Multi-Objective Day-Ahead Real Power Market Clearing with Voltage Dependent Load Models

2011 ◽  
Vol 12 (4) ◽  
Author(s):  
SurenderReddy Salkuti ◽  
Abhijit R Abhyankar ◽  
Pradeep R. Bijwe
Keyword(s):  
Production Cost ◽  
Cost Minimization ◽  
Power Market ◽  
Market Clearing ◽  
Real Power ◽  
Multi Objective ◽  
Load Models ◽  
Welfare Maximization ◽  
Social Welfare Maximization ◽  
Voltage Dependent

In this paper, we investigate the influence of voltage dependent load models on day ahead real power market clearing (DA-RPMC). The investigations clearly bring out the unsuitability of conventional single objectives such as production cost minimization (PCM) (or social welfare maximization (SWM)), due to reduction of load served. Hence, the multi-objective optimization is essential in this context. The paper proposes several objectives such as production cost minimization (PCM) (or social welfare maximization (SWM)), load served maximization (LSM), and Voltage Stability Enhancement Index (VSEI); which can be judiciously combined as per the needs of the operating condition. Multi-objective Strength Pareto Evolutionary Algorithm (SPEA) has been used to solve the DA-RPMC problem. The effectiveness of the proposed approach is tested on IEEE 30 bus system and the detailed simulation studies have been carried out by considering different operating conditions with voltage dependent load modeling.

Co-optimization of Energy and Demand-Side Reserves in Day-Ahead Electricity Markets

2015 ◽  
Vol 16 (2) ◽  
pp. 195-206 ◽  
Author(s):  
S. Surender Reddy ◽  
A. R. Abhyankar ◽  
P. R. Bijwe
Keyword(s):  
Demand Response ◽  
Electricity Markets ◽  
Optimization Problem ◽  
Demand Side ◽  
Load Modeling ◽  
Multi Objective ◽  
Welfare Maximization ◽  
Social Welfare Maximization ◽  
Strength Pareto Evolutionary Algorithm ◽  
Voltage Dependent

Abstract This paper presents a new multi-objective day-ahead market clearing (DAMC) mechanism with demand-side reserves/demand response (DR) offers, considering realistic voltage-dependent load modeling. The paper proposes objectives such as social welfare maximization (SWM) including demand-side reserves, and load served error (LSE) minimization. In this paper, energy and demand-side reserves are cleared simultaneously through co-optimization process. The paper clearly brings out the unsuitability of conventional SWM for DAMC in the presence of voltage-dependent loads, due to reduction of load served (LS). Under such circumstances multi-objective DAMC with DR offers is essential. Multi-objective Strength Pareto Evolutionary Algorithm 2+ (SPEA 2+) has been used to solve the optimization problem. The effectiveness of the proposed scheme is confirmed with results obtained from IEEE 30 bus system.

Solving realistic reactive power market clearing problem of wind-thermal power system with system security

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Sravanthi Pagidipala ◽  
Sandeep Vuddanti
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Power Market ◽  
Operating Conditions ◽  
Objective Functions ◽  
Market Clearing ◽  
Load Model ◽  
Multi Objective ◽  
Reactive Power Market ◽  
Single Objective

Abstract This paper proposes a security-constrained single and multi-objective optimization (MOO) based realistic security constrained-reactive power market clearing (SC-RPMC) mechanism in a hybrid power system by integrating the wind energy generators (WEGs) along with traditional thermal generating stations. Pre-contingency and post-contingency reactive power price clearing plans are developed. Different objective functions considered are the reactive power cost (RPC) minimization, voltage stability enhancement index (VSEI) minimization, system loss minimization (SLM), and the amount of load served maximization (LSM). These objectives of the SC-RPMC problem are solved in a single objective as well as multi-objective manner. The choice of objective functions for the MOO model depends on the load model and the operating condition of the system. For example, the SLM is an important objective function for the constant power load model, whereas the LSM is for the voltage-dependent/variable load model. The VSEI objective should be used only in near-critical loading conditions. The SLM/LSM objective is for all other operating conditions. The reason for using multiple objectives instead of a single objective and the rationale for the choice of the appropriate objectives for a given situation is explained. In this work, the teaching learning-based optimization (TLBO) algorithm is used for solving the proposed single objective-based SC-RPMC problem, and a non-dominated sorting-based TLBO technique is used for solving the multi-objective-based SC-RPMC problem. The fuzzy decision-making approach is applied for extracting the best-compromised solution. The validity and efficiency of the proposed market-clearing approach have been tested on IEEE 30 bus network.

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