An Energy Management System for PV Sources in Standalone and Connected DC Networks Considering Economic, Technical, and Environmental Indices

This research proposes an efficient energy management system for standalone and grid-connected direct current (DC) distribution networks that consider photovoltaic (PV) generation sources. A complete nonlinear programming model is formulated to represent the efficient PV dispatch problem while taking three different objective functions into account. The first objective function corresponds to the minimization of the operational costs with respect to the energy purchasing costs at terminals of the substation, including the maintenance costs of the PV sources. The second objective function is the reduction of the expected daily energy losses regarding all resistive effects of the distribution lines. The third objective function concerns the minimization of the total emissions of CO (Formula presented.) into the atmosphere by the substation bus or its equivalent (diesel generator). These objective functions are minimized using a single-objective optimization approach through the application of the Salp Swarm Algorithm (SSA), which is combined with a matrix hourly power flow formulation that works by using a leader–follower operation scheme. Two test feeders composed of 27 and 33 nodes set for standalone and grid-connected operation are used in the numerical validations. The standalone grid corresponds to an adaptation of the generation and demand curves for the municipality of Capurganá, and the grid-connected system is adapted to the operating conditions in the metropolitan area of Medellín, i.e., a rural area and a major city in Colombia. A numerical comparison with three additional combinatorial optimizers (i.e., particle swarm optimization (PSO), the multiverse optimizer (MVO), and the crow search algorithm (CSA)) demonstrates the effectiveness and robustness of the proposed leader–follower optimization approach to the optimal management of PV generation sources in DC grids while considering different objective function indices. © 2022 by the authors

Optimal integration of solar photovoltaic generation in distribution networks to minimize the total annual operating costs by applying the black widow algorithm

El problema de ubicación y dimensionamiento óptimo de fuentes fotovoltaicas (PV) en sistemas eléctricos de distribución es estudiado en este artículo mediante la aplicación del algoritmo de optimización de la viuda negra (BWOA). Este problema es de naturaleza no lineal entera mixta y se aborda mediante una estrategia de optimización del tipo maestro-esclavo. En la etapa maestra el BWOA define la ubicación y el tamaño de los generadores PV mediante una codificación discreta-continua, y con esta información la etapa esclava (flujo de potencia para distribución) determina las variables eléctricas del sistema, con las cuales se evalúa la función objetivo y las restricciones del problema. Como función objetivo se considera la minimización de los costos anuales de operación y mantenimiento del sistema sumado con los costos totales de compra de energía en la red eléctrica para un período de planificación de 20 años. Los resultados numéricos en los sistemas IEEE de 34 y 85 nodos demuestran que con la metodología de optimización propuesta es posible reducir alrededor del 27 % de los costos operativos anuales en ambos sistemas con la ubicación óptima de tres fuentes fotovoltaicas. Comparaciones con metodologías metaheurísticas y exactas reportadas en la literatura especializada, confirman la eficiencia y robustez de la metodología propuesta.The problem of the optimal location and sizing of photovoltaic (PV) sources in electrical distribution systems is addressed in this article through the application of the black widow optimization algorithm (BWOA). This problem is of mixed-integer nonlinear nature and is addressed by a master-slave type optimization strategy. In the master stage, the BWOA defines the location and size of the PV generators through discrete-continuous coding, and with this information, the slave stage (power flow for distribution) determines the electrical variables of the system, with which is evaluated the objective function and the constraints of the problem. As an objective function, the minimization of the annual costs of operation and maintenance of the system is considered, added to the total costs of purchasing energy in the electrical network for a planning period of 20 years. The numerical results in the IEEE 34- and IEEE 85-node systems show that with the proposed optimization methodology it is possible to reduce around 27 % of the annual operating costs in both systems with the optimal location of three photovoltaic sources. Comparisons with metaheuristics and exact methodologies reported in the specialized literature confirm the efficiency and robustness of the proposed methodology

An Energy Management System for PV Sources in Standalone and Connected DC Networks Considering Economic, Technical, and Environmental Indices

This research proposes an efficient energy management system for standalone and grid-connected direct current (DC) distribution networks that consider photovoltaic (PV) generation sources. A complete nonlinear programming model is formulated to represent the efficient PV dispatch problem while taking three different objective functions into account. The first objective function corresponds to the minimization of the operational costs with respect to the energy purchasing costs at terminals of the substation, including the maintenance costs of the PV sources. The second objective function is the reduction of the expected daily energy losses regarding all resistive effects of the distribution lines. The third objective function concerns the minimization of the total emissions of CO2 into the atmosphere by the substation bus or its equivalent (diesel generator). These objective functions are minimized using a single-objective optimization approach through the application of the Salp Swarm Algorithm (SSA), which is combined with a matrix hourly power flow formulation that works by using a leader–follower operation scheme. Two test feeders composed of 27 and 33 nodes set for standalone and grid-connected operation are used in the numerical validations. The standalone grid corresponds to an adaptation of the generation and demand curves for the municipality of Capurganá, and the grid-connected system is adapted to the operating conditions in the metropolitan area of Medellín, i.e., a rural area and a major city in Colombia. A numerical comparison with three additional combinatorial optimizers (i.e., particle swarm optimization (PSO), the multiverse optimizer (MVO), and the crow search algorithm (CSA)) demonstrates the effectiveness and robustness of the proposed leader–follower optimization approach to the optimal management of PV generation sources in DC grids while considering different objective function indices