Optimal Design of a Distributed Energy Resources System That Minimizes Cost While Reducing Carbon Emissions

2017 ◽  
Author(s):  
Robert Flores ◽  
Jack Brouwer
Keyword(s):  
Carbon Emissions ◽  
Energy Demand ◽  
Energy Resource ◽  
Minimum Cost ◽  
Mixed Integer ◽  
Distributed Energy ◽  
Gas Generator ◽  
Mixed Integer Linear Program ◽  
The Cost ◽  
The University

From a practical perspective, economics drive the development of distributed energy resource (DER) systems. However, the adoption of a DER system provides an opportunity for the end user to completely control their environmental footprint. This work examines the process of designing a DER system while controlling carbon emissions. A mixed integer linear program (MILP) for sizing and dispatching a DER system is developed. The MILP includes a novel formulation of constraints that govern utility natural gas, generator operational state, and charging of thermal energy storage. The MILP is executed using real energy demand data for the University of California, Irvine to optimally design a DER system that minimizes cost while also reducing carbon emissions by a specified quantity. Two primary technology scenarios are explored (DER including storage with and without electrical export). A trajectory of DER technology adoption is determined for both technology scenarios. The different operational methods through which each system achieved lower carbon emissions at minimum cost is examined. Finally, the cost to reduce carbon emissions is calculated for both technology scenarios.

scholarly journals Algorithms for the power-p Steiner tree problem in the Euclidean plane

2018 ◽  
Vol 25 (4) ◽  
pp. 28
Author(s):  
Christina Burt ◽  
Alysson Costa ◽  
Charl Ras
Keyword(s):  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Valid Inequalities ◽  
Minimum Cost ◽  
Performance Ratio ◽  
Mixed Integer ◽  
Steiner Tree Problem ◽  
Steiner Points ◽  
Tree Construction ◽  
The Cost

We study the problem of constructing minimum power-$p$ Euclidean $k$-Steiner trees in the plane. The problem is to find a tree of minimum cost spanning a set of given terminals where, as opposed to the minimum spanning tree problem, at most $k$ additional nodes (Steiner points) may be introduced anywhere in the plane. The cost of an edge is its length to the power of $p$ (where $p\geq 1$), and the cost of a network is the sum of all edge costs. We propose two heuristics: a ``beaded" minimum spanning tree heuristic; and a heuristic which alternates between minimum spanning tree construction and a local fixed topology minimisation procedure for locating the Steiner points. We show that the performance ratio $\kappa$ of the beaded-MST heuristic satisfies $\sqrt{3}^{p-1}(1+2^{1-p})\leq \kappa\leq 3(2^{p-1})$. We then provide two mixed-integer nonlinear programming formulations for the problem, and extend several important geometric properties into valid inequalities. Finally, we combine the valid inequalities with warm-starting and preprocessing to obtain computational improvements for the $p=2$ case.

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 Vehicle Routing and Scheduling Optimization of Ship Steel Distribution Center under Green Shipbuilding Mode

2019 ◽  
Vol 11 (15) ◽  
pp. 4248 ◽  
Author(s):  
Jinghua Li ◽  
Hui Guo ◽  
Qinghua Zhou ◽  
Boxin Yang
Keyword(s):  
Vehicle Routing ◽  
Carbon Emissions ◽  
Water Drop ◽  
Time Windows ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Vehicle Routing And Scheduling ◽  
Routing And Scheduling ◽  
Distribution Process ◽  
The Cost

Timeliness of steel distribution centers can effectively ensure the smooth progress of ship construction, but the carbon emissions of vehicles in the distribution process are also a major source of pollution. Therefore, when considering the common cost of vehicle distribution, taking the carbon emissions of vehicles into account, this paper establishes a Mixed Integer Linear Programming (MILP) model called green vehicle routing and scheduling problem with simultaneous pickups and deliveries and time windows (GVRSP-SPDTW). An intelligent water drop algorithm is designed and improved, and compared with the genetic algorithm and traditional intelligent water drop algorithm. The applicability of the improved intelligent water drop algorithm is proven. Finally, it is applied to a specific example to prove that the improved intelligent water drop algorithm can effectively reduce the cost of such problems, thereby reducing the carbon emissions of vehicles in the distribution process, achieving the goals of reducing environmental pollution and green shipbuilding.

scholarly journals Stochastic Mixed-Integer Programming (SMIP)-Based Distributed Energy Resource Allocation Method for Virtual Power Plants

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 67
Author(s):  
Rakkyung Ko ◽  
Sung-Kwan Joo
Keyword(s):  
Renewable Energy ◽  
Power Plants ◽  
Renewable Energy Sources ◽  
Energy Resource ◽  
Mixed Integer ◽  
Virtual Power ◽  
Distributed Energy ◽  
Distributed Energy Resource ◽  
Stochastic Mixed Integer Programming ◽  
Virtual Power Plants

Virtual power plants (VPPs) have been widely researched to handle the unpredictability and variable nature of renewable energy sources. The distributed energy resources are aggregated to form into a virtual power plant and operate as a single generator from the perspective of a system operator. Power system operators often utilize the incentives to operate virtual power plants in desired ways. To maximize the revenue of virtual power plant operators, including its incentives, an optimal portfolio needs to be identified, because each renewable energy source has a different generation pattern. This study proposes a stochastic mixed-integer programming based distributed energy resource allocation method. The proposed method attempts to maximize the revenue of VPP operators considering market incentives. Furthermore, the uncertainty in the generation pattern of renewable energy sources is considered by the stochastic approach. Numerical results show the effectiveness of the proposed method.

Optimum Siting and Sizing of Distributed Energy Resources Taking into Consideration Hourly Operating Strategies

2014 ◽  
Vol 953-954 ◽  
pp. 871-875
Author(s):  
Hong Bo Ren ◽  
Qiong Wu ◽  
Jian Yang ◽  
Yin Yin Ban
Keyword(s):  
Evaluation Model ◽  
Energy Resource ◽  
District Heating ◽  
Mixed Integer ◽  
Design Parameters ◽  
Distributed Energy ◽  
Distributed Energy Resource ◽  
Production And Consumption ◽  
Operating Strategies ◽  
And Storage

In this paper, a distributed energy resource (DER) system plan and evaluation model is extended to include the design of district heating network. In the model, production and consumption of electric power and heat, power transmissions, transport of fuels to the production plants, transport of water in the district heating pipelines and storage of heat are taken into account. The problem is formulated as a mixed integer linear programming (MILP) model where the objective is to minimize the overall cost of the DER system. The solution gives the DER structure, i.e., which production units, heat transport lines and storages should be built as well as their locations, together with design parameters for plants and pipelines.

scholarly journals Decomposing Loosely Coupled Mixed-Integer Programs for Optimal Microgrid Design

2021 ◽  
Author(s):  
Alexander J. Zolan ◽  
Michael S. Scioletti ◽  
David P. Morton ◽  
Alexandra M. Newman
Keyword(s):  
Minimum Cost ◽  
Energy System ◽  
Mixed Integer ◽  
Nonlinear Program ◽  
Diesel Generator ◽  
Mixed Integer Linear Program ◽  
Loosely Coupled ◽  
Distributed Energy System ◽  
One Year ◽  
Microgrid Design

Microgrids are frequently employed in remote regions, in part because access to a larger electric grid is impossible, difficult, or compromises reliability and independence. Although small microgrids often employ spot generation, in which a diesel generator is attached directly to a load, microgrids that combine these individual loads and augment generators with photovoltaic cells and batteries as a distributed energy system are emerging as a safer, less costly alternative. We present a model that seeks the minimum-cost microgrid design and ideal dispatched power to support a small remote site for one year with hourly fidelity under a detailed battery model; this mixed-integer nonlinear program (MINLP) is intractable with commercial solvers but loosely coupled with respect to time. A mixed-integer linear program (MIP) approximates the model, and a partitioning scheme linearizes the bilinear terms. We introduce a novel policy for loosely coupled MIPs in which the system reverts to equivalent conditions at regular time intervals; this separates the problem into subproblems that we solve in parallel. We obtain solutions within 5% of optimality in at most six minutes across 14 MIP instances from the literature and solutions within 5% of optimality to the MINLP instances within 20 minutes.

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