Optimal Allocation of Energy Storage Systems for Voltage Control in LV Distribution Networks

This paper deals with the problem of cost-optimal operation of smart buildings that integrate a centralized HVAC system, photovoltaic generation and both thermal and electrical storage devices.Building participation in a Demand-Response program is also considered. The proposed solution is based on a specialized Model Predictive Control strategy to optimally manage the HVAC system and the storage devices under thermal comfort and technological constraints. The related optimization problems turn out to be computationally appealing, even for large-scale problem instances. Performance evaluation, also in the presence of uncertainties and disturbances, is carried out using a realistic simulation framework.

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“…The characterization of the storage system based on rechargeable batteries used in this paper is as follows (see, e.g., [27,28]…”

Section: Electrical Storage Modelmentioning

confidence: 99%

An integrated model predictive control approach for optimal HVAC and energy storage operation in large-scale buildings

et al. 2019

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“…These studies are focused on minimizing the annual investment cost, operation and maintenance, installation cost, power loss cost, interruption cost and maximizing the utility, reliability, safety, stability, consumption of renewable energy. Most of these studies use optimal power flow (OPF), genetic algorithm (GA), particle swarm optimisation (PSO) and block coordinate decent (BCD) algorithms programmes [61][62][63][64][65][66][67][68][69][70][71]. The constraints considered in these studies are based on conventional power system constraints, cost constraints, ESS constraints and renewable energy constraints.…”

Section: Optimum Location Of Smes In Wpgs Integrated Gridmentioning

confidence: 99%

Superconducting magnetic energy storage for stabilizing grid integrated with wind power generation systems

Mukherjee

Rao

2018

J. Mod. Power Syst. Clean Energy

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Due to interconnection of various renewable energies and adaptive technologies, voltage quality and frequency stability of modern power systems are becoming erratic. Superconducting magnetic energy storage (SMES), for its dynamic characteristic, is very efficient for rapid exchange of electrical power with grid during small and large disturbances to address those instabilities. In addition, SMES plays an important role in integrating renewable sources such as wind generators to power grid by controlling output power of wind plant and improving the stability of power system. Efficient application of SMES in various power system operations depends on the proper location in the power system, exact energy and power ratings and appropriate controllers. In this paper, an effort is given to explain SMES device and its controllability to mitigate the stability of power grid integrated with wind power generation systems.

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“…The methodology is based on: (a) a GA bi-level optimization method that reduces the voltage fluctuations caused by the PV penetration through optimally configuring the BESS and (b) a linear programming (LP) routine that determines the dispatch strategy for each BESS unit generated by the GA as to guarantee minimum daily coincident peak demand in an IEEE 8500-Node test feeder. 8 also discussed the problem of finding optimal configuration of BESS in radial low voltage networks in order to prevent over and under voltages. 9 demonstrated a multi-objective optimization approach for optimal sizing and siting of energy storage systems in distribution networks based on reduction in peak power and losses while minimizing the investment cost.…”

Section: Introductionmentioning

confidence: 99%

Optimal placement and sizing of photovoltaics and battery storage in distribution networks

Chedid

Sawwas

2019

Energy Storage

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A two‐step optimization approach is proposed to study the effects of adding a battery energy storage system (BESS) to a distribution network incorporating renewable energy sources. In this article, the first step finds the optimal size and placement of the photovoltaic (PV) arrays that lead to the lowest possible losses, cost and voltage deviation from the reference bus, while the second step starts by performing another optimization in order to find the optimal size and placement of the BESS that lead to a further reduction in the same objectives. The optimized Grid‐PV and Grid‐PV‐BESS configurations are subjected to a time domain power flow so that the annual energy losses and voltage profile of each bus can be observed. The article provides a novel formulation that treats the problem as a multi‐objective optimization and uses the Genetic Algorithm technique to reach optimal configuration in both steps. An Institute of Electrical and Electronic Engineers 13‐Bus test feeder is used to demonstrate the usefulness of the proposed technique.

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Optimal Allocation of Energy Storage Systems for Voltage Control in LV Distribution Networks

Cited by 138 publications

References 25 publications

An integrated model predictive control approach for optimal HVAC and energy storage operation in large-scale buildings

An integrated model predictive control approach for optimal HVAC and energy storage operation in large-scale buildings

Superconducting magnetic energy storage for stabilizing grid integrated with wind power generation systems

Optimal placement and sizing of photovoltaics and battery storage in distribution networks

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