Optimal VAR Planning Considering Intermittent Wind Power Using Markov Model and Quantum Evolutionary Algorithm

Abstract

Techniques for distributed generations (DGs) have attracted increasing attention due to their effects on environmental sustainability and the reduction in traditional megawatt (MW) generation expansion. Wind farms are one of the DGs and have intermittent characteristics. This paper presents a method for static VAR planning considering existing wind generator voltages and transformer taps as controllers to regulate the voltage profile in a distribution system with wind farms. Wind power generations and bus loads are modeled with the Markov model. The probabilities and durations of the operation states are obtained. Through a quantum evolutionary algorithm, the cost of static VAR compensators and MW loss in the system are minimized and the operational constraints are fulfilled. The applicability of the proposed method is verified through simulations using a standalone 25-bus (Penghu) system and a 17-bus system. Index Terms-Intermittence, Markov model, quantum evolutionary algorithm, VAR planning, voltage fluctuation.

Multi-Objective Configuration Optimization of a Hybrid Energy Storage System

“…Wind power generation and its techniques have attracted increasing worldwide attention because of their effective reduction in environmental pollution, fossil fuel consumption, and the costs of overall electricity generation [1]. Technology for wind power generation system is regarded to be much more mature than that of other distributed generation systems [2].…”

Decision making of a virtual power plant under uncertainties for bidding in a day-ahead market using point estimate method

“…In [10], a short-term scheduling procedure is adopted, composed of two stages: a day-ahead scheduler for the optimization of distributed resources production during the following day, and an intra-day scheduler which adjusts the scheduling every 15 min so that the operation requirements and constraints of the distribution network are taken into account. The integration of DERs into power system operation through participating in the ancillary service markets for providing regulation, reserve services and voltage regulation are considered in [11][12][13][14][15][16][17]. In [18], the performance of customer-owned DG units is quantified from different perspectives through an uncertainty study.…”

Predictive voltage control for a distribution network with renewable energy sources

“…The voltage and reactive power control represents an optimal power flow (O PF) task whose objective is to minimize or maximize the objective and at the same time maintain constraints within the respective limits. Some examples of this approach are [3]- [4]. The OPF solves power flow equations in every iteration and thereby taking the full advantage for analyzing all security constraints.…”