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A model in Optimization in Power-Shared Community

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A MODEL FOR ENERGY OPTIMIZATION IN POWER-SHARED COMMUNITY

IE 453- ENERGY SYSTEMS AND PLANNING

PROJECT REPORT

Team Members

Gizem Can 21000652

Ödül Binbaşıoğlu 21002393

Abstract

Nowadays, most of the academic researchers and industrial practitioners paying attention to the solar power, since it can be regarded as natural, clean and inexhaustible energy. The globe is now generally relying on fossil fuels such as coal, oil and natural gas. However, if people continue like that energy would be finite and one of the greatest threats to the environment. Hence, solar power is the solution that people seek for ages. Solar panel is useful device for family to heat water and to produce electricity to feed home electric devices. Based on the fact that home devices are commonly used in the evening, so it is intuitive and advisable to store electricity produced in day time into battery for evening use. However, equipping battery in every family may create highly expensive storage costs. Because of this reason, power-shared community scenario will be a nice proposed solution to this problem. In this report, we applied an energy optimization model (EOM) to determine the storage quota given to each family and optimize in the global community level the usage and storage of energy produced by families. The results show that it is an effective approach to put into practice.

1) INTRODUCTION

Currently, energy plays a big role in our lives and sustainability of energy is even more important than that. Because of the reason that fossil fuels are non-renewable, they counted as finite resources that will eventually dwindle, becoming too expensive or too environmentally damaging to retrieve [1]. In contrast, renewable energy resources such as wind and solar energyare constantly replenished and will never run out. If we look from the viewpoint of electricity; today it is generally produced or transformed through hydro power, nuclear power and thermal power.

Coal-fired power station generates more pollutants, which can deteriorate air quality and ultimately cause greenhouse effect. Although nuclear power, providing about 13-14 % of the world's electricity, is regarded as the cleanest and most efficient way to produce electricity, releases of radioactive materials can cause fateful disaster, for example Fukushima Daiichi nuclear disaster on 11 March 2011 [2]. Hydro power dams must lower water level and change water flow, which can result in serious negative biodiversity impact, for example preventing fish from cruising.

In order to produce electricity in an efficient and safe way; without damaging natural environment and biodiversity, we should be using wind power and solar power. However; wind turbines for converting wind power to electricity is so expensive compare to other energy sources. Thus, they are seldom own by families but by state or farms.

Solar power facility, which converts the sunlight into electricity by using photovoltaics is another safe and clean approach to generate electricity and is widely equipped in most families.

2) PROBLEM DEFINITION

Experts in academic and industrial fields are now seeking new ways to produce electricity for sustainability of the energy, but also efficiency in terms of cost is another consideration when applying new systems. As we mentioned above, wind power can be think as costly when families want to adopt it as a energy for their own electricity consumption. On the other hand, solar power is more cost effective one as an alternative energy. However, still surplus electricity after feeding home electronic devices, is either used to boil water or even wasted.

In power-shared community scenario; the surplus electricity generated by each family in the day time could be either used by other families in the same community if possible, or stored temporarily and to be used in the evening or night. However, few family buys high-capacity battery to store surplus electricity since battery cost is much more expensive than buying electricity from state grid. Based on the fact that battery cost does not increase linearly with its capacity while its margin of cost and capacity is in degression, sharing a single battery (or storage facility) with a couple of families can create economy of scale, which could increase electricity usage as well as decline battery cost per family [3]. If electricity reaches the capacity of storage facility, the surplus electricity could be sold to state grid. Fig.l demonstrates the infrastructure of power utilization by family.

Our paper is based on power-shared community, which owns storage facilities shared by community families. Each family generates electricity by solar panels providing power to operate home electronic devices. Surplus energy could be stored in any shared storage facility, but limited by an upper bound as each family shares part of power facility capacity. Family chooses in priority the closest energy storage facility so as to reduce energy loss while transmission.

The total energy stored in a storage facility is constrained by its capacity. The energy surpassing its capacity would be sold to state grid. Family consumes in priority the electricity stored in the storage facilities based on the amount it stored, and then buy electricity from state grid Fig 2. gives a demonstration of the power-shared comnunity scenario.

3) MODELING AND ANALYSIS

In this part, how the authors of the paper modeled the problem will be explained and also the small scale of this problem will be solved by using GAMS Solver 2009 licensed version. The GAMS model is in Appendix 1.

First of all the authors declared the sets, parameters, variables, objective function and constraints in order to model the problem. Below figure the sets are defined. According to this, there are three types of sets. First one represents the family number, second one represents the energy storage facility number and the last one represents the time of periods.

The parameters and their descriptions are shown below.

There are nine parameters and three of them represent the cost/price values, three of them represent the rates of energy loss/conversion,

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