# Experimental Validation of Peer-to-Peer Distributed Voltage Control System
## 1 Introduction
A Distributed optimization-based control system is characterized by the complete absence of a central controller. Every RES is considered to be an autonomous control agent where all agents are equally important. To overcome the absence of the central decision making controller, the agents communicate with each other in a P2P fashion. With communication, they are able to make the correct control decisions in every particular situation. Failure of one controller in distributed control system does not lead to an inability to control the system. The work in [9] describes fundamental concepts and approaches within the field of distributed control systems that are appropriate to power engineering applications. Centralized control systems often suffer from serious computation, robustness, and communication issues for power networks with many controllable devices. Distributed control is perhaps the only viable strategy for such networks. Nevertheless, these centralized systems can achieve high performance. In a centralized control system, there is only one controller, which receives all necessary data, and based on all available information the multi-objective controller can achieve a globally optimal performance. An interesting question is whether P2P distributed control systems can achieve a comparable good performance to the centralized one. Most research studies appearing in the literature attempt to answer this question by means of simulators, as reviewed in [10; 11; 12]. For instance, in [13] a gradient descent method has been used to distribute a centralized optimization problem over agents participating in the voltage control, a push-sum gossip algorithm is implemented to enable P2P communication between the agents. Simulink (MATLAB, version R2016a, The MathWorks, Inc, Natick, MA, USA) has been used to model a 5-bus microgrid and to validate the performance of the proposed algorithm. In [14], a dual decomposition technique is used to design a P2P-based voltage control system. A backward/forward sweep power flow calculation algorithm, coded in MATLAB, has been used to model a low voltage, 62-bus, semiurban feeder and to test the ability of the algorithm to control the voltage effectively within limits. In [15], openDSS simulator (version 2017, EPRI, Palo Alto, CA) has been used to validate the effectiveness and robustness of a fully distributed voltage control algorithm that has been developed based on the Alternating Direction Method of Multipliers and consensus protocol (consensus ADMM). The same method has been used in [16] and validated using CVX software (version 2014, CVX Research, Inc., Stanford, CA, USA) (convex programming). Distributed Energy Storage Systems (DESSs) are used in [17] to control the voltage profiles of active distribution networks in a distributed way. The proposed methodology is based on network partitioning strategy. Linear programming and voltage sensitivities are used to define the areas for which each DESS maximizes its influence. To study the performance of the proposed algorithms, MATLAB has been used to code the algorithms and to model an IEEE 123 nodes test system. The concept of network partitioning is also used in [18] to implement a decentralized voltage control system that regulates reactive power of photovoltaic (PV) inverters. The proposed methodology of [18] is based on Lyapunov theory and has been validated via Matlab/Simulink environment. The concepts of transactive energy (TE), home microgrids (H-MGs) and coalition formation are used in [19] to design an algorithm for optimal use of electrical/thermal energy distribution resources, while maximizing profit of H-MGs. The algorithm is based on an optimization problem in which an objective function is based on economic strategies, distribution limitations and the overall demand in the market structure. MATLAB was used to solve the optimization problems of the proposed algorithm.