J. Salehi; F.S. Gazijahani; A. Safari
Abstract
Executing interruptible loads (ILs) can be significantly effective for optimal and secure operation of power systems. These ILs can aid the operators not only to increase the reliability of the power supply but also to reduce the procurement costs of the whole system. Therefore, determining the optimal ...
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Executing interruptible loads (ILs) can be significantly effective for optimal and secure operation of power systems. These ILs can aid the operators not only to increase the reliability of the power supply but also to reduce the procurement costs of the whole system. Therefore, determining the optimal location and capacity of ILs for a given incentive rate is of great interest to distribution companies. To do so, in this paper simultaneous allocation and sizing of ILs, wind turbines (WT), photovoltaic (PV) and capacitors have been done in the radial distribution network for different demand levels and subsequently the optimal value of compensation price for the ILs has been determined. Given the probabilistic nature of load, wind and solar generation as well as the price of energy at the pool, we have also proposed a stochastic model based on fuzzy decision making for modelling the technical constraints of the problem under uncertainty. The objective functions are technical constraint dissatisfaction, the total operating costs of the Distribution Company and CO2 emissions which are minimized by NSGA2. To model the uncertainties, a scenario-based method is used and then by using a scenario reduction method the number of scenarios is reduced to a certain number. The performance of the proposed method is assessed on the IEEE 33-node test feeder to verify the applicability and effectiveness of the method.
Distribution Systems
P. Salyani; J. Salehi
Abstract
The reliability of distribution networks is inherently low due to their radial nature, consequently distribution companies (DisCos) usually seek to improve the system reliability indices with the minimum possible investment cost. This can be known as system-oriented reliability planning (SORP). However, ...
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The reliability of distribution networks is inherently low due to their radial nature, consequently distribution companies (DisCos) usually seek to improve the system reliability indices with the minimum possible investment cost. This can be known as system-oriented reliability planning (SORP). However, there can exist some customers that are not satisfied by their reliability determined by adopting the SORP and they may be eager to have a higher level of reliability. Therefore, other planning in addition of SORP is required to concern the customer viewpoint reliability. This paper introduces the customer-oriented reliability planning (CORP) in medium voltage network which is an innovative approach in the context of load point reliability. To this end, first a SORP is conducted to improve the distribution system reliability index. Then the strategy is revised and the CORP is adopted by DisCo considering involving the results obtained in SORP and the customers that have declared to reduce their expected energy not supplied (EENS). Since the surplus investment cost stem from the planning revision is received from the requestor customers, CORP can provide a proper and acceptable mechanism to fairly allocate the surplus cost to those customers. Furthermore, this problem is studied under the probabilistic nature of distribution network. Simultaneous placement of distributed generators (DGs) and automatic sectionalizing switches is implemented too with a new defined load shedding mechanism in order to enhance the reliability level for both mentioned planning frameworks.
Distribution Systems
R. Afshan; J. Salehi
Abstract
This paper proposes a novel hybrid Monte Carlo simulation-genetic approach (MCS-GA) for optimal operation of a distribution network considering renewable energy generation systems (REGSs) and battery energy storage systems (BESSs). The aim of this paper is to design an optimal charging /discharging scheduling ...
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This paper proposes a novel hybrid Monte Carlo simulation-genetic approach (MCS-GA) for optimal operation of a distribution network considering renewable energy generation systems (REGSs) and battery energy storage systems (BESSs). The aim of this paper is to design an optimal charging /discharging scheduling of BESSs so that the total daily profit of distribution company (Disco) can be maximized. In this study, the power generation of REGSs such as photovoltaic resources (PVs) and the network electricity prices are studied through their uncertainty natures. The probability distribution function (PDF), is used to account for uncertainties in this paper. Also, the Monte Carlo simulation (MCS) is applied to generate different scenarios of network electricity prices and solar irradiation of PVs. Optimal scheduling of BESSs can be performed by genetic algorithm (GA). In this paper, firstly, the charging and discharging state of BESSs (positive or negative sign of battery power) is determined according to the variable amount of the electricity prices and power produced from PVs, which have been obtained from the Monte Carlo simulation. Then by using the GA, optimal amount of BESSs is determined. Therefore, a hybrid MCS-GA is used to solve this problem. Numerical examples are presented to illustrate the optimal charging/discharging power of the battery for maximizing the total daily profit.
Dynamics
H. Shahsavari; A. Safari; J. Salehi
Abstract
This paper studies the theory and modeling manner of solid oxide fuel cell (SOFC) into power network and its effect on small signal stability. The paper demonstrates the fundamental module, mathematical analysis and small signal modeling of the SOFC connected to single machine infinite bus (SMIB) system. ...
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This paper studies the theory and modeling manner of solid oxide fuel cell (SOFC) into power network and its effect on small signal stability. The paper demonstrates the fundamental module, mathematical analysis and small signal modeling of the SOFC connected to single machine infinite bus (SMIB) system. The basic contribution of the study is to attenuate the low frequency oscillations by optimal stabilizers in the presence of SOFC. To optimize the performance of system, fuzzy logic-based power system stabilizer (FLPSS) is exploited and designed by particle swarm optimization (PSO) technique. To ensure the effectiveness of the proposed optimal stabilizers, the simulation process takes in three scenarios of operating conditions. The effectiveness of proposed PSO based FLPSS on the oscillations in the power system, including SOFC is extensively demonstrated through time-domain simulations and by comparing FLPSS with the results of other stabilizers approaches.
