Abstract

The problem associated with economic dispatch of battery energy storage systems (BESSs) in alternating current (AC) distribution networks is addressed in this paper through convex optimization. The exact nonlinear programming model that represents the economic dispatch problem is transformed into a second-order cone programming (SOCP) model, thereby guaranteeing the global optimal solution-finding due to the conic (i.e., convex) structure of the solution space. The proposed economic dispatch model of the BESS considers the possibility of injecting/absorbing active and reactive power, in turn, enabling the dynamical apparent power compensation in the distribution network. A basic control design based on passivity-based control theory is introduced in order to show the possibility of independently controlling both powers (i.e., active and reactive). The computational validation of the proposed SOCP model in a medium-voltage test feeder composed of 33 nodes demonstrates the efficiency of convex optimization for solving nonlinear programming models via conic approximations. All numerical validations have been carried out in the general algebraic modeling system.

Highlights

  • One of the systems utilized for the purpose of improving the operation of alternative current (AC)distribution networks is battery energy storage systems (BESSs), since they generate some benefits in the networks [1,2], such as reducing losses in the electrical network, lessening operating costs, improving voltage profiles, and compensating power oscillations generated by the high variability of wind speed and solar radiation from renewable energy sources [3,4,5]

  • In order to deal with the stochastic variations of the renewable energy behavior, in this work of research, we implement the forecasting methodology reported in [15], which is based on recursive neural networks to predict the renewable power output with a length of 24 h considering as inputs humidity, pressure, time, and wind speed for wind power generation, and solar radiation, time, and temperature for a photovoltaic generation

  • These results show that only 16.67% of the tested combinatorial methods can reach the best solution for the optimal power flow problem in the 33-node test feeder

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Summary

Introduction

One of the systems utilized for the purpose of improving the operation of alternative current (AC). The convex reformulation of the classical and well-known economic dispatch problem via conic programming by applying the hyperbolic relaxation of the power balance equations, which has not previously reported in the literature pertaining to economic dispatch analyses in AC distribution networks; The validation of the positive impacts that have the usage of the apparent power capabilities in batteries to reduce the energy purchasing costs in conventional sources, which allows additional improvements of about 2% when it comes to classical unity power factor scenarios for the operation of BESSs. It is important to mention that the numerical results reported in this research, in general, coincide with the large-scale nonlinear solvers available in the GAMS software.

Nonlinear Programming Formulation
Objective Function
Set of Constraints
Second-Order Cone Programming Reformulation
Dynamic Active and Reactive Power Control
Test Systems
Renewable Energy Behavior
Battery Information
Computational Validations
Simulations Cases
Numerical Performance of the 33-Node Test Feeder
Objective
Numerical Performance of the 69-Node Test Feeder
Complementary Analysis
Method
Conclusions and Future Works
Findings
Objective function value vi
Full Text
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