Application of swarm mean-variance mapping optimization on location and tuning damping controllers

This paper introduces the use of the Swarm Variant of the Mean-Variance Mapping Optimization (MVMO-S) to solving the multi-scenario problem of the optimal placement and coordinated tuning of power system damping controllers (POCDCs). The proposed solution is tested using the classical IEEE 39-bus test system, New England test system. This papers includes performance comparisons with other emerging metaheuristic optimization: comprehensive learning particle swarm optimization (CLPSO), genetic algorithm with multi-parent crossover (GA-MPC), differential evolution DE algorithm with adaptive crossover operator, linearized biogeography-based optimization with re-initialization (LBBO), and covariance matrix adaptation evolution strategy (CMA-ES). Numerical results illustrates the feasibility and effectiveness of the proposed approach

Performance assessment of evolutionary algorithms in power system optimization problems

Due to the stochastic nature, there are several concerns on the effectiveness and robustness of evolutionary algorithms when applied to solve different kinds of optimization problems in power systems field. To address this issue, this paper provides a comparative analysis of several evolutionary algorithms based on parametric and non-parametric statistical tests. Numerical examples are based on hydrothermal system operation and transmission pricing optimization problems

Assessment of the critical clearing time in low rotational inertia power systems

The growing share of power electronic/converter interfaced generation is decreasing the total system rotational inertia. The reduced rotational inertia in the power system has important impact on the electro-mechanical processes, the power angle and frequency evolution time are quicker resulting in faster transient processes. Rapid response of the protection systems shall be applied, in order to clear the faults in the power systems. This paper aims to identify the roots/mechanism of critical clearing time reduction/deterioration by determining/analyzing the trajectories of the critical clearing time (CCT) in low rotational inertia power systems. In this paper, the equal area criterion (EAC) is used for analysis purposes. Theoretical and practical findings demonstrate the increase of the rotational inertia increases the CCT

Effect of fast acting power controller of battery energy storage systems in the under-frequency load shedding scheme

This paper presents the assessment of the effect of fast acting power (FAP) controller in the battery energy storage system (BESS) the under-frequency load shedding (UFLS) scheme. Theoretical and practical discussions about the implementation of inertia frequency control for BESS are presented in this paper. The effect of changes in the gain of the synthetic inertial on the system frequency response is investigated using time domain simulations based on DIgSILENT PowerFactory

Online estimation of equivalent model for cluster of induction generators: a MVMO-based approach

This paper presents an approach based on the hybrid variant of the mean-variance mapping optimization algorithm (MVMO-SH) for the estimation of an Equivalent Model for a cluster of induction generators (IGs) from the on-line system response to a system frequency disturbance. Numerical results, obtained by using a small-size test system, demonstrate the viewpoint and effectiveness of the proposed approach

Effects of grounding configurations on post-contingency performance of MTDC system: a 3-terminal example

The grounding system is extremely important, as it affects the performance of the MTDC system virtually in any possible mode: normal (asymmetrical operation) and abnormal operation (faults), steady-state and dynamic. The objective of this paper is to introduce a simple approach to assess the steady-state post-contingency of multi-Terminal HVDC System and uses it order to illustrate the effects of grounding configurations on steady-state post-contingency performance. A 3-terminal HVDC system is used to formulate the main theoretical framework for performance prediction on post-contingency steady-state of MTDC system as well as for demonstrative purposes

Controller to enable the enhanced frequency response services from a multi-electrical energy storage system

The increased adoption of renewable energy generation is reducing the inertial response of the Great Britain (GB) power system, which translates into larger frequency variations in both transient and pseudo-steady-state operation. To help mitigate this, National Grid (NG), the transmission system operator in GB, has designed a control scheme called Enhanced Frequency Response (EFR) specifically aimed at energy storage systems (ESSs). This paper proposes a control system that enables the provision of EFR services from a multi-electrical energy storage system (M-EESS) and at the same time allows the management of the state of charge (SOC) of each ESS. The proposed control system uses a Fuzzy Logic Controller (FLC) to maintain the SOC as near as possible to the desired SOC of each ESS while providing EFR. The performance of the proposed controller is validated in transient and steady-state domains. Simulation results highlight the benefits of managing the SOC of the energy storage assets with the proposed controller. These benefits include a reduced rate of change of frequency (ROCOF) and frequency nadir following a loss of generation as well as an increase in the service performance measure (SPM) which renders into increased economic benefits for the service provider

Risk-based DC security assessment for future DC-independent system operator

—The use of multi-terminal HVDC to integrate wind power coming from the North Sea opens de door for a new transmission system model, the DC-Independent System Operator (DC-ISO). DC-ISO will face highly stressed and varying conditions that requires new risk assessment tools to ensure security of supply. This paper proposes a novel risk-based static security assessment methodology named risk-based DC security assessment (RB-DCSA). It combines a probabilistic approach to include uncertainties and a fuzzy inference system to quantify the systemic and individual component risk associated with operational scenarios considering uncertainties. The proposed methodology is illustrated using a multi-terminal HVDC system where the variability of wind speed at the offshore wind is included

Optimal management of reactive power sources in far-offshore wind power plants

This paper introduces a new approach for the optimal management of reactive power sources, which follows a predictive optimization scheme (i.e. day-ahead, intraday application). Predictive optimization is based to the principle of minimizing the real power losses, as well the number of On-load Tap Changer (OLTC) operations for 24 time steps ahead. The mixed-integer nature of the problem and the restricted computing budget is tackled by using an emerging metaheuristic algorithm called Mean-Variance Mapping Optimization (MVMO). The evolutionary mechanism of MVMO is enhanced by introducing a new mapping function, which improves its global search capability. The effectiveness of MVMO (i.e. fast convergence and robustness against randomness in initialization and factors used in evolutionary operations) and the achievement of optimal grid code compliance are demonstrated by investigating the case of a far-offshore wind power plant, interconnected with HVDC link

Risk-based DC security assessment for future DC-independent system operator

—The use of multi-terminal HVDC to integrate wind power coming from the North Sea opens de door for a new transmission system model, the DC-Independent System Operator (DC-ISO). DC-ISO will face highly stressed and varying conditions that requires new risk assessment tools to ensure security of supply. This paper proposes a novel risk-based static security assessment methodology named risk-based DC security assessment (RB-DCSA). It combines a probabilistic approach to include uncertainties and a fuzzy inference system to quantify the systemic and individual component risk associated with operational scenarios considering uncertainties. The proposed methodology is illustrated using a multi-terminal HVDC system where the variability of wind speed at the offshore wind is included