Optimization of Network-Load Interaction With Multi-Time Period Flexible Random Fuzzy Uncertain Demand Response

Huayi Wu,Ping Dong,Mingbo Liu

doi:10.1109/access.2019.2940721

Abstract

This paper represents a network-load interaction optimization framework integrated multi-time period flexible random fuzzy uncertain demand response (DR) model, which involved shifting of loads’ operation time and uncertain response to the price signal. The network-load interaction is to optimize load profile and network topology under the guidance of electricity price at the aim of achieving the economic and secure operation of the distribution network and at the same time satisfying the consumers’ satisfaction. This framework is a two-level framework, which includes the price-based DR level to minimize the daily load variance and maximize the customers’ satisfaction, and the reconfiguration level to minimize the network reconfiguration cost and power unbalancing. Firstly, the price-based DR level determines the price and the load profile subject to the multi-time period flexibility and uncertainties of the DR. Then, the reconfiguration level optimizes the network configuration topology according to the load profile and feeds the results back to the price-based DR level. This network-load interaction optimization model is tackled by the proposed multi-objective self-adaptive particle swarm (SAPSO) optimization algorithm. The proposed network-load interaction optimization model is applied to the IEEE33-bus distribution system and a real system. The results show that this model is efficient to solve the network economic operation and load profile optimization problem simultaneously.

Highlights

Electricity market with demand response (DR) has gained attention, which enables two - way flows of electricity and information to create a widely distributed automated energy delivery network [1]
This paper proposes a network - load interaction optimization framework that involves two optimization levels, the price - based DR level and the reconfiguration level, which subject to multi - time period flexible random fuzzy uncertain DR
Considering the multi-time period flexible random fuzzy uncertainty of DR, this paper proposes a two-level networkload interaction optimization framework for optimize the operation of the distribution system

Summary

INTRODUCTION

Electricity market with DR has gained attention, which enables two - way flows of electricity and information to create a widely distributed automated energy delivery network [1]. H. Wu et al.: Optimization of Network-Load Interaction With Multi-Time Period Flexible Random Fuzzy Uncertain DR the impact of the price - based DR on market clearing and locational marginal prices of the power system. These references do not take the random fuzzy uncertain characteristics of load demand response into account They tackle with the DR information as an effect factor in the reconfiguration instead of cooperating the DR optimal model and the reconfiguration optima. This paper proposes a network - load interaction optimization framework that involves two optimization levels, the price - based DR level and the reconfiguration level, which subject to multi - time period flexible random fuzzy uncertain DR. Compared with the previous work, this two - level network - load interaction optimization framework firstly considers the feedback loop between the flexible uncertain DR model under the electricity market environment and the reconfiguration optimal operation. The consumption dt can be estimated by equation (3) if the p0t and dt0 are given

MULTI-TIME PERIOD UNCERTAIN DEMAND RESPONSE MODEL

1) OBJECTIVE FUNCTION

RECONFIGURATION OPTIMIZATION ALGORITHM

CASE STUDY

Findings

CONCLUSION