M.R. Behnamfar; M. Abasi
Abstract
The present study focuses on the harris hawks optimizer. harris hawks optimization (HHO) is introduced based on population and nature patterns. The HHO algorithm imitates harris hawks attacking behavior and includes two phases called exploration and exploitation, which can be modeled with three ...
Read More
The present study focuses on the harris hawks optimizer. harris hawks optimization (HHO) is introduced based on population and nature patterns. The HHO algorithm imitates harris hawks attacking behavior and includes two phases called exploration and exploitation, which can be modeled with three strategies, 1) discovering the prey, 2) surprising attack, and 3) prey attack. The main purpose of using this type of algorithm is to optimally solve the short-term hydro-thermal self-scheduling (STHTSS) problem with wind power(WP), photovoltaic (PV), small hydro (SH) and pumped hydro storage (PHS) powr plants while considering uncertainties such as energy prices, ancillary services prices, etc, in the energy market. It will be shown how energy generation companies can use this algorithm and other algorithms and innovative methods that will be introduced in the future to achieve profit maximum with careful scheduling. It is worth mentioning that in this study, the effect of the presence and absence of two important factors, namely valve load cost (VLC) effect and prohibited operating zones (POZs) (with linear modeling) that can affect the profit of units (power plants) has been pointed out. Finally, as shown in this study, several tests perfomed on the IEEE118-bus system validate the precision and credibility of the harris hawks optimization algorithm.
M.R. Behnamfar; H. Barati; M. Karami
Abstract
optimal and economic operation is one of the main topics in power systems. In this paper, a stochastic single objective framework for GenCoʼs optimal self-scheduling unit commitment under the uncertain condition and in the presence of SH units is proposed. In order to solve this problem, a new meta-heuristic ...
Read More
optimal and economic operation is one of the main topics in power systems. In this paper, a stochastic single objective framework for GenCoʼs optimal self-scheduling unit commitment under the uncertain condition and in the presence of SH units is proposed. In order to solve this problem, a new meta-heuristic optimization technique named antlion optimizer (ALO) has been used. Some of the capabilities of the ALO algorithm for solving the optimization problems included : (1) the exploration and utilization, (2) abiding convergence, (3) capable of maintaining population variety, (4) lack of regulation parameters, (5) solving problems with acceptable quality. To approximate the simulation conditions to the actual operating conditions, the uncertainties of the energy price, spinning and non-spinning reserve (operating services) prices, as well as the renewable energy resources uncertainty, are considered in the proposed model. The objective function of the problem is profit maximization and modeled as a mixed-integer programming (MIP) problem. The proposed model is implemented on an IEEE 118-bus test system and is solved in the form of six case studies. Finally, the simulation results substantiate the strength and accuracy of the proposed model.
Power System Operation
M. R. Behnamfar; H. Barati; M. Karami
Abstract
This study addresses a stochastic structure for generation companies (GenCoʼs) that participate in hydro-thermal self-scheduling with a wind power plant on short-term scheduling for simultaneous reserve energy and energy market. In stochastic scheduling of HTSS with a wind power plant, in addition to ...
Read More
This study addresses a stochastic structure for generation companies (GenCoʼs) that participate in hydro-thermal self-scheduling with a wind power plant on short-term scheduling for simultaneous reserve energy and energy market. In stochastic scheduling of HTSS with a wind power plant, in addition to various types of uncertainties such as energy price, spinning /non-spinning reserve prices, uncertainties of RESs, such as output power of the wind power plant are also taken into account. In the proposed framework, mixed-integer non-linear programming of the HTSS problem is converted into a MIP. Since the objective of the study is to show how GenCosʼ aim to achieve maximum profit, mixed-integer programming is used here. Therefore, to formulate the MIP for the problem of HTSS with a wind power plant in the real-time modeling, some parameters like the impact of valve loading cost (VLC) that are accompanied by linear modeling, are considered. Furthermore, in thermal units, parameters such as prohibited operating zones (POZs) and different uncertainties like the energy price and wind power are included to formulate the problem more suitably. The point that is worth noting is the use of dynamic ramp rate (DRR). Also, the application of multi-functional curves (L) of hydro plants is considered when studying inter-unit scheduling. Finally, the required tests are conducted on a modified IEEE 118-bus system to verify the accuracy and methodology of the proposed method.