Abstract

In low latitudes, ice storage air conditioners (ISACs) have been widely used to cool while locally responding to the distribution network demand. However, due to the lack of the direct cold energy exchange between ISACs, the cooling load could only be shifted on the time scale instead of the space scale, resulting in an unsatisfactory regulation result. To address the above problem, this article proposes a novel collaborative expansion planning scheme for integrated cooling and power system. Firstly, to increase the regulation flexibility, a novel cold energy supply system is designed, where ice making stations and trucks are used to produce and deliver ices to multiple terminal ISACs. On this basis, taking the capacity of the wind turbines (WTs), large ice makers (LIMs), and trucks as configuration decisions, an optimal expansion planning model is established considering wind generation uncertainties. This model is converted into a classic mixed-integer second-order cone programming (MISOCP) problem using linear techniques, and efficiently solved by the Benders decomposition method. Finally, Shapley value method in economics is used to fairly distribute the revenues between the grid operator (GO) and ISAC owners. Simulation studies on IEEE 14-node distribution network indicate the proposed expansion model is effective and beneficial.

Highlights

  • With the awakening of energy crisis and environmental awareness, more and more renewable generation is connected to the distribution network [1]

  • The wind turbines (WTs) and a large ice makers (LIMs) as well as trucks could be invested and operated by the grid operator, ice storage air conditioners (ISACs) must participate in the integrated cooling and power system schedule

  • Where pWT and pLIM mean the investment prices of WTs, and LIMs, respectively, PiWT, PiLIM denote the configuration capacity at node i, CTruck indicates the truck sale price, r represents the interest rate, yWT, yLIM, and yTruck denotes the service lives of WTs, LIMs, and trucks, respectively. p fuel denotes the hourly fuel cost of truck driving, binary variable ij s,t means the truck driving flag from station i to station j at time t in scenario s, C Labor is the driver labor cost, ptEG represents the electricity price of external power grid, PsE,tG means the purchase power from the external grid, PsL,tS indicates the amount of load shedding, and pLS stands for the penalty price

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Summary

INTRODUCTION

With the awakening of energy crisis and environmental awareness, more and more renewable generation is connected to the distribution network [1]. Many researches have focused on the coordinated planning of the integrated electricity, heat and cooling MES, including the system strucure optimization [4,5,6], location, type, and capacity configuration of the common units [7,8,9,10,11,12,13], energy storage characteristic development [14,15,16,17], and uncertainty analysis [18,19,20]. Motivated by the existing research gaps, a novel integrated cooling and power MES expansion planning scheme for low-latitude distribution networks is proposed in this paper. The main contributions of this paper are summarized as follows: 1) A novel integrated cooling and power collaborative expansion planning framework for low-latitude distribution networks is proposed. FRAMEWORK OF EXPANSION PLANNING OF INTEGRATED COOLING AND POWER SYSTEM FOR LOWLATITUDE DISTRIBUTION NETWORKS

COLLABORATIVE EXPANSION PLANNING OF COOLING AND POWER SYSTEM
REVENUE DISTRIBUTION METHOD
C Truck r 1 r yTruck 1 r yTruck 1
CONSTRAINTS
SOLUTION ALGORITHM
BENDERS SOLUTION STAGE
RESULTS AND DISCUSSION
NUMERICAL SIMULATION RESULTS
RESULTS
COOPERATION REVENUE DISTRIBUTION
MPACT OF THE TRUCK TRASIT TIME
CONCLUSION
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