wind and solar based energy systems for communities pdf
Rupp Carriveau1 and David S-K. Ting1
According to dictionary.com , a community is a social group of any size whose
members dwell in a specific locality under one government, and they share the
same cultural and historical heritage.
Accordingly, both big cities and small towns
Their future leans on, among other things, the proper management of sustainable energy and natural resources that they feed on .
For the more
progressive localities, there is already in place some solid share of renewable
energy; wind, in particular.
Other than the promise of including a greater extent of
solar, these wind-fed communities must look at ways to further their current and
To improve performance and maintenance of the existing, particularly wind,
infrastructure alone would render significant stability in the community, renewable
The resulting benefits include both a cleaner environment and
healthier economy. In Chapter 2, Morshedizadeh et al.
describe practical, datadriven methods for predicting commercial wind turbine performance. A comprehensive set of supervisory control and data acquisition data was utilized to delineate
the entire process, including the proper treatment of missing data and outliers,
training of the intelligent algorithm, pertinent feature selection, and modelling of
the design networks.
The superiority of Bruce Lee’s Jeet Kone Do is largely
attributed to the combination and adaptation of the most potent moves from differing styles [3,4]. Likewise, it is illustrated that fusion of appropriately-weighted,
different networks can enhance the decision-making process, for best prediction of
wind turbine performance.
Furthermore, wind farms, large or small, can be optimized to best benefit the communities. Vasel-Be-Hagh outlines essential elements
of wind farm layout optimization in Chapter 3.
Several wake loss models and
different search methods, ranging from primitive to sophisticated ones, are analysed, compared, and contrasted.
The base location, number, rotor diameter, hub
height, rotational direction, and yaw angle of wind turbines, along with the shape of
the wind farm are fully considered in the optimization process.
Wake models, from
the computationally intensive large eddy simulation to purely empirical models are
explored. For optimization, Generic Algorithm, Greedy Algorithm, Particle Swarm
2 Wind and solar based energy systems for communities
Optimization, Ant Colony Search Algorithm, Simulated Annealing, and Definite
Point Selection Algorithm are presented.
The chapter concludes with 13 distinct,
interesting cases for the readers to sweat over.
The experiential exercise aims at
bringing readers up from ‘interested’ to ‘involved’, or, ‘amateurs’ to ‘new practitioners’, concerning wind farm optimization.
Admit it or not, money, to a large extent, does make the world go around.
Miller and Carriveau attempt to underplay the outstanding challenge with renewable energy implementation, the very high capital cost, in Chapter 4.
So, why don’t
we leave renewable energy developments to private enterprise? Among other
benefits, community energy provides power for the community, potential income
for the community, promotes social cohesion, provides local jobs, and certain
control regarding the protection of our environment.
While wind and solar successes in some smaller communities, both in overseas and in North America, can
alleviate significant uncertainty, the transferability of these to other communities
lingers on the specific available incentives and legalities.
Their newness to the
industry also induces extra costs for learning, which is absorbed into the raising
To alleviate the multitude of challenges faced by newcomers,
small renewable energy developers financing options are not only provided, but the
readers are guided through the process with specific successful examples.
These cases also have the potential to be extended into commercial, renewable energy
The gracious energy lavished via the sun can provide benefit beyond the heat
or thermal aspect. In Chapter 7, Singh et al. provide an overview of a community
level solar photovoltaic (PV) installation in the form of a solar garden, or solar
farm, or solar power plant, to partially or fully meet the electricity needs.
Three ownership models, along with their benefits and barriers, are presented. The realization of these models are illustrated with the help of actual examples, that is,
completed, conceptualized, and under construction projects in Canada, the United
States of America, Europe, South America, and East Africa.
It is not surprising to
see that no single model works in all situations.
The important point is that countries, provinces, states, and cities must develop policies that promote investment in
community renewable energy projects, notably, solar PV projects.
We definitely do not want to see any part of solar PV systems flying around
during gusty days.
As such, it is critical that the wind loads on solar PV installations
are properly assessed, and to ensure that the installations can withstand the beatings
of the wind. Kazmirowicz et al.
examine the wind loads on rooftop solar PV
installations in an urban setting, in Chapter 8.
The renewed concern on the vitality
of these installations is, in part, due to the continuous cost reduction, drastic rise in
rooftop units in crowded urban areas, and the global rise in damaging wind conditions such as typhoons and hurricanes.
The induced loads by these and other
extreme winds are of particular interest.
Surprising or not, there is a lack of field
measurements of wind loads on solar PV structures.
The existing Australian standard is presented, prior to introducing Urban Wind Environment, and this is logically followed by Australian mounting system design practices.
Both wind tunnel
test methods and computational fluid dynamic simulations are useful in securing
the structural health of current and future PV installations.
4 Wind and solar based energy systems for communities
economics of battery storage.
For proper battery selection, the energy consumption
pattern is a priori.
The selection process safety considerations are discussed. It is
somewhat awakening to learn that safety policies and standards are a key challenge
in keeping the industry on the right track.
Like solar PV installation regulations,
according to these Australian authors, Australia, once again, stands as a pioneer in
regulatory intervention to drive adoption of energy storage.
There will be no future if conservation is undermined.
And conservation goes
hand-in-hand with demand management.
Ma and Venkatesh propose a conservation model which targets conservation at the most price-sensitive consumers but
only during peak energy-consumption periods, in Chapter 11.
Other than peakusage disincentives, they also propose incentives for consumption during off-peak
periods. This disincentive–incentive conservation approach works by flattening the
demand curve, delaying base expansions, and lowering unit costs.
The target is on
the localized community energy systems, like the battery storage imparted by Zhu
et al. in the previous chapter, to absorb momentary fluctuations in supply and
Their philosophy differs from the traditional one, which aims at realizing
conservation by lowering the variable costs through behavioural change and efficiency. Presumably, Ma and Venkatesh understand our great struggle when it
comes to changing habits; like the idiom, it is easier to change mountains and rivers
then to alter one’s character.
Wisely, they tackle the challenge head-on, by reducing
fixed costs, which requires no behavioural change of the consumers.
Data-driven methods for prediction of smallto-medium wind turbines performance
, Rupp Carriveau1 and
David S-K. Ting1
The growth in the wind energy is rapidly increasing.
Accurate modelling of wind
turbines performance as targeted by ongoing research studies can escalate wind
energy production capabilities, reliability, and expand its potential to replace fossil
In addition, optimisation of turbines will considerably expand the profit
margins and garner the attraction of investors.
Optimization of wind farms for communities
Energy supplies are moving away from environmentally damaging, finite, and
expensive fossil fuels to renewable energy resources through technological innovations. Wind energy is one of the most advanced renewable energy resources due
to the extensive research that has been ongoing over the last decades to optimize
aerodynamic performance of wind turbines, structural design of wind turbines,
control strategies, site selection, and the layout of wind farms.
This chapter outlines
fundamental elements of wind-farm-layout optimization including optimization
parameters, objective functions, wake loss models, and search methods.
Optimization parameters include base location, number, rotor diameter, hub height, rotational direction, and yaw angle of wind turbines, as well as shape of wind farm
area. In the wake loss models section, all existing wake-loss models including large
eddy simulation, nonlinear and linearized Reynolds-averaged Navier–Stokes
models, stochastic models, kinematic models, and empirical models are discussed.
In addition, different search methods, from simple greedy search algorithms to
advanced genetic algorithms (GAs), are briefly reviewed and compared.
Financing for community wind and solar
Lindsay Miller1 and Rupp Carriveau1
Community energy, and in particular, community wind and solar, has experienced
significant growth in recent years.
The main challenge to further expansion and
implementation of community renewable energy projects is the high capital costs
associated with project development.
This chapter will present case studies of community wind and solar financing and include innovative mechanisms such as lease
financing, sales of renewable energy credits, crowdfunding, and unconventional loan
Through compilation of these cases, the objective is to provide prospective
small renewable energy developers options as to how they can go about financing
their projects and ultimately empower communities to independently produce energy
while reducing greenhouse gases.