scholarly journals Community Microgrid Scheduling Considering Network Operational Constraints and Building Thermal Dynamics

2017 ◽  
Author(s):  
Guodong Liu ◽  
Thomas B. Ollis ◽  
Bailu Xiao ◽  
Xiaohu Zhang ◽  
Kevin Tomsovic
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Operating Cost ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Temperature Deviation ◽  
Thermal Dynamics ◽  
Electricity Cost ◽  
Voltage Deviation ◽  
Operational Constraints

This paper proposes a Mixed Integer Conic Programming (MICP) model for community microgrids considering the network operational constraints and building thermal dynamics. The proposed multi-objective optimization model optimizes not only the operating cost, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point, but also several performance indices, including voltage deviation, network power loss and power factor at the Point of Common Coupling (PCC). In particular, the detailed thermal dynamic model of buildings is integrated into the distribution optimal power flow (D-OPF) model for the optimal operation. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of the proposed model and significant savings in electricity cost with network operational constraints satisfied.

Optimal Scheduling Method of Controllable Loads in DC Smart Apartment Building

2015 ◽  
Vol 16 (6) ◽  
pp. 579-589 ◽  
Author(s):  
Tsubasa Shimoji ◽  
Hayato Tahara ◽  
Hidehito Matayoshi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu
Keyword(s):  
Power Flow ◽  
Residential Buildings ◽  
Heat Pumps ◽  
Optimal Operation ◽  
Optimal Scheduling ◽  
Electricity Pricing ◽  
Residential Areas ◽  
Electricity Cost ◽  
Pricing Scheme ◽  
Scheduling Method

Abstract From the perspective of global warming suppression and the depletion of energy resources, renewable energies, such as the solar collector (SC) and photovoltaic generation (PV), have been gaining attention in worldwide. Houses or buildings with PV and heat pumps (HPs) are recently being used in residential areas widely due to the time of use (TOU) electricity pricing scheme which is essentially inexpensive during middle-night and expensive during day-time. If fixed batteries and electric vehicles (EVs) can be introduced in the premises, the electricity cost would be even more reduced. While, if the occupants arbitrarily use these controllable loads respectively, power demand in residential buildings may fluctuate in the future. Thus, an optimal operation of controllable loads such as HPs, batteries and EV should be scheduled in the buildings in order to prevent power flow from fluctuating rapidly. This paper proposes an optimal scheduling method of controllable loads, and the purpose is not only the minimization of electricity cost for the consumers, but also suppression of fluctuation of power flow on the power supply side. Furthermore, a novel electricity pricing scheme is also suggested in this paper.

Improved Pseudo-Gradient Search Particle Swarm Optimization for Optimal Power Flow Problem

2016 ◽  
pp. 177-207 ◽  
Author(s):  
Jirawadee Polprasert ◽  
Weerakorn Ongsakul ◽  
Vo Ngoc Dieu
Keyword(s):  
Particle Swarm Optimization ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Voltage Stability ◽  
Stability Index ◽  
Gradient Search ◽  
Fuel Cost ◽  
Swarm Optimization ◽  
Optimal Power ◽  
Voltage Deviation

This paper proposes an improved pseudo-gradient search particle swarm optimization (IPG-PSO) for solving optimal power flow (OPF) with non-convex generator fuel cost functions. The objective of OPF problem is to minimize generator fuel cost considering valve point loading, voltage deviation and voltage stability index subject to power balance constraints and generator operating constraints, transformer tap setting constraints, shunt VAR compensator constraints, load bus voltage and line flow constraints. The proposed IPG-PSO method is an improved PSO by chaotic weight factor and guided by pseudo-gradient search for particle's movement in an appropriate direction. Test results on the IEEE 30-bus and 118-bus systems indicate that IPG-PSO method is superior to other methods in terms of lower generator fuel cost, smaller voltage deviation, and lower voltage stability index.

Optimal Transmission Switching Problem Utilizing an Enhanced Multi-Phase Seeker Optimization Algorithm

2016 ◽  
Vol 24 ◽  
pp. 85-102 ◽  
Author(s):  
Ragab A. El-Sehiemy ◽  
Mohammed Badeaa Shafiq ◽  
Ahmed M. Azmy
Keyword(s):  
Transmission Lines ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Cost Savings ◽  
Production Costs ◽  
Voltage Deviation ◽  
Multi Phase ◽  
The Cost ◽  
Seeker Optimization Algorithm

This paper proposes a procedure based on a multi-phase seeker optimization algorithm (MSOA) for optimizing the commitment of transmission system. The under consideration problem is formulated with the aid of AC-based security constrained optimal power flow (SC-OPF) considering system constraints. The target is to detect transmission lines commitment schedule that reduces system production costs and enables sufficient reserve levels from both generation and transmission. The methodology is illustrated through several computational tests on IEEE 57 and IEEE 118 bus test systems to confirm the previous objectives. It is proven that numerical results based on the use the AC model demonstrate that the calculation time is short enough and the cost savings are reasonably better than DC power flow model. In addition, all transmission lines are preserved within their permissible boundaries and the voltage deviation is maintained at the least levels.

scholarly journals A Scalable Mixed-Integer Decomposition Method for Security-Constrained Optimal Power Flow with Complementarity Constraints

2021 ◽  
Author(s):  
Kibaek Kim ◽  
Youngdae Kim ◽  
Daniel Maldonado ◽  
Michel Schanen ◽  
Victor Zavala ◽  
...  
Keyword(s):  
Decomposition Method ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Mixed Integer ◽  
Complementarity Constraints ◽  
Optimal Power

scholarly journals Distribution Optimal Power Flow With Energy Sharing Via a Peer-To-Peer Transactive Market

2021 ◽  
Vol 9 ◽  
Author(s):  
Boshen Zheng ◽  
Yue Fan ◽  
Wei Wei ◽  
Yourui Xu ◽  
Shaowei Huang ◽  
...  
Keyword(s):  
Equilibrium Condition ◽  
Power Flow ◽  
Distribution Systems ◽  
Optimal Power Flow ◽  
Distribution Network ◽  
Market Equilibrium ◽  
Peer To Peer ◽  
Mixed Integer ◽  
Optimal Power ◽  
Transactive Energy

The technology advancement and cost decline of renewable and sustainable energy increase the penetration of distributed energy resources (DERs) in distribution systems. Transactive energy helps balance the local generation and demand. Peer-to-peer (P2P) energy trading is a promising business model for transactive energy. Such a market scheme can increase the revenue of DER owners and reduce the waste of renewable energy. This article proposes an equilibrium model of a P2P transactive energy market. Every participant seeks the maximum personal interest, with the options of importing or providing energy from/to any other peer across different buses of the distribution network. The market equilibrium condition is obtained by combining the Karush–Kuhn–Tucker conditions of all problems of individual participants together. The energy transaction price is endogenously determined from the market equilibrium condition, which is cast as a mixed-integer linear program and solved by a commercial solver. The transactive energy flow is further embedded in the optimal power flow problem to ensure operating constraints of the distribution network. We propose a remedy to recover a near optimal solution when the second-order cone relaxation is inexact. Finally, a case study demonstrates that the proposed P2P market benefits all participants.

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