Role of polygeneration in sustainable energy system development : Challenges and opportunities from optimization viewpoints

A sustainable energy system can be treated as a development of the distributed generation concept. It meets energy demands locally from renewable energy or/and high-efficiency polygeneration production technologies, and is characterized by energy and cost efficiency, reliability, and environmental-friendliness.Distributed energy systems typically use renewable energy resources to supply all energy demands, such as heat, cooling, and electric power in an integrated way. However, it seems that too much emphasis is placed on power and associated renewable energy-based power technologies for dealing with sustainability issues in public discussion and the research community. Often, equally important thermal energy (heat and cooling) and polygeneration are ignored. Polygeneration is an energy- efficient technology for generating simultaneously heat and power as well as other energy products in a single integrated process. Energy efficiency contributes significantly to CO2 emission reduction. This paper discusses the role of polygeneration in a distributed energy system and the contributions of polygeneration to the development of sustainable energy systems. The paper also stresses that efficient decision support tools for sustainable polygeneration systems are important to achieve sustainability. First, the joint characteristic of a polygeneration plant that defines the dependency between different energy products is reviewed. Then, typical methods for dealing with polygeneration systems are reviewed. The review attempts to highlight the complexity of polygeneration systems and potential of polygeneration systems to adjust output of different energy products. Next, the challenges of sustainable polygeneration energy systems are discussed. Then some practices for operating polygeneration plants are discussed.Peer reviewe

An efficient algorithm for bi-objective combined heat and power production planning under the emission trading scheme

The growing environmental awareness and the apparent conflicts between economic and environmental objectives turn energy planning problems naturally into multi-objective optimization problems. In the current study, mixed fuel combustion is considered as an option to achieve tradeoff between economic objective (associated with fuel cost) and emission objective (measured in CO2 emission cost according to fuels and emission allowance price) because a fuel with higher emissions is usually cheaper than one with lower emissions. Combined heat and power (CHP) production is an important high-efficiency technology to promote under the emission trading scheme. In CHP production, the production planning of both commodities must be done in coordination. A long-term planning problem decomposes into thousands of hourly subproblems. In this paper, a bi-objective multi-period linear programming CHP planning model is presented first. Then, an efficient specialized merging algorithm for constructing the exact Pareto frontier (PF) of the problem is presented. The algorithm is theoretically and empirically compared against a modified dichotomic search algorithm. The efficiency and effectiveness of the algorithm is justified.Peer reviewe

Scheduling periodical deliveries to minimize fleet size

In this thesis, we study the problem in which a distribution center delivers goods to a fixed set of customers periodically. Each customer has a specified delivery frequency (the number of deliveries over a T-day period). The deliveries to the same customer are required to be spaced as evenly as possible while the actual delivery days are flexible. We propose a routing then scheduling approach to solve the problem of minimizing the fleet size. In this approach, a routing problem for making one delivery to every customer is solved first. Then these routes are scheduled over the T days based on the delivery frequency. For the problem with the same delivery frequency, a simple and effective scheduling algorithm is developed and its performance is analysed theoretically. Then a modified scheduling algorithm is proposed to generate alternative feasible solutions with the same fleet size. This modified algorithm lays the foundation for the algorithm dealing with the problem with different delivery frequencies. For the problem with different delivery frequencies, the customers with the same delivery frequency are grouped first and the optimal routes are found for each group. An Integer programming model is then given to combine the schedules of all the groups. Finally heuristics are developed to solve the problem efficiently. Delivery days for different delivery frequencies need to be well coordinated taking the flexibility in the schedule of each frequency. Our heuristic takes a dynamic pattern generation approach (sequentially determining the cluster size of delivery days for each delivery frequency) and employs a number of different coordination algorithms. Extensive computational experiments are carried out demonstrating that the average performance of the heuristics is very good. With the assumption that customers with different delivery frequencies do not appear in the same delivery route, the computational results show that the difference between the fleet size determined by the heuristics and the lower bound is one when T<60, and the difference is two when 60≤T≤360

An efficient model and algorithm for the transmission-constrained multi-site combined heat and power system

This paper deals with the transmission-constrained multi-site combined heat and power (CHP) problem and formulates it as a linear programming (LP) model with a special structure. CHP systems are treated as an extension of power-only systems. Each site can be treated as a regional energy system to supply both heat and power. Heat demand is satisfied by local production while power demand can be satisfied by local generation plus power exchange over the power network. The challenge of this problem is that power transmission needs to be coordinated with both power and heat production in each site. The transmission-constrained multi-site CHP system can be operated cost-efficiently according to hourly demand forecast for heat and power by coordinating production and transmission activities among different sites. An efficient network power Simplex algorithm is developed to this end. Numerical experiments with realistic test data show that the algorithm is 7–360 (with average 30) times faster than a commercial LPcode.Peer reviewe

An efficient linear programming model and optimization algorithm for trigeneration

Trigeneration is a booming technology for efficient and clean provision of energy. It has potential for reducing pollution emissions dramatically. Similar to combined heat and power (CHP) production, cost-efficient operation of a trigeneration system can be planned using an optimization model based on hourly load forecasts. A long-term planning model decomposes into thousands of hourly models, which can be solved separately. In this paper, we model the hourly trigeneration problem as a linear programming (LP) model with a joint characteristic for three energy components to minimize simultaneously the production and purchase costs of three energy components, as well as CO2 emissions costs. Then we explore the structure of the problem and propose the specialized Tri-Commodity Simplex (TCS) algorithm that employs this structure efficiently. The speed of TCS is based on extremely fast basis inverse operations and reuse of old basic solutions from previously solved hourly models. We compare the performance of TCS with realistic models against an efficient sparse Simplex code using the product form of inverse. In test runs, TCS is from 36 to 58 times faster when starting from the initial basis and from 43 to 179 times faster when reusing the old basis.Linear programming Trigeneration Energy Optimization CO2 emissions