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 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 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 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 Soft Open Points-Based Energy Storage in Active Distribution Networks by Considering the Battery Lifetime

2021 ◽  
Vol 8 ◽  
Author(s):  
Jian Wang ◽  
Niancheng Zhou ◽  
Anqi Tao ◽  
Qianggang Wang
Keyword(s):  
Energy Storage ◽  
Reactive Power ◽  
Programming Model ◽  
Distribution Networks ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Operation Model ◽  
Battery Lifetime ◽  
Battery Degradation ◽  
Active Distribution Networks

Soft open point-based energy storage (SOP-based ES) can transfer power in time and space and also regulate reactive power. These characteristics help promote the integration of distributed generations (DGs) and reduce the operating cost of active distribution networks (ADNs). Therefore, this work proposed an optimal operation model for SOP-based ES in ADNs by considering the battery lifetime. First, the active and reactive power equations of SOP-based ES and battery degradation cost were modeled. Then, the optimal operation model that includes the operation cost of ADNs, loss cost, and battery degradation cost was established. The mixed integer nonlinear programming model was transformed to a mixed integer linear programming model derived through linearization treatment. Finally, the feasibility and effectiveness of the proposed optimization model are verified by the IEEE33 node system.

The Value of Energy Flexibility: Integrating Wind Resources in New York State

2018 ◽  
Author(s):  
Terence M. Conlon ◽  
Vijay Modi ◽  
Michael B. Waite
Keyword(s):  
New York ◽  
Energy Storage ◽  
New York State ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
York State ◽  
Average Load ◽  
Battery Capacity ◽  
Wind Potential ◽  
Wind Resources

This paper explores the effects of energy system flexibility on the contribution of wind generation to the New York State (NYS) electricity generation mix. First, the benefits of NYS-specific flexible hydropower are investigated. For all simulations, a mixed integer linear program minimizes net load to determine the maximum aggregate capacity factor for the installed wind power. A similar routine explores the benefits of three different types of energy flexibility: flexible supply, flexible demand, and bidirectional flexibility (i.e. energy storage). To compare across technologies, a novel method of standardizing flexibility inputs, Potential Flexible Energy (PFE), is introduced. With 30 GW wind capacity in NYS (average electricity demand of 18.7 GW), introducing electric vehicles with an average load of 1.44 GW and daily available battery capacity of 34.5 GWh (roughly equivalent to the daily use of 3.4 million passenger EVs) increases statewide wind utilization by 840 MW (9.0% of wind potential and 4.5% of average load). Added flexibility in the form of energy storage yields similar results: with 3.2 GW charge/discharge capability and 76.8 GWh storage capacity, statewide wind utilization increases by an average of 660 MW (7.0% of wind potential and 3.5% of average load). Because of transmission constraints and the geographic distribution of high-potential wind resources, increased wind utilization is only achieved when flexibility is added in the region where 86% of the 30 GW simulated wind capacity is located.

Integrated forest harvest planning and road-building model with consideration of economies of scale

2020 ◽  
Vol 50 (10) ◽  
pp. 989-1001
Author(s):  
Azadeh Mobtaker ◽  
Julio Montecinos ◽  
Mustapha Ouhimmou ◽  
Mikael Rönnqvist
Keyword(s):  
Economies Of Scale ◽  
Road Construction ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Road Building ◽  
The Road ◽  
Building Model ◽  
Wood Processing ◽  
Proposed Model ◽  
Transportation Plan

We consider the problem of tactical forest management over a 5-year horizon with yearly periods. The main decisions made consider which harvest areas to cut in each period, the flow of timber from an area to each wood-processing mill to satisfy its annual demand, and which roads to build to access a harvest area not connected to the existing road network. The goal is to minimize the total transportation and road-building costs subject to budget limitations. To explore the benefits of economies of scale (EOS) in road construction, we incorporated this notion in the proposed model. Then, the efficiency of the obtained solution is compared with the model without EOS. The proposed model is a mixed-integer linear program, including several timber assortments and multiple periods. We validated the model for a realistic case in the context of the province of Quebec. The results demonstrate that consideration of EOS significantly reduces the total cost by about 5.3%. In the EOS solution, the road segments that are built every year are very concentrated in specific parts of the region, allowing a road-building company to take advantage of EOS. Moreover, this solution provides a much more efficient timber transportation plan.

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