D. S. Strebkov, V. G. Chirkov, All-Russian Institute for Electrification in Agriculture, Russian Academy of Agricultural Science.

The extended use of bio-fuels is an important part of the sustainable development strategy declared by the EU for the several forthcoming decades. For transport applications alone, the target of 2% share of bio-fuels and other renewables is set for 2005 which shall rise by 0.75% per year up to 5.75% in the year 2010 [1]. Russia has the highest in Europe potential of reproducible plant biomass and is capable of making a substantial contribution to the EU biofuel market. The aim of this paper is to give a brief analysis of the current economic, social and technological conditions for Russia’s integration into the EU bio-fuel strategy.

Biomass resources in Russia

Plant biomass wastes applicable to energy purposes in Russia are estimated to be 100 Mt/year of plant cultivation residues and 700 Mt/year of timber-felling and wood­working wastes [2]. It is equivalent to about 1400 TWh of energy per year, while the amount of biomass to be commercially available in the EU by 2010 is only approx. 1100 TWh (90 Mt o. e.) per year [3]. Biomass resources in the European part of Russia alone amount to over 400 TWh/year, according to the evaluation made by the Swedish organisation NUTEK [4]. Long-fallow and unused arable lands constitute additional biomass resources potential. In 1995, 15 million hectares of arable land in Russia stayed unused, which is more than twice as much that, according to EU experts, would be allocated for energy crops in Europe (5.6 million hectares or 10 %) by 2020 [5]. If this land were used for SRC, it could annually yield, for instance, about 105 Mt of oven dry willow wood [6], which is equivalent to over 500 TWh. Agricultural production in Russia has considerably decreased since 1990s when the economic policy of the new federal government retrenched abruptly the subsidies to agricultural enterprices. This has led to the bankruptcy of most of the large-scale farms that were the backbone of the rural economic structure for over half a century. Since then, unused arable land has considerably increased providing favourable conditions for implementation of modern SRC energy crop production technologies.

150 -100 -50 0 50 100 150 Fig. 4 Seasonal comparison of average electricity generation from wind, quotient of average monthly values of July and January production 1979-1992; met. data: ECMWF.

The most favourable areas for electricity production from wind power in EU countries are dominated by winter winds. For this reason, as is illustrated in Fig. 4, the major contribution of wind generation occurs during this period.

The achievable production — Graph E) — Fig. 5 varies from month to month significantly more than the electricity demand — Graph G). The trade wind regions of northern Africa (southern Morocco and Mauritania, Graph c) and d))exhibit similarly strong seasonal variations, but their peak production is during the summer months. By purposefully selecting a combination of certain areas for production, the typical monthly electricity generation may largely be matched to demand. This fact is illustrated in Graph F), in which one-third of the rated capacities are assumed to lie within the EU, with the rest equally divided among the other regions. In this manner, the area of generation and thus the total potential is greatly expanded, simultaneously accompanied by very beneficial smoothing effects.

P_Mean/P_Rated 0.37 ■ a) Northern Russia and Western Siberia 0.28 b) Kazakhstan 0.38 c) Southern Morocco 0.36 d) Mauritania 0.30 [33] E) Good Wind Sites within EU and Norway 0.33 —F) Combination: 1/3 E) and each 1/6 a), b), 0.47^- G) Electric Demand within EU and Norway

Fig. 6 Seasonal comparison of average photovoltaic electricity generation, quotient of average monthly values of July and January production 1979-1992; met. data: ECMWF and NCEP

1.0 0.9

0.8 s 0.7 0.6 > “ 05 ф s 04 0.3 c о 0.2 0.1

0.0

Time [Month]

1.5

1.2

и c « I Q о

0.9

m 0.6 0.3 §

0.0

Fig. 5 Relative monthly average: electricity production from wind turbines (WT) in selected good wind areas and electricity consumption of EU and Norway. a.) to d.) represent Extraeuropean production E.) represents European production and F.) is the combined production of wind power at all regions whereas G.) represents the average consumption in the EU & Norway weighted with the today’s rated power of all power plants installed. The variations in the electricity production from wind power diminish by transcending from the simultaneous feed-in from domestic European locations to generation that includes production from outside of Europe. In the case of a high percentage of electricity being produced from wind power, the instances of excessive generation will be significantly reduced as well as the periods of relatively low feed-in from wind power.

c) und d)

• 4.3 Temporal Behaviour of the Electricity Produced by Parabolic Trough Power Plants

Fig. 7 Seasonal comparison of average heat production by mirror arrays in concentrating parabolic power plants, quotient of average monthly values of December and July production 1983-1992; met. data: ECMWF and NCEP.

Due to the parallel configuration of the mirror elements, the trough array may partially block the rays of the sun when it is low on the horizon. For this reason, and because of the low angle of incidence during the winter, the output varies throughout the months of the year in addition to random changes of incident radiation caused by local weather phenomena. This effect is diminished gradually while approaching equatorial latitudes, but it is still distinctly noticeable even at locations in southern Mauritania, where the achievable production in December reaches more than 80% of July production, as indicated in Fig. 7. Solar thermal generation alone is therefore not adequate to track the seasonal variations in European electricity consumption. In combination with European wind power, however, this requirement may be quite easily met.

The solar energy resources in the building stock is assessed in several steps of which the key features are presented in the table below.

Solar-architectural key features for the assessment of the buildings and their potential for solar energy purposes (photovoltaic and thermal)

Major characteristics	Descriptive and analytical elements
Solar characteristics	• Irradiation (general in the area concerned) • Yield (specific for the surfaces concerned) • Shading caused by elements other than construction features of the building concerned, e. g. trees, neighbouring buildings, wider horizon)
Architectural characteristics	• Shape (eight basic types of roof forms) • Construction features of the relevant building skin parts (e. g. chimneys, windows, terrasses, HVAC, etc.)
Other characteristics	• Listed buildings • Cultural / historical zones

With respect to the solar irradiation, it can be stated that sunshine is quite generous a) for the Canton of Geneva as a whole (if compared to other densely populated areas in Switzerland) with 1350 kWh per square meter of optimally oriented surface and b) for a wide range of differently oriented surfaces, too. Examples can illustrate the latter point (compare with the figure below):

1. a surface oriented south yields at least 90% of the maximum annual solar irradiation if it is tilted between 2° and 62°

2. a surface tilted by 25° yields at least 90% of the maximum annual solar irradiation if it is oriented between — 67° et 67°, thus grosso modo between ESE and WSW.

3.

Solar Irradiation in Relative Terms of Maximum Yearly Yield (Solar Criteria) for Different Surfaces (Tilt and Orientation) — Location: Geneva-Cointrin 180- 150- 120 * 90- 60- ЗО* 0* — ЗО* — Є0* -90* -120* -150* -180* Orientation (Azimut)

о 95%-IOO% □ 90%-85% o85%80% o80%-85% □ 75%80% ■70%-75% ■65%-70% ■60%4′;5% ■55%«% ■50%-55% ■45%-50% ■«%-«%

a horizontal surface still yields 89% of the maximum annual solar irradiation.

Solar irradiation in relative terms of maximum yearly yield (solar criteria in % of 1350 kWh per square meter and year) for different surfaces (tilt and orientation) — location: Geneva- Cointrin

□ □ bailments

В □ batiments

H □ parcelles I I <all other values^ PROPRI_PUB 0СДР; СЕН; CFF; C 0 □ 0 0

communes

0 0 orthophoto В D mns_relief_ge В □ Plan de ville E 0 MNS 0 0 partiel_lm 0 0 partie2_lm 0 0 partie3_lm 0 0 partie4_lm 0 0 partie5_lm 0 0 partie6_lm

?Іх]

Identify (ram: | batiments_pub

Location: І497182.74 Л1Є175.75

SHAPE

Polygon

COMMUNE Onex NO_COMM 34 NO_BATIMEN 1315

BATDDP

DATEDT DESTINATIO Salle despoil NOMENCLATU 4.5.2 NOME N_CLAS E quipement collectif PROVENANCE autie

SURFACE

OBJECTID 43093S3

EPOQUE SHAPE_AREA 829.90775 SHAPE_LEN 11Є. 037047

The buildings and their surfaces are subsequently attributed to 19 categories while being visually assessed with GIS. First category comprises horizontal surfaces (e. g. flat roofs), the other 18 categories are defined through six orientation sectors (steps of 30°) and three tilt classes (moderate, medium and high tilt). An illustration of how the view and statistical data are screened is shown in the figure below.

Screenshot of aerial picture and statistical data provided by the GIS. Source: SITG

The different elements — both positively and negatively influencing the suitability of the building with respect to solar energy uses — are summarised on sequenced quality levels and aggregated in respective indexes providing quantitative reference values. The table below presents the global analysis results of the approx. 1700 public buildings assessed.

Levels of solar-architectural suitability and reduction factors Surfaces Suitability index Ground floor area 1’888’400 m2 1.00 Roof surfaces with suitable exposition (good solar yield) 1‘447‘921 m2 0.77 Reduction factor « construction — obstruction » 44.8% Roof surfaces with suitable exposition and architecture 799‘517 m2 0.42 Reduction factor « shading » 18.6% Solar-architecturally suitable surface 650‘546 m2 0.34

Levels of solar-architectural suitability and reduction factors as well as resulting surfaces and global suitability indexes (reference ratio « suitable area / ground floor area »)

A first assessment round is dedicated to the public buildings in Geneva, which belong either to the municipalities or to the canton and with a minimum ground floor area of 300 m2. A second assessment round is dedicated to a representative selection of buildings of the whole building stock in the territory.

Intermediary results based on the approx. 1700 objects assessed are available for the « geometry » potential, i. e. solar-architectural suitability of the building skin given. These results range from basic descriptions of the building stock in terms of building types, age structure, property structure, roofscape, etc. to elaborated analysis of the solar — architectural suitability of the public building stock for solar photovoltaic and thermal

570 public buildings have been identified with a tilted roof area being solar — architecturally suitable (minimum solar yield is 90%) for photovoltaic applica­tions. The most important system class in relative terms is the size category from 10 to 30 kWp with a share of 47%.

729 public buildings have been identified with a horizontal / flat roof area being solar-architecturally suitable (minimum solar yield is 90%) for photovoltaic appli­cations. The most important system class in relative terms is the size category from 10 to 30 kWp with a share of 40%.

203 public buildings have been identified with a tilted roof area being solar — architecturally suitable (orientation south ±30°) for solar thermal applications. The most important system class in relative terms is the size category from 100 to 300 m2 with a share of 42%. The solar active collector is calculated on a basis of 1 m2 of suitable roof area is equivalent to 1 m2 of suitable active collector area.

738 public buildings have been identified with a horizontal / flat roof area being solar-architecturally suitable for solar thermal applications. The most important system class in relative terms is the size category from 100 to 300 m2 with a share of 42%. The solar active collector is calculated on a basis of 3 m2 of suitable roof area is equivalent to 1 m2 of suitable active collector area.

applications. Hereunder, a set of results concerning the relative distribution of potentially installable system size classes is given for the public building stock assessed.

Currently, more implementation relevant issues (e. g. age and stability of building roofs, construction work envisaged, legal and financial issues, social and communal acceptance and willingness, etc.) are under analysis in close collaboration with the municipalities concerned. More results will be published in a report later this year.

Le Potentiel Solaire dans le Canton de Geneve

Analyse et Evaluation du Potentiel Solaire — Photovoltai’que et Thermique — dans le Parc Immobilier Public du Canton de Geneve

Front picture of the future report on the solar energy potential in the Canton of Geneva.

JOSEPH MUTITU NDEGWA1 & MARY MUTHONI GITHINJI RURAL FRIENDS KENYA, P. O BOX 11987, 00400,

TOM MBOYA STREET; NAIROBI-Kenya.

E-mail: mary@lion. meteo. go. ke

Abstract

There is now a global acknowledgement and greater understanding of the depth and extent of poverty especially in the least developed countries whose consequences affect all people everywhere one way or the other. Over 1.2 billion human beings suffer extreme deprivation and lack even the most basic of life sustenance — food, water and shelter among others (World Bank, 2000; IFAD, 2001; DFID, 2001).

In Kenya, one of the poorest and heavily indebted countries in the world, majority of the people live in rural areas where their only means of livelihood is subsistence agriculture. Alternative means of livelihoods for the majority of poor people in rural areas are rare. Opportunities for economic advancement are scarce and rural infrastructure upon which development activities hinge does not exist or is in an unusable state. There is a general lack of rural industries even for processing of agricultural produce. This situation makes the well-being and the welfare of the rural people extremely appalling.

Energy is very essential for sustainable development in rural areas. Electricity supply in Kenya is confined mostly in major urban centres only. Poor people rely on unsustainable forms of energy sources mainly burning of wood for domestic needs such as lighting resulting in serious environmental and health consequences among them, desertification and internal pollution. The latter is a pre-cursor of prevalent asthmatic conditions. There is therefore an urgent and greater need to provide sustainable and affordable forms of renewable energy to poor people in rural areas for household use and to help stimulate development activities in information technology and other light agro-industries. We propose a credit scheme through a revolving fund to enable poor people access solar technology to meet their energy needs. We appeal for support from the international community in this initiative.

1. Introduction

Over the recent years much focus has been placed on the issue of poverty and sustainable development by the international community through various fora with many discourses over these issues. Major strides have therefore been achieved as exemplified by the development of the Millenium Development Goals (MDGs) and identification of steps needed to achieve the goals at the World Summit for sustainable Development in 2002. The MDGs envisages halfing the number of people living in abject poverty by the year 2015. Over 1.2 billion people are in this category, majority of them being in poor developing countries.

In Kenya, over half of the population estimated at 32 million live in abject poverty. Majority of these people live in rural areas engaged in subsistence farming as the only means of
livelihood. These people lack the most basic of necessities needed to attain a decent living standard. They lack adequate food, proper shelter, safe drinking water and proper health service among others. There are no opportunities to generate most needed income. These people are cut off from the current global developments in communication technology with an alarming widening digital divide.

There is therefore great challenge in the task of transforming the lives of such people in line with the objectives of achieving MDGs. The fight on poverty and attainment of sustainable development should focus on development of assets in terms of financial, natural, physical environmental and social resources. In each of these aspects, there exists great potential for utilization of renewable energy strategies to develop the livelihood assets for the poor people particularly in the rural areas. These could be in the area of food processing, cooking, and preservation that enhances quality and amounts available to overcome hunger and food poverty. Solar energy could also be used to enhance health through water sanitization. In another aspect solar energy can also be used in soil solarisation to control soil infection for proper crop production.

Other areas with potential to develop applying renewable energy strategies include domestic lighting, water heating, information and communication technology, for example rural radios, e-mail and internet services, TV and video telephony. Others applications could be in the area of small agricultural-based processing facilities, cottage industries and community health facilities.

An on-grid PV hybrid system has to show a lower FCR than that of the fossil firing power plants which feed the grid. Hence, full annual load of PV hybrid systems should not be recommended in general, unless generators with improved efficiencies are employed, which will permit extended hours of operation. Shown in the figure are three less steep, light dashed lines, which represent the use of CC of 60% (instead of a diesel or a Rankine cycle) for the PV hybrid. As expected, much better FCR and GREF values come out, which provide continued environmental benefits for extended hours. A 50% efficient combined diesel — Rankine system will exhibit intermediate lines (between the SEGS and CC lines). For each mode and strategy the related environmental benefits (as a function of the length of operation time) can be directly evaluated according to the system FCR and GREF by use of Figure 1.

The 60% level seems to offer a worthwhile standard for industrial countries with advanced power systems and grids and availability of gas. Tentatively, however, it seems that standards may be partially relaxed for particular locations due to specific conditions such as system size, availability of gas and distance from grid. Thence the secondary standard of 40% may come to play. It represents many power plants which exist to day and which continue to spread. Whatever GREF standards taken, they should always be transparent. It is obvious that a GREF related to a standard of 40% is numerically different from one related to a standard of 60%, which means also a difference in environmental contribution. The equations below will quantify the differences as a function of the specified standards.

If a PV system is going to be added to an existing, off-grid diesel or Rankine-cycle generator at an isolated, remote site, it seems be reasonable to consider the new PV output as green energy (GREF=1), independently of the conversion efficiency of the existing generator. However, when we plan to install a new hybrid system, which includes a new fuel firing subsystem, it is mandatory to raise the question of GREF and standards, in view of the global strategy for abating the global GHG (greenhouse gas) menace. Implementation of the strategy requires frequent scrutiny of on-going decisions about variety of ways in using fuel. These require the application of the yardsticks of FCR, GREF and cCa (cost of carbon avoidance, see below). Global strategy should encourage system refurbishment and installation of mini-grids at remote sites in order to enable improvement of generators efficiency. Fig. 1 and CCA (Equation 3) are useful for modelling off-grid PV hybrid systems as well.

At the beginning of simulation procedure, there are daily meteorological data (solar irradiance G and ambient temperature Ta) and load profiles (AC power PL) obtained by proper models. For each month an average day, characterised by the functions G(t), Ta(t) and PL(t), is defined.

The expression of global irradiance G (W/m2), derived for clear days, involves the parameters: daily irradiation as monthly mean value Hd (kWh/m2), daylight hours hi, peak value Gmax and shape factor cg. It is the normalised ratio between the peak value Gmax and the mean value Gmean = Hd/hl. The value of cG, for the same Gmean, determines the shape of the waveform: if cG=1, the waveform is sinusoidal; if cG>1, i. e. Gmax is higher than the sinusoidal peak value, the waveform is sharp. Different values of cG, for the same Gmean, determine different values of cell temperature TPV and PV energy. Then, the module over-temperature ATPV(t) with respect to the ambient temperature Ta(t) is evaluated by a linear function of irradiance, where the proportionality factor is the thermal resistance Rth between PV modules and ambient.

Proper mathematical models are used for each component: the equivalent circuits of the PV modules, of the batteries depending on the SOC and of the inverter depending on the losses at open circuit and load conditions. The main output is the reliability index.

Iph — /sclsrc

G

1000 3

[1 + aT (Tpv

— 298)]

I0 — I0Isrc

TPV 298

e-E,/kTpv

e-E,/k 298

(1) (2)

The I-U characteristics of a PV module are determined by a typical equivalent circuit of the solar cell. The parameters of the one-diode model are: ideal PV current generator Iph; reverse saturation current of the junction I0; quality factor of the junction m; shunt resistance Rsh and series resistance Rs. In this model, only the PV current and the reverse saturation current depend on G(t) and TPV(t):

where IscIstc and IoIstc are determined at Standard Test Conditions STC (G = 1000W/m2 with AM = 1.5, TpV=298K) and aT is the temperature coefficient of Isc, besides the band-gap Eg and the Boltzmann constant k. The parameters of the solar cell equivalent circuit are obtained at STC by the manufacturer l(U) characteristic of one module: in table 2 the open circuit voltage Uoc is reported rather than l0 which can be calculated in this condition by Uoc.

lph (A)	Uoc (V)	m	Rsh (Q)	Rs (fi)
5.4	0.58	1.34	1.0	0.002

Table 2

Concerning the battery model, already presented, it is necessary to note that SOC is determined by the actual current of battery lb, taking into account a charge-discharge efficiency ^b = 0.88 which decreases the charge storage. In presence of a voltage generator (battery), the operating point at DC frame is determined by the PV current during daylight and by the lamp load during the night: it is easy to compute PV energy EPV, load energy El and SOC, besides number of charge-discharge cycles Nc and corresponding LOLH. To achieve a good accuracy about the SOC evaluation, a time step of five minutes has been chosen.

Table 3 Month Epv (Wh) El (Wh) SOC Nc LOLH (h) Jan 390.4 390.0 0.41 4 70.3 Jul 264.8 227.5 0.96 0 0 Aug 295.0 257.8 0.95 0 0 Dec 259.9 398.7 0.34 8 159.4

Clear day in January Fig. 5. Simulation results for a winter day.

This procedure has been applied to the previous PV system, oriented in South direction with a tilt angle of 45° as prescribed by manufacturer, at latitude of 45° N in northern Italy (yearly irradiation of 1500 kWh/m2). The main results are presented in table 3 for some months, clarifying that LOLH occur in January and December, but an important waste of PV energy occurs in summer because SOC rises many times up to unity. Fig. 5 shows daily simulation results and fig. 6 reports the monthly variation of SOC in December.

1. Conclusions

The application of the simulation to a commercial road lighting PV system highlights that: in December and January it is not able to supply the load for all the night; the LOLH is higher than 200 h with a corresponding reliability index of 95% through the year; moreover a waste of PV energy in summer is too remarkable.

December Fig. 6. Simulation results of SOC for a winter month.

A greater tilt angle (60° — 65°), by increasing the PV energy in winter and reducing the same in summer, would enhance the reliability index and decrease the waste of PV energy; a theoretic study towards this goal is in developing phase.

Therefore this simulation is a useful tool in order to verify the sizing choice of PV power and battery capacity, usually based on an energy balance in a mean month.

[1]