. However, the optimised set-points may not remain optimal for a longer period due to the variability of loads and renewable generations. This study proposes a technique for readjusting the dispatch of the suitable generation units, between the optimisations carried out by the central controller, to support load changes. To this end, the potential field concept has been suggested to be adopted by the loads to select the appropriate generation units. The decision is made based on different criteria, such as their cost, reliability, emission, and power loss. This process requires low computational efforts, and thus, can act and make decisions immediately. This is valid as far as the change in the loads is not substantial. For a change above a predetermined level, the microgrid's central controller steps in to optimise the system. The central controller also performs the regular optimisation periodically to retune the whole system and reconfirm the optimal operation. The performance of the proposal has been evaluated by numerical analysis and validates the success and efficacy of the proposal. [ABSTRACT FROM AUTHOR]

Using different types of generation systems in ships, which are known as all‐electric ships, can play a key role in increasing economic benefits in the long term. On the other hand, electrical energy storage systems (EESSs) provide flexibility for supporting the electrical load of ships in the presence of renewable energy sources and the other generation units. Since power demands of a ship are not limited to an electrical load, combined heat and power (CHP) units can be considered as backup units for heat‐only units in addition to their economic and environmental advantages. In this study, new optimal power management is presented to handle a generation scheduling problem of a cruise ship for 12 h time intervals. In this regard, this method is based on the Lagrangian relaxation approach, a subset of ɛ‐constraint approaches, and the use of marginal cost to determine the performance of EESS in each time interval by taking all the constraints into account. The capability of the proposed algorithm is analysed by simulation results of a cruise ship, including conventional, CHP, EESS and heat‐only units, in order to achieve minimum operation cost with a short runtime. [ABSTRACT FROM AUTHOR]

During recent years, allocating the network losses to loads and generation units based on network transactions is an important issue in the power industry. This study presents an appropriate method to allocate the network losses to loads and generation units according to their network transactions. This method is appropriate and faster than other loss allocation techniques and does not consider unreasonable assumptions in the loss allocation process. This method explicitly assigns the network losses according to individual transactions, and this leads to allocate the network losses among all network transactions. This approach is based on the share of the loads and generation units on active and reactive power flows passing through the lines according to transactions. The implementation of the method on large networks is simple and fast. To approve the performance of the presented method, the proposed loss allocation technique has been applied to a three‐bus case study system and the IEEE 14‐bus test system. Also, several different transaction modes are used to show the performance of the presented method for transmission loss allocation based on transactions. [ABSTRACT FROM AUTHOR]

During the past few years, due to the growth of electric power consumption, generation costs as well as rises in the level of greenhouse gases efficiency bring special focus on distributed generation. Developing distributed generation resources, especially renewable energy resources, is one of the safest ways to solve such problem. These resources have been decentralised by being installed close to the houses producing few kilowatts. Therefore, there are no losses in transmission lines and provide response for demand. Based on their benefits, the use of such energy resources should be developed in the future, but its management and optimal use is a major challenge. This has become one of the main concerns ofenergy systems researchers. In the current study, an innovative model is provided as a strategic management. It is intended to optimise the operation in smart homes consisting of generation units such as a wind turbine, solar panels, storages, and un/controllable loads. The main objective of this optimisation management is to maximise microgrid profitability for 24 h. The overall results of the model proved that the profit of microgrid increased significantly.

A huge motivation has recently made on microgrid (MG) financial issues, aimed to investigate the contribution of MG operator (MGO) and private investor to reach an optimal operational strategy. Motivating the private investors to contribute in an energy production, is a considering benefit sharing factor by MGO to satisfy both of MGO and private investor. In this study, a reliability‐constrained optimisation approach is presented to calculate the number and size of MG system components. To this aim, planning problem is solved in two cases; full available state and state with considering random outage of units. Furthermore, all uncertainties of generation units are considered in the problem formulation. Non‐sequential Monte Carlo method is used to generate all scenarios. The proposed model simultaneously optimises two objectives, namely the benefits of MGO. The two‐stage heuristic method is used to solve the objective function. In the first stage, by utilising genetic algorithm, the solution to form the Pareto optimal front is found. In the second stage, to select the trade‐off solution among obtained Pareto solutions, the fuzzy satisfying method has been used. Simulations are carried out in two cases, with and without considering the share of a private investor of MGO's benefit, i.e. β. [ABSTRACT FROM AUTHOR]

Operation flexibility is a prerequisite to ensure the success of a power market operation. Due to the variable generation mix, generation units that are flexible to meet the challenge of ramping and provide operation reserve are important in today's system operations. Generators participating in frequency regulation and other ancillary services might lose energy market revenue due to reserved margins, thus regulation performance should be evaluated and paid for. The actual value of operation flexibility is dependent on the system characteristics and the market mechanism. Using the information available in energy management system and combined cycle power plants, this study proposes a simple and practical method to estimate the variant fuel cost increase of combined cycle units to provide frequency regulation service in an island power system. Based on actual operation data, analysis results testify the fact that the efficiency of the combined cycle units is reduced at lower loads and the units are subjected to different fuel cost increases at distinct operation configurations. The proposed method is justifiable and applicable for assessing variant costs incurred in providing energy system flexibility. [ABSTRACT FROM AUTHOR]

In electrical power system, economic load dispatch is a generic operation for optimal sharing of generation units to meet the system load. With the rapid development of the renewable infrastructure and wide encouragement for green energy have emerged hybrid generating systems in power systems. However, there continuous ever‐increasing production is creating challenges as well as implicating economic factor also in operation. A collective cost function is considered with the conventional thermal generators along with the consideration of renewable energy sources to envisage the economic factor. For these renewable sources, like wind and solar, the proportional cost, their uncertainty and variability by overestimation and underestimation cost are considered. To achieve this economic day‐ahead scheduling, dynamic operation in time scale of 1 h interval is performed. The stochastic nature of wind and solar is modelled by Weibull and Beta distributions, respectively. Moreover, economic optimisation is obtained by a newly developed algorithm called improved fireworks algorithm with non‐uniform operator (IFWA‐NMO). This introduces adaptive dimension strategy, limiting mapping operator and non‐uniform operator. The effectiveness of proposed IFWA‐NMO is investigated on standard dynamic economic load dispatch (DELD) system and also employed to solve conventional DELD with wind‐solar system. [ABSTRACT FROM AUTHOR]

This paper proposes a safe reinforcement learning algorithm for generation bidding decisions and unit maintenance scheduling in a competitive electricity market environment. In this problem, each unit aims to find a bidding strategy that maximizes its revenue while concurrently retaining its reliability by scheduling preventive maintenance. The maintenance scheduling provides some safety constraints which should be satisfied at all times. Meeting the critical safety and reliability requirements when the generation units have incomplete information regarding each other's bidding strategy is a challenging problem. Bi-level optimization and reinforcement learning are state-of-the-art approaches for solving this type of problem. However, neither bi-level optimization nor reinforcement learning can handle the challenges of incomplete information and critical safety constraints. To tackle these challenges, we propose the safe deep deterministic policy gradient reinforcement learning algorithm, which is based on a combination of reinforcement learning and a predicted safety filter. The case study demonstrates that the proposed approach can yield a higher profit compared to other state-of-the-art methods while concurrently satisfying the system safety constraints. Moreover, the case study shows that the reward of the learning algorithm with incomplete information can converge to a reward of the complete information game. • Formulating generators' maintenance scheduling and bidding as a bi-level optimization. • Developing a multi-agent deep RL to obtain the maintenance scheduling and bidding. • Designing a predicted safety filter to satisfy all the safety constraints. • Converting optimization to single-level optimization and finding the NE of the game. [ABSTRACT FROM AUTHOR]

Today, many Independent System Operators (ISOs) establish programs to manipulate the reserve provided by Demand Response (DR) in ancillary service markets. In this study, Ancillary Service DR (ASDR) programs, recently introduced by Federal Energy Regulatory Commission, is integrated to an n–k Contingency Constrained Unit Commitment problem to investigate the capability of the DR Providers (DRPs), newly added ancillary market participants, in mitigating the impacts of simultaneous multiple contingencies in a power system. In the proposed model, an n–k security criterion by which power balance constraint is satisfied under any contingency state comprising simultaneous outages in generation units is investigated in the presence of the ASDR programs. Demand side reserve is supplied by DRPs, which have the responsibility of aggregating and managing customer responses to offer a bid‐quantity to the ISO. The proposed formulation is a Mixed Integer Programming problem based on primal‐dual optimisation, reported recently in literature. In addition, a detailed discussion about versatile effects of ASDR programs on n–k security criterion is presented to demonstrate the applicability of the proposed model. [ABSTRACT FROM AUTHOR]

Nowadays, the rising concern about the costs of fuel and operation of generating units in the energy control centre deserve progress of solution methodologies for the practical economic dispatch (ED) problems. ED aims to schedule the committed units' output power while satisfying practical constraints and load demand. The generator ramp rate limits, non‐convex and discontinuous nature of prohibited operating zones, non‐smooth characteristic of valve‐point effects, multi‐fuel type of generation units, transmission line losses and the large number of units in practical power plants make this problem very hard to solve. In this study, a new solution method of integrating the classical gradient‐based optimisation technique and a new enhanced simplified swarm optimisation algorithm is comprehensively presented and successfully applied to determine the feasible, robust, fast and globally or near‐globally optimal solution within a rapid timeframe for the ED problems. The simulations are carried out on four‐test systems, including 10‐, 15‐, 40‐ and 80‐units using the proposed optimisation technique in the Fortran Power Station 4.0 software. The current proposal outperforms other methods showcased in the recent state‐of‐the art literature in the area. [ABSTRACT FROM AUTHOR]

Inspired by the neighbourhood cooperation, a new discrete optimisation algorithm is proposed. The so‐called binary neighbourhood field optimisation (BNFO), utilises the attractive field of the superior neighbour and the repulsive field of the inferior neighbour. As a kind of local search, BNFO is able to deliver promising results efficiently within acceptable computational time. BNFO is applied to solve the unit commitment problem (UCP), whose objective is to minimise the operation cost of the generation units over the scheduling horizon. After numerical tests on several benchmark UCP cases, the obtained costs are less expensive compared with conventional Lagrangian relaxation, genetic algorithm, evolutionary programming, particle swarm optimisation and differential evolutionary. BNFO can converge to promising results with less computation times, especially for the large‐scale UCPs. [ABSTRACT FROM AUTHOR]

The unit commitment problem is one of the most significant and basic issues in the monitor, control, and operation of modern power systems, which has always been a subject of great concern to researchers and operators as the most extensive human-made system. Before restructuring, one of the main objectives of unit commitment problem was the minimization of the total operation cost of power plants subject to various constraints, including unit and network ones. As the privatization and restructuring process became more serious, the primary purpose of the unit commitment problem has been changed to maximizing the total profit, which led to the emergence of a new concept known as profit-based unit commitment problem. Accordingly, the maximization of the profit for generation companies, all over the studied period, is a top-priority direction. This paper presents a comprehensive overview of the profit-based unit commitment problem in restructured power systems by investigating the most important studies on this topic and providing a complete classification. It also outlines the challenges facing researchers in this field, offers new insights, and suggests future directions. • Describing a comprehensive formulation for profit-based unit commitment problem. • Presenting a complete and comprehensive overview of profit-based unit commitment problem. • Reporting the used case study systems, simulation tools, hardware, and run-time. • Briefly reviewing the fitness functions, parameter setting, convergence criterion, and the obtained profit values. • Addressing the main challenging issues regarding the mentioned problem. [ABSTRACT FROM AUTHOR]