scholarly journals Optimal Operation for Economic and Exergetic Objectives of a Multiple Energy Carrier System Considering Demand Response Program

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3995 ◽  
Author(s):  
Yu Huang ◽  
Shuqin Li ◽  
Peng Ding ◽  
Yan Zhang ◽  
Kai Yang ◽  
...  
Keyword(s):  
Demand Response ◽  
Test System ◽  
Optimal Operation ◽  
Energy Carrier ◽  
Mixed Integer ◽  
Selection Strategy ◽  
Operation Strategy ◽  
Carrier System ◽  
Energy Carriers ◽  
Scheduling Model

An MECS (multiple energy carrier system) could meet diverse energy needs owing to the integration of different energy carriers, while the distinction of quality of different energy resources should be taken into account during the operation stage, in addition the economic principle. Hence, in this paper, the concept of exergy is adopted to evaluate each energy carrier, and an economic–exergetic optimal scheduling model is formulated into a mixed integer linear programming (MILP) problem with the implementation of a real-time pricing (RTP)-based demand response (DR) program. Moreover, a multi-objective (MO) operation strategy is applied to this scheduling model, which is divided into two parts. First, the ε-constraint method is employed to cope with the MILP problem to obtain the Pareto front by using the state-of-the-art CPLEX solver under the General Algebraic Modeling System (GAMS) environment. Then, a preferred solution selection strategy is introduced to make a trade-off between the economic and exergetic objectives. A test system is investigated on a typical summer day, and the optimal dispatch results are compared to validate the effectiveness of the proposed model and MO operation strategy with and without DR. It is concluded that the MECS operator could more rationally allocate different energy carriers and decrease energy cost and exergy input simultaneously with the consideration of the DR scheme.

scholarly journals Optimal Operation of the Campus Microgrid considering the Resource Uncertainty and Demand Response Schemes

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Hafiz Abd ul Muqeet ◽  
Hafiz Mudassir Munir ◽  
Aftab Ahmad ◽  
Intisar Ali Sajjad ◽  
Guang-Jun Jiang ◽  
...  
Keyword(s):  
Power Systems ◽  
Demand Response ◽  
Solar Irradiance ◽  
Distribution System ◽  
Energy Demand ◽  
Mathematical Problem ◽  
Optimal Solution ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Proposed Model

Present power systems face problems such as rising energy charges and greenhouse gas (GHG) releases. These problems may be assuaged by participating distributed generators (DGs) and demand response (DR) policies in the distribution system (DS). The main focus of this paper is to propose an energy management system (EMS) approach for campus microgrid (µG). For this purpose, a Pakistani university has been investigated and an optimal solution has been proposed. Conventionally, it contains electricity from the national grid only as a supply to fulfil the energy demand. Under the proposed setup, it contains campus owned nondispatchable DGs such as solar photovoltaic (PV) panels and microturbines (MTs) as dispatchable sources. To overcome the random nature of solar irradiance, station battery has been integrated as energy storage. The subsequent nonlinear mathematical problem has been scheduled by mixed-integer nonlinear programming (MINLP) in MATLAB for saving energy cost and battery aging cost. The framework has been validated under deterministic and stochastic environments. Among random parameters, solar irradiance and load have been taken into consideration. Case studies have been carried out considering the demand response strategies to analyze the proposed model. The obtained results show that optimal management and scheduling of storage in the presence of DGs mutually benefit by minimizing consumption cost (customer) and grid load (utility) which show the efficacy of the proposed model. The results obtained are compared to the existing literature and a significant cost reduction is found.

scholarly journals Impact of Demand Response on Reliability Enhancement in Distribution Networks

2021 ◽  
Vol 13 (23) ◽  
pp. 13201
Author(s):  
Mohammad Reza Mansouri ◽  
Mohsen Simab ◽  
Bahman Bahmani Firouzi
Keyword(s):  
Demand Response ◽  
Electricity Market ◽  
Distribution System ◽  
Distribution Systems ◽  
Market Price ◽  
Distribution Networks ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Reliability Indices ◽  
Operation Costs

This paper presents an innovative instantaneous pricing scheme for optimal operation and improved reliability for distribution systems (DS). The purpose of the proposed program is to maximize the operator’s expected profit under various risk-taking conditions, such that the customers pay the minimum cost to supply energy. Using the previous information of the energy consumption for each customer, a customer baseline load (CBL) is defined; the energy price for consumption costs higher and lower than this level would be different. The proposed scheme calculates the difference between the baseline load and the consumption curve with the electricity market price instead of calculating the total consumption of the customers with the unstable price of the electricity market, which is uncertain. In the proposed tariff, the developed cost and load models are included in the distribution system operation problem, and the objective function is modeled as a mixed integer linear programming (MILP) problem. Also, the effect of demand response (DR) and elasticity on the load curve, the final profit of the distribution system operator, and payment risk and operation costs are examined. Since there are various uncertainties in the smart distribution grid, the calculations being time-consuming and volumetric is important in the evaluation of reliability indices. Thus, when computation volume can be decreased and computation speed can be increased, analytical reliability analysis methods can be used, as they were in the present work. Finally, the changes in the reliability indices were calculated for the ratio of the customers’ sensitivity to the price and the customers’ participation in the proposed tariff using an analytical method based on Monte Carlo simulation (MCS). The results showed the efficiency of the proposed method in increasing the operator profit, reducing the operation costs, and enhancing the reliability indices.

scholarly journals Optimal Outage Management Model Considering Emergency Demand Response Programs for a Smart Distribution System

2020 ◽  
Vol 10 (21) ◽  
pp. 7406
Author(s):  
Sobhan Dorahaki ◽  
Rahman Dashti ◽  
Hamid Reza Shaker
Keyword(s):  
Demand Response ◽  
Power Distribution ◽  
Distribution System ◽  
Test System ◽  
Mixed Integer ◽  
Distributed Generations ◽  
Grid Topology ◽  
The Cost ◽  
Demand Response Programs ◽  
Outage Management

In this paper, a novel smart outage management system considering Emergency Demand Response Programs (EDRPs) and Distributed Generations (DGs) denoted as SOMSDGsEDRPs is proposed. The EDRPs are provided to decrease the cost of load shading in a time of emergency. The objective function of the problem is proposed to minimize the load shading cost, the DG dispatch cost, the demand response cost and the repair dispatch time for crews. The SOMSDGsDERPs solves an optimization problem that is formulated as Mixed Integer Linear Programming (MILP) taking into account the grid topology constraints, EDRP constraints, DG constraints and crew constraints. The MILP formulation was demonstrated in the GAMS software and solved with the CPLEX solver. The proposed method was tested on the IEEE 34 bus test system as well as an actual Iranian 66 bus power distribution feeder. The results show that the EDRPs and DGs can be effective in decreasing the outage cost and increasing the served load of the distribution power system in a crisis time.

scholarly journals Combined Economic Emission Dispatch with Environment-Based Demand Response Using WU-ABC Algorithm

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6450
Author(s):  
Ho-Sung Ryu ◽  
Mun-Kyeom Kim
Keyword(s):  
Demand Response ◽  
Test System ◽  
Optimal Operation ◽  
Pollutant Emissions ◽  
Superior Performance ◽  
Pollutant Emission ◽  
Abc Algorithm ◽  
Penalty Factor ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

Owing to the growing interest in environmental problems worldwide, it is essential to schedule power generation considering the effects of pollutants. To address this, we propose an optimal approach that solves the combined economic emission dispatch (CEED) with maximum emission constraints by considering demand response (DR) program. The CEED consists of the sum of operation costs for each generator and the pollutant emissions. An environment-based demand response (EBDR) program is used to implement pollutant emission reduction and facilitate economic improvement. Through the weighting update artificial bee colony (WU-ABC) algorithm, the penalty factor that determines the weighting of the two objective functions is adjusted, and an optimal operation solution for a microgrid (MG) is then determined to resolve the CEED problem. The effectiveness and applicability of the proposed approach are demonstrated via comparative analyses at a modified grid-connected MG test system. The results confirm that the proposed approach not only satisfies emission constraints but also ensures an economically superior performance compared to other approaches. These results present a useful solution for microgrid operators considered environment issues.

scholarly journals Optimization of Multi-Energy Microgrid Operation in the Presence of PV, Heterogeneous Energy Storage and Integrated Demand Response

2021 ◽  
Vol 11 (3) ◽  
pp. 1005
Author(s):  
Jingshan Wang ◽  
Ke-Jun Li ◽  
Yongliang Liang ◽  
Zahid Javid
Keyword(s):  
Energy Storage ◽  
Demand Response ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Confidence Levels ◽  
Load Demand ◽  
Proposed Model ◽  
Typical Summer ◽  
Economic Ties

In this paper, a model is proposed for the optimal operation of multi-energy microgrids (MEMGs) in the presence of solar photovoltaics (PV), heterogeneous energy storage (HES) and integrated demand response (IDR), considering technical and economic ties among the resources. Uncertainty of solar power as well as the flexibility of electrical, cooling and heat load demand are taken into account. A p-efficient point method is applied to compute PV power at different confidence levels based on historical data. This method converts the uncertain PV energy from stochastic to deterministic to be included in the optimization model. The concept of demand response is extended and mathematically modeled using a linear function based on the quantized flexibility interval of multi-energy load demand. As a result, the overall model is formulated as a mixed-integer linear program, which can be effectively solved by the commercial solvers. The proposed model is implemented on two typical summer and winter days for various cases. Results of case studies show the important benefits for maximum PV utilization, energy efficiency and economic system operation. Moreover, the influence of the different confidence levels of PV power and effectiveness of IDR in the stochastic circumstances are addressed in the optimization-based operation.

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