• Energy Research

Abstract This paper presents a methodology to minimize the total cost of buying power from different energy producers including renewable energy generations particularly within the context of a microgrid. The proposed idea is primarily based on the controlled operation of a battery energy storage system (BESS) in the presence of practical system constraints coupled with our proposed cost optimization algorithm. The complex optimization problem with constraints has been solved using the well-known concept of dynamic programming. The methodology has been assessed using actual power and price data from six different power generation sites and cost reduction has been calculated for a number of BESSs by varying their energy and power capacities. Twofold benefits of the proposed methodology lie in minimizing the total cost along with the constraint-based efficient operation of the BESS. Simulation results depict that the given power demand at a particular region can be fulfilled properly at all times using a BESS and multiple power generation.

This paper intends to discuss the combined economic emission hydrothermal scheduling [Energy Convers. Manage. 51 (2010) 561–571], while an improved Quantum-behaved Particle Swarm Optimization (QPSO) method has been utilized to solve the proposed optimization problem. The economic/environmental hydrothermal scheduling problem is a non-convex optimization problem, which is subjected to several equality and inequality constraints. These constraints relate to the power balance and the technical limitations of thermal and cascaded hydro units. The solutions obtained in the original paper [1], do not satisfy the constraint on the power produced by hydro generating units that should be positive at any time of the scheduling period. In this regard, this paper indicates this inaccuracy occurred in the original paper [1], and solves the problem using epsilon-constraints technique and lexicographic optimization to present the solutions satisfying all the constraints of the mentioned problem.

This paper proposes a method for short term security-constrained unit commitment (SCUC) for hydro and thermal generation units. The SCUC problem is modeled as a multi-objective problem to concurrently minimize the ISO's cost as well as minimizing the emissions caused by thermal units. The non-linearity of valve loading effects is linearized in the presented problem. In order to model the SCUC problem more realistically, this paper considers the dynamic ramp rate of thermal units instead of the fixed rate. Moreover, multi-performance curves pertaining to hydro units are developed and the proposed SCUC problem includes the prohibited operating zones (POZs). Besides, the model of SCUC is transformed into mixed integer linear programming (MILP) instead of using mixed integer non-linear programming (MINLP) which has the capability to be solved efficiently using optimization software even for real size power systems. Pareto optimal solutions are generated by employing lexicographic optimization as well as hybrid augmented-weighted e-constraint technique. Furthermore, a Fuzzy decision maker is utilized in this paper to determine the most preferred solution among Pareto optimal solutions derived through solving the proposed multi-objective SCUC problem. Eventually, the proposed model is implemented on modified IEEE 118-bus system comprising 54 thermal units and 8 hydro units. The simulation results reveal that the solutions obtained from the proposed technique in comparison with other methods established recently are superior in terms of total cost and emission output.

Demand-side management (DSM) includes various persuasive measures to improve the use of energy; thus, it has been studied from various perspectives in the literature. Nowadays, the context of productivity has an important role in the evaluation of the electrical energy systems. Accordingly, this paper presents a platform to comprehensively contemplate the DSM from the productivity perspective that features its three aspects. First, the widespread indices of DSM are manifestly redefined, and a plenary index of DSM is introduced, reflecting both energy and investment productivity. Second, the modification of energy efficacy and consumption pattern is discussed, considering a general categorization of DSM modalities based on the pertaining index of each branch. Third, a modified model of demand response (DR) is developed to implement seven DR strategies in the smart microgrids. The simulation results demonstrate that the load factor can improve up to 8.12% with respect to the normal consumption pattern. Moreover, the load factor can be further enhanced at least by 4.22% in comparison with the customary model.

This paper discusses the short-term combined economic emission scheduling of hydrothermal power systems with cascaded reservoirs [Energy Convers Manage. 50 (2009) 97–104], while differential evolution algorithm has been employed to solve the optimization problem. However, this problem is subjected to several constraints like the generation limitations of generating units. The solutions reported in the original paper do not satisfy the constraint on the initial and final reservoir storage volumes of hydro units as well as the constraint on the generated power by such units, which should be positive at any time of the scheduling period. Thus, this paper intends to prove this issue and solve the problem using Normal Boundary Intersection (NBI) method, in order to propose the correct solutions satisfying all the constraints of the short-term hydrothermal scheduling problem.

This article proposed a new model for reconfiguration and distributed generation (DG) allocation in the distribution network by considering network loss reduction and power quality improvement. The objective function aims to minimize losses and improve power quality indices by using the new antlion optimizer (ALO) algorithm. The proposed reconfiguration has been investigated on an unbalanced IEEE 33-bus grid with and without DG resources and capacitors. In this study, a branch exchange technique with an optimization method is used to determine the best network arrangement. Simulation results are implemented in different scenarios. In each of the scenarios, power quality indices and network losses before and after the optimization are compared. The results indicate that by using the proposed method, the rate of power quality indices and the losses in the case study are reduced. Also, the results of this study were compared with the results of sample studies. The results show that ALO has better performance with the goal of power loss reduction.

Abstract Current power networks and consumers are undergoing a fundamental shift in the way traditional energy systems were designed and managed. The bidirectional peer-to-peer (P–P) energy transactions pushed passive consumers to be prosumers. The future smart grid or the internet of energy (IoE) will facilitate the coordination of all types of prosumers to form virtual power plants (VPP). The paper aims to contribute to this growing area of research by accumulating and summarizing the significant ideas of the integration of distributed prosumers and small-scale VPP to the internet of energy (IoE). The study also reports the characteristics of IoE in comparison to the traditional grid and offers some valuable insights into the control, management and optimization strategies of prosumers, distributed energy resources (DERs) and VPP. As bidirectional P–P energy transaction by the prosumers is a crucial element of IoE, their management strategies including various demand-response approach at the customers’-levels are systematically summarized. The integration of DERs and prosumers to the VPP considering their functions, infrastructure, type, control objectives are also reviewed and summarized. Various optimization techniques and algorithm, and their objectives functions and the types of mathematical formulation that are used to manage the DERs and VPP are discussed and categorized systematically. Finally, the factors which affect the integration of DERs and prosumers to the VPP are identified.

Abstract This study deals with the inaccuracies occurred in short-term hydrothermal scheduling using different methods published in Energy Conversion and Management journal. The reported solutions do not meet the hydroelectric power generation limits. In this regard, the generated power ought to be positive during all hours of scheduling, while the hydroelectric power generation of plant 3 has negative amounts.

The global warming problem together with the environmental issues has already pushed the governments to replace the conventional fossil-fuel vehicles with electric vehicles (EVs) having less emission. This replacement has led to adding a huge number of EVs with the capability of connecting to the grid. It is noted that the presence of such vehicles may introduce several challenges to the electrical grid due to their grid-to-vehicle and vehicle-to-grid capabilities. In between, the power quality issues would be the main items in electrical grids highly impacted by such vehicles. Thus, this study is devoted to investigating and reviewing the challenges brought to the electrical networks by EVs. In this regard, the current and future conditions of EVs along with the recent research works made into the issue of EVs have been discussed in this study. Accordingly, the problems due to the connection of EVs to the electrical grid have been discussed, and some solutions have been proposed to deal with these challenges.