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.

Optimal Power Generation Unit Sizing for Combined Heating and Power Systems With Uncertain Loads and Fuel/Electricity Prices

2011 ◽  
Author(s):  
Aaron Smith ◽  
Kyungtae Yun ◽  
Robert Thomas ◽  
Rogelio Luck
Keyword(s):  
Power Systems ◽  
Optimal Solution ◽  
Optimal Operation ◽  
Computational Effort ◽  
Mixed Integer ◽  
Weather Data ◽  
Optimal Sizing ◽  
Electricity Cost ◽  
Analytical Scheme

An optimal sizing method is developed in this work based on an analytical scheme for determining optimal operation decisions. Using the analytic optimal operation scheme allows for a more thorough optimal sizing method because of the minimal computational effort required as compared to mixed integer programming approaches. For example, an optimal sizing method based on this approach can more feasibly consider several years of weather data and the range of likely fuel/electricity costs for the term of operation of the PGU. The optimal sizing method in this work takes advantage of this efficient optimal operation scheme and provides a robust optimal solution with respect to weather and fuel/electricity cost uncertainty. A case study of a medium sized office building is carried out by testing the algorithm for a range of 20 commercially available diesel engine PGUs.

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 Energy Management of a Campus Microgrid Considering Financial and Economic Analysis with Demand Response Strategies

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8501
Author(s):  
Haseeb Javed ◽  
Hafiz Abdul Muqeet ◽  
Moazzam Shehzad ◽  
Mohsin Jamil ◽  
Ashraf Ali Khan ◽  
...  
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Demand Response ◽  
Distribution System ◽  
Mathematical Problem ◽  
Economic Effects ◽  
Mixed Integer ◽  
Renewable Energy Resources ◽  
Pv System ◽  
Utility Grid

An energy management system (EMS) was proposed for a campus microgrid (µG) with the incorporation of renewable energy resources to reduce the operational expenses and costs. Many uncertainties have created problems for microgrids that limit the generation of photovoltaics, causing an upsurge in the energy market prices, where regulating the voltage or frequency is a challenging task among several microgrid systems, and in the present era, it is an extremely important research area. This type of difficulty may be mitigated in the distribution system by utilizing the optimal demand response (DR) planning strategy and a distributed generator (DG). The goal of this article was to present a strategy proposal for the EMS structure for a campus microgrid to reduce the operational costs while increasing the self-consumption from green DGs. For this reason, a real-time-based institutional campus was investigated here, which aimed to get all of its power from the utility grid. In the proposed scenario, solar panels and wind turbines were considered as non-dispatchable DGs, whereas a diesel generator was considered as a dispatchable DG, with the inclusion of an energy storage system (ESS) to deal with solar radiation disruptions and high utility grid running expenses. The resulting linear mathematical problem was validated and plotted in MATLAB with mixed-integer linear programming (MILP). The simulation findings demonstrated that the proposed model of the EMS reduced the grid electricity costs by 38% for the campus microgrid. The environmental effects, economic effects, and the financial comparison of installed capacity of the PV system were also investigated here, and it was discovered that installing 1000 kW and 2000 kW rooftop solar reduced the GHG generation by up to 365.34 kg CO2/day and 700.68 kg CO2/day, respectively. The significant economic and environmental advantages based on the current scenario encourage campus owners to invest in DGs and to implement the installation of energy storage systems with advanced concepts.

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.

scholarly journals Optimum Distribution System Expansion Planning Incorporating DG Based on N-1 Criterion for Sustainable System

2021 ◽  
Vol 13 (12) ◽  
pp. 6708
Author(s):  
Hamza Mubarak ◽  
Nurulafiqah Nadzirah Mansor ◽  
Hazlie Mokhlis ◽  
Mahazani Mohamad ◽  
Hasmaini Mohamad ◽  
...  
Keyword(s):  
Power Systems ◽  
Distribution System ◽  
Industrial Revolution ◽  
Optimal Solution ◽  
Search Space ◽  
Planning Problem ◽  
System Expansion ◽  
Optimum Distribution ◽  
Optimal Sizing ◽  
Expansion Planning

Demand for continuous and reliable power supply has significantly increased, especially in this Industrial Revolution 4.0 era. In this regard, adequate planning of electrical power systems considering persistent load growth, increased integration of distributed generators (DGs), optimal system operation during N-1 contingencies, and compliance to the existing system constraints are paramount. However, these issues need to be parallelly addressed for optimum distribution system planning. Consequently, the planning optimization problem would become more complex due to the various technical and operational constraints as well as the enormous search space. To address these considerations, this paper proposes a strategy to obtain one optimal solution for the distribution system expansion planning by considering N-1 system contingencies for all branches and DG optimal sizing and placement as well as fluctuations in the load profiles. In this work, a hybrid firefly algorithm and particle swarm optimization (FA-PSO) was proposed to determine the optimal solution for the expansion planning problem. The validity of the proposed method was tested on IEEE 33- and 69-bus systems. The results show that incorporating DGs with optimal sizing and location minimizes the investment and power loss cost for the 33-bus system by 42.18% and 14.63%, respectively, and for the 69-system by 31.53% and 12%, respectively. In addition, comparative studies were done with a different model from the literature to verify the robustness of the proposed method.

scholarly journals Optimal Scheduling of Distributed Energy Resources in Residential Building under the Demand Response Commitment Contract

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2810 ◽  
Author(s):  
Keon Baek ◽  
Woong Ko ◽  
Jinho Kim
Keyword(s):  
Demand Response ◽  
Management System ◽  
Reference Model ◽  
Storage System ◽  
Operating Cost ◽  
Energy Resource ◽  
Residential Building ◽  
Mixed Integer ◽  
Distributed Energy ◽  
Proposed Model

This study proposes optimal day-ahead demand response (DR) participation strategies and distributed energy resource (DER) management in a residential building under an individual DR contract with a grid-system operator. First, this study introduces a DER management system in the residential building for participation to the day-ahead DR market. The distributed photovoltaic generation system (PV) and energy-storage system (ESS) are applied to reduce the electricity demand in the building and sell surplus energy on the grid. Among loads in the building, lighting (LTG) and heating, ventilation, and air conditioning (HVAC) loads are included in the DR program. In addition, it is assumed that a power management system of an electric vehicle (EV) charging station is integrated the DER management system. In order to describe stochastic behavior of EV owners, the uncertainty of EV is formulated based on their arrival and departure scenarios. For measuring the economic efficiency of the proposed model, we compare it with the DER self-consuming operation model without DR participation. The problem is solved using mixed integer linear programming to minimize the operating cost. The results in summer and winter are analyzed to evaluate the proposed algorithm’s validity. From these results, the proposed model can be confirmed as reducing operation cost compared to the reference model through optimal day-ahead DR capacity bidding and implementation.

scholarly journals Research on Economic Operation Strategy of CHP Microgrid Considering Renewable Energy Sources and Integrated Energy Demand Response

2019 ◽  
Vol 11 (18) ◽  
pp. 4825 ◽  
Author(s):  
Jun Dong ◽  
Shilin Nie ◽  
Hui Huang ◽  
Peiwen Yang ◽  
Anyuan Fu ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Demand Response ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Rapid Development ◽  
Utilization Efficiency ◽  
Energy Output ◽  
Mixed Integer ◽  
Energy Structure ◽  
Economic Operation

Renewable energy resources (RESs) play an important role in the upgrading and transformation of the global energy structure. However, the question of how to improve the utilization efficiency of RESs and reduce greenhouse gas emissions is still a challenge. Combined heating and power (CHP) is one effective solution and has experienced rapid development. Nevertheless, with the large scale of RESs penetrating into the power system, CHP microgrid economic operation faces great challenges. This paper proposes a CHP microgrid system that contains renewable energy with considering economy, the environment, and system flexibility, and the ultimate goal is to minimize system operation cost and carbon dioxide emissions (CO2) cost. Due to the volatility of renewable energy output, the fuzzy C-means (FCM) and clustering comprehensive quality (CCQ) models were first introduced to generate clustering scenarios of the renewable energy output and evaluate the clustering results. In addition, for the sake of improving the flexibility and reliability of the CHP microgrid, this paper considers the battery and integrated energy demand response (IEDR). Moreover, the strategy choices of microgrid operators under the condition of grid-connected and islanded based on environment and interest aspects are also developed, which have rarely been involved in previous studies. Finally, this stochastic optimization problem is transformed into a mixed integer linear programming (MILP), which simplifies the calculation process, and the results show that the operation mode under different conditions will have a great impact on microgrid economic and environmental benefits.

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 Reliability Enhancement of Electric Distribution Network Using Optimal Placement of Distributed Generation

2021 ◽  
Vol 13 (20) ◽  
pp. 11407
Author(s):  
Sanaullah Ahmad ◽  
Azzam ul Asar
Keyword(s):  
Power Systems ◽  
Distributed Generation ◽  
System Reliability ◽  
Distribution System ◽  
Energy Demand ◽  
Distribution Network ◽  
Optimal Location ◽  
Computational Time ◽  
Actual Distribution ◽  
Distribution System Reliability

As energy demand is increasing, power systems’ complexities are also increasing. With growing energy demand, new ways and techniques are formulated by researchers to increase the efficiency and reliability of power systems. A distribution system, which is one of the most important entities in a power system, contributes up to 90% of reliability problems. For a sustainable supply of power to customers, the distribution system reliability must be enhanced. Distributed generation (DG) is a new way to improve distribution system reliability by bringing generation nearer to the load centers. Artificial intelligence (AI) is an area in which much innovation and research is going on. Different scientific areas are utilizing AI techniques to enhance system performance and reliability. This work aims to apply DG as a distributed source in a distribution system to evaluate its impacts on reliability. The location of the DG is a design criteria problem that has a relevant effect on the reliability of the distribution system. As the distance of load centers from the feeder increases, outage durations also increase. The reliability was enhanced, as the SAIFI value was reduced by almost 40%, the SAIDI value by 25%, and the EENS value by 25% after injecting DG into the distribution network. The artificial neural network (ANN) technique was utilized to find the optimal location of the DG; the results were validated by installing DG at prescribed localities. The results showed that the injection of DG at proper locations enhances the reliability of a distribution system. The proposed approach was applied to thte Roy Billinton Test System (RBTS). The implementation of the ANN technique is a unique approach to the selection of a location for a DG unit, which confirms that applying this computational technique could decrease human errors that are associated with the hit and trial methods and could also decrease the computational complexities and computational time. This research can assist distribution companies in determining the reliability of an actual distribution system for planning and expansion purposes, as well as in injecting a DG at the most optimal location in order to enhance the distribution system reliability.

scholarly journals Hydro-reservoir management and unit-commitment in energy optimization

2021 ◽  
Author(s):  
Flávio Leite Loução Junior ◽  
Marlon Sproesser Mathias ◽  
Claudia Sagastizábal ◽  
Luiz-Rafael Santos ◽  
Francisco Nogueira Calmon Sobral
Keyword(s):  
Power Systems ◽  
Demand Response ◽  
Power Plants ◽  
Unit Commitment ◽  
Thermal Power ◽  
Point Of View ◽  
Mixed Integer ◽  
Thermal Power Plants ◽  
Hydro Power ◽  
Optimal Dispatch

In partnership with CCEE, CEPEL and RADIX as industrial partners, in 2021 the study group focused on the dynamics of hourly prices when industrial consumers are demand responsive, as a follow-up of the industrial problem tackled in 2018 and 2019, on ``Day-ahead pricing mechanisms for hydro-thermal power systems''. Demand response is currently being tested by the Brazilian independent system operator and by the trading chamber, ONS. The program considers reductions of consumption of some clients as an alternative to dispatching thermal power plants out of the merit order. The day-ahead problem of finding optimal dispatch and prices for the Brazilian system is modelled as a mixed-integer linear programming problem, with non-convexities related to fixed costs and minimal generation requirements for some thermal power plants. The work focuses on the point of view of an individual hydro-power generator, to determine business opportunities related to adhering to a demand response program.

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